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European Journal of Marketing Understanding how resource deployment strategies influence trade show organizers’ performance effectiveness Wondwesen Tafesse

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Article information: To cite this document: Wondwesen Tafesse , (2014),"Understanding how resource deployment strategies influence trade show organizers’ performance effectiveness", European Journal of Marketing, Vol. 48 Iss 5/6 pp. 1009 - 1025 Permanent link to this document: http://dx.doi.org/10.1108/EJM-06-2012-0342 Downloaded on: 06 September 2015, At: 06:54 (PT) References: this document contains references to 49 other documents. To copy this document: [email protected] The fulltext of this document has been downloaded 287 times since 2014*

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Understanding how resource deployment strategies influence trade show organizers’ performance effectiveness Downloaded by UiT Norges arktiske universitet At 06:54 06 September 2015 (PT)

Wondwesen Tafesse Bodø Graduate School of Business, The University of Nordland, Bodø, Norway

Resource deployment strategies 1009 Received 6 June 2012 Revised 21 April 2013 Accepted 7 May 2013

Abstract Purpose – The purpose of this study is to examine how the deployment of market-based resources influence trade show (TS) organizers’ performance effectiveness as measured with exhibitor and visitor attendance levels. To this end, the study synthesizes several market-based resources including TS longevity, TS webpage interactivity, industry association support, exhibition duration and exhibition area, and investigates how their deployments affect TS attendance levels. Design/methodology/approach – A cross-sectional dataset was compiled on 79 TSs by searching a variety of online sources. Organizers’ performance effectiveness was measured using TS attendance levels. The extent to which organizers deployed market-based resources was likewise quantified using hard data. A series of regression models was estimated to isolate the effect of the market-based resources on TS attendance levels. Findings – The results demonstrate the existence of positive relationships between market-based resources and TS attendance levels which are characterized by diminishing returns. More specifically, the authors found that as the amount of the deployment of the market-based resources increases, their incremental contributions to TS attendance levels become smaller. Practical implications – The findings offer comprehensive managerial insights about how organizers can improve their attendance levels by carefully deploying market-based resources. Originality/value – The few available works that try to address the question of why some TSs are well attended while others are not rely on the opinions of exhibitors and visitors. This study attempts to address the same question from the organizers perspective, and, in so doing, it contributes to the spares literature on TS management from the organizers perspective. Keywords Exhibitor attendance, Marketing resources, Trade show attendance, Trade show organization, Visitor attendance Paper type Research paper

1. Introduction Trade shows (TSs) generate substantial economic benefits for TS organizers as well as local businesses (Busche, 2005; Kirchgeorg et al., 2010). TS organizers make money from many sources including exhibitor registrations, visitor admissions, booth space rentals and sponsorships (Busche, 2005; Kresse, 2005). Local businesses also benefit financially from TS activities by supplying services to exhibitors and visitors such as accommodation, transportation and freight handling (Busche, 2005; Munuera and Ruiz, 1999). Because these economic impacts deepen as more number of exhibitors and visitors are attracted to TSs, TS organizers are keen to increase their TS attendance

European Journal of Marketing Vol. 48 No. 5/6, 2014 pp. 1009-1025 © Emerald Group Publishing Limited 0309-0566 DOI 10.1108/EJM-06-2012-0342

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levels, although not all of them succeed in their efforts. As Gopalakrishna et al. (2010) observed, “several trade shows debut every year [in the USA], but the number that were cancelled or postponed rose from 98 in 1995 to 221 in 2003” (p. 241). Despite the soaring TS failure rate, relatively little attention is paid to why some TSs are well attended while others are not. The few available works that try to address this question mainly rely on analysis of the opinions of exhibitors and visitors based on few, cherry-picked issues such as service quality (Berne and Gracia-Uceda, 2008; Gottlieb et al., 2011) and interaction quality (Hultsman, 2001; Smith et al., 2003). The findings indicate that exhibitors and visitors favorably rate TSs offering greater customer services (Berne and Gracia-Uceda, 2008; Gottlieb et al., 2011) and quality interaction opportunities (Hultsman, 2001; Smith et al., 2003). Although useful, these findings offer limited insights for TS organizers, as they cover specific issues and are derived principally from the opinions of exhibitors and visitors. As Gopalakrishna and Lilien (2012) recently noted, there is paucity of research on TS management issues directly from the organizers’ perspective (Gopalakrishna and Lilien, 2012). The purpose of this study is to contribute to the sparse literature on TS management from the organizers’ perspective by examining how resource deployment strategies influence TS organizers’ performance effectiveness. Because TS organizers’ performance effectiveness is shown to be reflected on their attendance levels (Whitfield and Webber, 2011), these were used to measure TS organizers’ performance effectiveness. The study then turned to the marketing resources literature (Fahy et al., 2006; Hooley et al., 2005; Srivastava et al., 1998) to identify market-based resources that are vital in the TS management context including reputational, customer linking and physical resource classes. These resource classes were measured through representative indicator resources. Synthesis of the indicator resources relied on: • conceptual and methodological criteria and resulted in the selection of TS longevity for reputational resources; • TS webpage interactivity and industry association support for customer linking resources; and • exhibition duration and exhibition area for physical resources. The study proceeded by developing hypotheses explicating the mechanisms by which the indicator resources contribute to TS attendance levels. Specifically, it is hypothesized that the indicator resources will have positive relationships with TS attendance levels, but these relationships will have diminishing returns. That is, as the deployments of the indicator resources intensify, their incremental contributions to TS attendance levels would become smaller. To test and validate the hypothesized relationships, a cross-sectional dataset was compiled on a sample of international TSs (n ⫽ 79) and a series of regression equations were estimated. The findings lend strong support to the majority of the hypothesized relationships and contribute to the rather sparse empirical literature on TS management from the organizers’ perspective. Taken together, the findings offer useful insights into how TS organizers can enhance their attendance levels by systematically deploying market-based resources. Next, the conceptual framework of the study will be introduced.


2. Conceptual framework The guiding assumption is that TS organizers attempt to fulfill the profit motive that drives their business by increasing their attendance levels (Whitfield and Webber, 2011). Building a large attendance base is necessary if TS organizers are to deepen the economic impact of their shows (Busche, 2005; Gopalakrishna and Lilien, 2012). However, this requires configuring supportive TS environments for exhibitors and visitors (Rosson and Seringhaus, 1995). By configuring supportive TS environments, TS organizers can expand their exhibitor and visitor base insofar as supportive TS environments result in satisfied exhibitors and visitors (Gopalakrishna et al., 2010; Gottlieb et al., 2011; Smith et al., 2003). In turn, satisfied exhibitors and visitors are likely to return to future editions and drawn in others through referrals (Smith et al., 2003). Therefore, TS organizers’ effectiveness in configuring supportive TS environments would eventually be reflected on their attendance levels (Whitfield and Webber, 2011). TS attendance levels could, thus, provide a reasonable quantitative proxy to TS organizers’ performance effectiveness, although these are by no means definitive measures. Following this line of reasoning, TS organizers’ performance effectiveness was quantified using TS attendance levels. As it is possible for TS organizers to perform well in attracting exhibitors but poorly in attracting visitors and vice versa, however, exhibitor attendance and visitor attendance were proposed as two separate metrics of organizers’ performance effectiveness (Hultsman, 2001; Rosson and Seringhaus, 1995). In their effort to configure supportive TS environments, TS organizers deploy different combinations of resources (Hultsman, 2001; Wu et al., 2008). Resources are the principal means by which TS organizers configure supportive TS environments for exhibitors and visitors (Gopalakrishna and Lilien, 2012). The question then is which assortments of resources would be useful for configuring supportive TS environments? The marketing resources literature has developed comprehensive discussions that could be applied toward addressing this question from a theoretical vantage point. The marketing resources literature has its root in the resource-based view of the firm, although it continues to develop as a predominantly marketing theory (Srivastava et al., 2001). Discussions in this literature are built around the central idea that market-based resources confer marketplace advantages (Hunt and Morgan, 1995; Srivastava et al., 1998; Vorhies et al., 1999). Market-based resources are defined to encompass the variety of marketing assets and capabilities that firms deploy to create attractive market offers (Day, 1994; Fahy et al., 2006; Hooley et al., 2005; Srivastava et al., 1998). But, as the full range of market-based resources that firms deploy to create attractive market offers is vast, scholars have suggested parsimonious classifications. For example, Srivastava et al. (1998) drew broader distinctions between relational and intellectual market-based assets. Relational assets characterize the relationship that firms have with their multiple partners including, among others, distributors, retailers, customers and suppliers. Intellectual assets typify the knowledge of firms about their competitive environment and the entities inside it, including competitors, customers, suppliers and other strategic interest groups. Hooley et al. (2005) presented a model of market-based resources with customer linking, reputation, market innovation and human resource dimensions. Customer-linking resources are the outside in capabilities making instant recognitions of customer needs possible. Reputational resources are those that assist the

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establishment of strong market credibility. Market innovations are the external and internal linkages and capabilities facilitating successful marketplace innovations. Human resource captures employees’ knowledge and skill sets. Day (1994) distinguished the capabilities embedded in market-driven organizations into three classes: (1) Inside-out capabilities are the internal processes needed to produce attractive market offers (e.g. manufacturing, human resources). (2) Outside-in capabilities are the external processes needed to make sense of the external environment (e.g. market sensing, customer linking). (3) Spanning capabilities are those needed to integrate the internal and external processes (e.g. customer service, product development). An additional classification of marketing capabilities can be found in Vorhies et al. (1999). It is worth considering some of the peculiarities of TS management here. First, TS management constitutes a set of activities that are temporally and spatially bounded (Hultsman, 2001; Stevens, 2005). Second, TS management involves serving the needs of several core customer groups simultaneously, often by creating values that are intangible and difficult to evaluate (e.g. networking and learning opportunities) (Rosson and Seringhaus, 1995). Third, TS management entails constantly interfacing with a number of core and peripheral actors including exhibitors, visitors, government departments, industry associations and service suppliers to successfully implement TS programs (Kresse, 2005). These idiosyncrasies suggest that certain market-based resource classes may be important in the context of TS management. In particular, reputational, customer linking and physical resource classes are expected to be critical. However, the deployments of these resource classes were captured through carefully synthesized indicator resources. The fact that reputational, customer linking and physical resource classes are defined with expansive scopes means (Day, 1994; Fahy et al., 2006; Hooley et al., 2005) that direct measurement efforts are difficult, making the use of indicator resources attractive. In synthesizing the indicator resources, both conceptual and methodological criteria were applied. The conceptual criterion calls for the indicator resources to share functional similarities with the distinguished resource classes so that the synthesized indicators accurately represent the distinguished resource classes. The methodological criterion calls for the indicator resources to be quantified with objective measures as motivated by the methodological choice of the study. Based on these two criteria: • TS longevity was selected to represent reputational resources; • TS webpage interactivity and industry association support were selected to represent customer-linking resources; and • exhibition duration and exhibition area were selected to represent physical resources. In the next section, hypotheses will be developed explicating the mechanisms by which the synthesized indicator resources influence TS attendance levels.


3. Hypotheses 3.1 Reputational resources (TS longevity) The marketing resources literature defines reputational resources as those resources that are capable of enhancing the credibility of the firm in the eyes of customers (Fahy et al., 2006; Hooley et al., 2005). Firm assets such as experience, service quality, product brands and superior promotional capabilities can all enhance firm reputation (Miles and Covin, 2000; Schwaiger, 2004). Reputational assets create competitive advantages primarily by increasing customers’ confidence about the market offers of firms (Nguyen and Leblanc, 2001). In the context of TS management, exhibitors and visitors may construct their perception of TS reputation using a variety of cues including TS longevity, organizers experience and exhibitors and visitors profile (Berne and Gracia-Uceda, 2008; Kijewski et al., 1993). For two reasons, this study proposed TS longevity as an indicator of TS reputation. First, TS longevity measures the number of years that TSs have been in existence, and as such, it could act as an ex-ante cue for credibility. For instance, exhibitors and visitors tend to view older TSs as more credible than newer ones (Bathelt and Schuldt, 2008). Second, TS longevity is easily quantifiable. For instance, it could be quantified by using the volume of past editions as was done in the present study. Regarding its effect on TS attendance levels, longevity is expected to have positive contributions. First, as TS management is evolutionary by nature, organizers behind older TSs are likely to accumulate rich management experience from executing successive TS editions in the past. Such experiences could become be a source of unique advantage in terms of staging successful TS editions in the future (Kijewski et al., 1993; Tafesse and Korneliussen, 2012). Second, TS longevity could help organizers boost their shows’ commercial and professional profile. As TS credibility grows with its longevity, organizers behind older TSs will find it easier to attract important industry actors whose presence at the fairground fosters learning and networking opportunities (Bathelt and Schuldt, 2008; Rosson and Seringhaus, 1995). However, the positive relationship between TS longevity and TS attendance levels is anticipated to exhibit diminishing returns. That is, as show longevity increases, its incremental contribution to TS attendance levels is anticipated to decline. Because new TSs are far more prone to postponements, cancellations and other types of risk factors than established ones (Gopalakrishna et al., 2010), longevity is anticipated to become more useful for assessing TS reputation during early stages. As TSs mature, however, the incremental reputational value of TS longevity would decline. H1a. TS longevity will have a positive relationship with exhibitor attendance, but there will be diminishing returns to this relationship. H1b. TS longevity will have a positive relationship with visitor attendance, but there will be diminishing returns to this relationship. 3.2 Customer-linking resources (TS webpage interactivity and association support) Both Day (1994) and Hooley et al. (2005) view customer-linking capabilities as assets that enable firms to discern customer needs promptly through interactive and collaborative efforts. Firm expertise in areas of customer interactions, customer collaborations and networking is seen as a relevant indicator of customer-linking capabilities (Vorhies et al., 1999). The significance of customer-linking capabilities for


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TS management cannot be overemphasized, as TS organizers have to increasingly interface with multiple market actors including exhibitors, visitors, government departments, industry associations and external service suppliers to successfully implement their programs (Gopalakrishna and Lilien, 2012; Kirchgeorg, 2005; Kresse, 2005). This study proposed interactive TS webpage and industry association support as indicators of organizers’ customer-linking capability. The view of webpage interactivity adapted in this study draws on a conceptualization which emphasizes the range of interactive technologies available on webpages (Coyle and Thorson, 2001; Ramirez and Burgoon, 2004). According to this conceptualization, a webpage is interactive when it possesses different technological features permitting users to engage in real-time exchange of information (Burgoon, et al., 2002; Ramirez and Burgoon 2004). Following this conceptualization, TS webpage interactivity was quantified by tallying the interactivity tools affixed to TS webpages including e-mail addresses, online registration, application form, social media plugins, FAQs and contact addresses. In the context of TS management, the value of interactive webpages lies in their ability to facilitate rich online interactions among exhibitors, visitors and organizers (Davidson et al., 2002; Egdar, 2002; Gopalakrishna and Lilien, 2012). On the one hand, interactive TS webpages allow TS organizers to learn about the profile, commercial interest and service needs of exhibitors and visitors. This knowledge could then be applied to develop customized services (Davidson et al., 2002; Gopalakrishna and Lilien, 2012). On the other hand, interactive TS webpages enable exhibitors and visitors to learn about the profile and commercial interests of each other. Based on this knowledge, both actors could align their respective goals and expectations (Davidson et al., 2002; Lee et al., 2008). However, this positive relationship between TS webpage interactivity and TS attendance levels is expected to exhibit diminishing returns. That is, the incremental contribution of TS webpage interactivity to TS attendance levels is expected to diminish as the level of TS webpage interactivity rises. When initial interactivity level is already high, adding a new interactivity tool can only create a small incremental effect on TS attendance levels due to duplication, for instance. But, when initial interactivity level is low, adding a new interactivity tool will have a more pronounced incremental effect on TS attendance levels as the newly added tool can fill existing interactivity gaps. H2a. TS webpage interactivity will have a positive relationship with exhibitor attendance, but there will be diminishing returns to this relationship. H2b. TS webpage interactivity will have a positive relationship with visitor attendance, but there will be diminishing returns to this relationship. Industry association support, the second indicator resource for TS organizers customer-linking capability, represents the backings that industry associations offer to TS organizers in the form of endorsements, sponsorships, ownerships and participations at TSs as exhibitors or visitors (Kresse, 2005; Rice, 1992; Rosson and Seringhaus, 1995). Following this, industry association support was quantified by tallying the number of industry associations that endorsed, sponsored, owned and participated at the TSs. Industry association support is instrumental in organizing TSs successfully, as industry associations maintain strong linkages with relevant market actors as well as policymakers (Berne and Gracia-Uceda, 2008; Kresse, 2005). TS


organizers could exploit these market and political linkages to enhance the profile of their TSs and, consequentially, attendance levels (Kresse, 2005). For instance, TS organizers could enhance their industry and policy profile by partnering with relevant industry associations having proper connections (Kresse, 2005; Rosson and Seringhaus, 1995). TS organizers could also acquire highly qualified exhibitors and visitors via the publicity efforts of industry associations (Berne and Gracia-Uceda, 2008; Rice, 1992). However, this positive relationship between industry association support and TS attendance levels is expected to exhibit diminishing returns. That is, the incremental contribution of industry association support to TS attendance levels is expected to diminish as the level of industry association support rises. When initial association support level is high, bringing a new industry association on board will only create a small incremental effect on TS attendance levels due to duplication, for instance. But, when initial association support level is low, bringing a new industry association on board will have a more pronounced incremental effect on TS attendance levels through filling existing association support gaps. H3a. Industry association support will have a positive relationship with exhibitor attendance, but there will be diminishing returns to this relationship. H3b. Industry association support will have a positive relationship with visitor attendance, but there will be diminishing returns to this relationship.

3.3 Physical resources (exhibition duration and exhibition area) It is a well-established premise that control over key physical assets such as manufacturing plants, servicescapes and information infrastructures represents an important source of firm competitive advantage (Barney, 1991; Grant, 1991; Hunt and Morgan, 1995). TS management is not an exception in this respect, as possession over physical resources equips TS organizers with a superior ability to configure supportive TS environments for exhibitors and visitors (Gottlieb et al., 2011; Kirchgeorg, 2005). As noted earlier, however, TS management constitutes a set of activities that are bound by time and space (Berne and Gracia-Uceda, 2008; Hultsman, 2001). In recognition of this unique temporal and spatial boundedness of TS management, this study proposed physical indicator resources with temporal and spatial features: exhibition duration and exhibition area. Exhibition duration can be conceptualized as the total amount of time that TSs are kept open to visitors (Hultsman, 2001). Based on this conceptualization, exhibition duration was here quantified as a product of the number of exhibition days per edition and the number of exhibition hours per each exhibition day. A positive relationship between exhibition duration and TS attendance levels is expected for the following reasons: • First, longer shows could attract more exhibitors, as such shows enable exhibitors to carry out a number of important activities such as image building and customer relationship building for an extended period. In turn, this, maximizes exhibitors’ return on their fixed costs (Hultsman, 2001). • Second, longer shows could attract higher number of visitors, as such shows afford more flexible visiting hours (Berne and Gracia-Uceda, 2008; Hultsman, 2001).



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• Third, longer shows are less likely to become overcrowded, as visitors would normally be spread out along the shows’ extended durations.

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However, this positive relationship between exhibition duration and TS attendance levels is anticipated to be subject to the law of diminishing returns. That is, as exhibition duration increases, the incremental contribution of exhibition duration to TS attendance levels is anticipated to decline. The reason is interest and enthusiasm about TSs, which is instrumental in attracting a steady stream of visitors, that would start to wane as the TSs drag on for several days. This, in turn, may prompt exhibitors to avoid relatively longer TSs. H4a. Exhibition duration will have a positive relationship with exhibitor attendance, but there will be diminishing returns to this relationship. H4b. Exhibition duration will have a positive relationship with visitor attendance, but there will be diminishing returns to this relationship. This study followed the example of previous studies in quantifying exhibition area using square meters of total floor space covered by TSs. However, previous studies applied this measurement at the individual exhibitor level, while this study applied it at the aggregate level (Dekimpe et al., 1997; Gopalakrishna and Lilien, 1995). A positive relationship between exhibition area and attendance levels is expected for the following reasons: • First, larger exhibition areas facilitate efficient interactions and exchanges by providing exhibitors and visitors with convenient physical spaces (Gottlieb et al., 2011; Kirchgeorg, 2005). • Second, TS organizers deploying larger exhibition areas are better able to satisfy exhibitors’ specific booth design and location preferences, allowing exhibitors to set up their exhibit booths as they wish. • Third, larger exhibition areas create efficiencies and save logistical costs for exhibiting firms (Kirchgeorg, 2005; Tafesse and Korneliussen, 2012). However, this positive association between exhibition area and TS attendance levels is expected to exhibit diminishing returns. That is, as an exhibition area increases, its incremental contribution to TS attendance levels is expected to decline. Adding more space to an already large exhibition area may have the unintended consequence of fragmenting the configuration of the fairground. This may then reduce the rich exchange and interaction opportunities facilitated by an otherwise compact fairground (Power and Jansson, 2008). H5a. Exhibition area will have a positive relationship with exhibitor attendance, but there will be diminishing returns to this relationship. H5b. Exhibition area will have a positive relationship with visitor attendance, but there will be diminishing returns to this relationship. 4. Model specification To test the proposed hypotheses, it is important to convert the underlying relationships into appropriate statistical tests. As discussed in the forgoing section, the indicator

resources are hypothesized to have positive relationships with TS attendance levels, but with diminishing returns. These types of positive relationships characterized by diminishing returns could be tested by using double-log regression. Statistically significant double-log coefficient estimates lying between 0 and 1 offer evidence of positive relationships characterized by diminishing returns (Hill et al., 2011). With this in mind, the indicator resources are related to exhibitor attendance and visitor attendance using the double-log specification: ln(EXH) ⫽ ␤0 ⫹ ␤1ln(LON) ⫹ ␤2ln(WEB) ⫹ ␤3ln(IND) ⫹ ␤4ln(DUR) Downloaded by UiT Norges arktiske universitet At 06:54 06 September 2015 (PT)

⫹ ␤5ln(AREA) ⫹ ␮

(1)

ln(VIS) ⫽ ␤0 ⫹ ␤1ln(LON) ⫹ ␤2ln(WEB) ⫹ ␤3ln(IND) ⫹ ␤4ln(DUR) ⫹ ␤5ln(AREA) ⫹ ␮

(2)

where, EXH ⫽ number of exhibitors; VIS ⫽ number of visitors; ␤j ⫽ parameters to be estimated (j ⫽ 0…,5); LON ⫽ count of past editions; WEB ⫽ count of TS webpage interactivity tools; IND ⫽ count of supporting industry associations; DUR ⫽ amount of exhibition duration in hours; AREA ⫽ amount of exhibition floor space in square meters; and ␮ ⫽ error term. It is widely reported that visitor orientation and industry coverage influence the size and composition of TS attendances (Dekimpe et al., 1997; Gopalakrishna and Williams, 1992; Wu et al., 2008). Visitor orientation is about whether TSs are open to the general public (b2c) or only to trade and professional visitors (b2b), while industry coverage is about whether TSs cover many unrelated industry types (horizontal) or few related industry types (vertical) (Kirchgeorg, 2005; Tafesse et al., 2010). Visitor orientation is anticipated to systematically affect visitor attendance such that b2c TSs will attract more visitors than b2b TSs because b2c TSs target trade visitors, professional visitors and the general public, while b2b TSs target only trade and professional visitors. Industry coverage, on the other hand, is anticipated to influence both exhibitor and visitor attendances such that horizontal TSs will attract higher number of exhibitors and visitors than vertical TSs. This is because horizontal TSs are targeted at a wide range of industries, and hence, they have wider market appeals. Visitor orientation and industry coverage were measured as dichotomous variables reflecting the aforementioned categories. To control for their effect on TS attendance levels, they were dummy coded and entered as covariates (i.e. visitor orientation [VO] ⫽ 0 if the TS is b2c, 1 if the TS is b2b; industry coverage [IC] ⫽ 0 if the TS is vertical, 1 if the TS is horizontal). In addition, the effect of exhibit fee (FEE) on exhibitor attendance was controlled. Exhibit fee influences exhibitor attendance, as it represents a large portion of the total exhibiting cost. Exhibit fee was constructed as a continuous variable by summing up registration fee, booth rental rates per square meters and other mandatory fees and was standardized across TSs using US dollars. With these enhancements, equations (1) and (2) become: ln(EXH) ⫽ ␤0 ⫹ ␤1ln(LON) ⫹ ␤2ln(WEB) ⫹ ␤3ln(IND) ⫹ ␤4ln(DUR) ⫹ ␤5ln(AREA) ⫹ ␤6(IC) ⫹ ␤7(FEE) ⫹ ␮

(3)


ln(VIS) ⫽ ␤0 ⫹ ␤1ln(LON) ⫹ ␤2ln(WEB) ⫹ ␤3ln(IND) ⫹ ␤4ln(DUR)

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Table I. Descriptive statistics (n ⫽ 79)

(4)

⫹ ␤5ln(AREA) ⫹ ␤6(IC) ⫹ ␤7(VO) ⫹ ␮

5. Description of empirical data This study used, as a sampling frame, an online database compiled by the leading TS Web site biztradeshows.com. This comprehensive database stores information on thousands of TSs and sorts them by industry, by country, by venue and by date. But, because the quantity of TSs in the database is too large to allow an efficient random sampling procedure, convenience sampling was applied to select individual TSs. Multiple steps were taken to systematize the sampling and data collection process. First, countries from which individual TSs will be drawn were selected. The selection of the countries was such that the resultant sample reflected a composition of globally important TS host countries (see the paragraphs below for the countries selected). By selecting TSs from several globally important TS host countries, the study sought to report findings that could be generalized across heterogeneous market contexts. Second, individual TSs from the sampled countries were selected, and pertinent information regarding their latest editions was collected from multiple online sources. The latest editions of all the selected TSs took place between 2010 and 2012. Relevant details pertaining to each TS edition were collected from multiple sources including TS webpages, TS organizer webpages, trade and industry association webpages and government department webpages, among others. As the full range of information required to assemble a complete data set for each TS edition was seldom available from a single online source, multiple information sources had to be consulted. Third, even after exhausting these sources, there would be missing information on some of the selected TSs. In these cases, concerned organizers would be contacted through emails to comment on the missing items. Most contacted organizers replied to email requests within a reasonable period of time. Those TSs whose organizers failed to reply were replaced by other comparable TSs. Using the above steps, a cross-sectional data set on 79 TSs was compiled. In terms of industry coverage, about a third of the TSs were horizontal (29 per cent), while the rest of the TSs were vertical (70 per cent). In terms of visitor orientation, about half of the TSs (52 per cent) were b2b, while the other half (48 per cent) were b2c. In terms of country of origin, the selected TSs were based in Germany (17 per cent), China (13 per cent), Italy (12 per cent), the Gulf States (10 per cent), the USA (9 per cent), India (8 per cent), Turkey (6 per cent), Scandinavia (5 per cent), Brazil (5 per cent), South Africa (5 per cent) and

Variables

Unit of measurement

Notations

Mean

SD

Minimum

Maximum

Exhibitor attendance Visitor attendance TS longevity TS webpage interactivity Industry association support Exhibition duration Exhibition area Exhibit fee

Number of exhibitors Number of visitors Count of past editions Count of interactivity tools Count of supporting industry associations Hours Square meters US dollar

EXH VIS LON WEB IND

1,010 72,074 23 3.38 8.77

1,815 176,473 23.3 0.965 10.174

45 1,462 1 1 0

111,63 1,500,000 100 5 54

DUR AREA FEE

36.9 74,178 675

17.04 156,880 510

14 1,320 50

100 1,100,000 2,600


other countries (9 per cent). With respect to measurement, all the variables of interest were quantified using objective measures. Summary statistics are provided in Table I. A quick run through Table I indicates that the sample is slightly skewed toward established and larger TSs. But there is also substantial variability in the sample in terms of both TS attendance levels and intensity of resource deployments. For instance, the sample consists of both leading global events (e.g. World Travel Market from the UK) and niche national events (e.g. Smak from Norway). Before estimating equations (3) and (4), the data were checked for assumptions of linearity, heteroscedasticity and normality. Analyses of the residual plots indicate that the standardized residuals of both dependent variables, i.e. ln(EXH) and ln(VIS), were randomly scattered about the horizontal line with no detectable systemic patterns. The normal probability plots of both dependent variables also show that the standardized residuals fell close to the diagonal line without any substantial deviation. Multicollinearity was not an issue either. First, none of the independent variables were highly correlated with each other. In fact, the maximum value in the correlation matrix of independent variables was 0.45. Second, the variance inflation factors were substantially lower than 10 which is an often used cutoff (Hair et al., 2010). The maximum variance inflation factor was 0.961 in the exhibitor model and 0.989 in the visitor model.


6. Findings and discussion 6.1 Hypotheses testing Equations (3) and (4) are estimated using ordinary least squares regression. Table II summarizes the estimation results. The exhibitor model achieves a good fit (R2 adjusted ⫽

Main variables

ln(EXH) Parameters ␤ (t-values)

ln(LON)

␤1

ln(WEB)

␤2

ln(IND)

␤3

ln(DUR)

␤4

ln(AREA)

␤5

Control variables IC

␤6

FEE

␤7

R2 R2 adjusted F ratio Notes: ** p ⬍ 0.05, *** p ⬍ 0.01

0.28 (3.683***) 0.15 (2.022**) 0.21 (2.735***) ⫺0.04 (0.599) 0.37 (4.459***) 0.28 (4.093***) ⫺0.19 (⫺2.739**) 0.704 0.674 23.77***

Main variables

ln(VIS) Parameters ␤ (t-values)

ln(LON)

␤1

ln(WEB)

␤2

ln(IND)

␤3

ln(DUR)

␤4

ln(AREA)

␤5

Control variables IC

␤6

VO

␤7

0.1 (1.315) 0.16 (2.212**) ⫺0.039 (⫺0.521) 0.25 (3.361***) 0.52 (6.328***) 0.17 (2.41**) ⫺0.18 (⫺2.584**) 0.708 0.679 24.59***

Table II. Estimation results of equations (3) and (4) (n ⫽ 79)

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0.67) and confirms all but one of the hypothesized relationships. As hypothesized, exhibitor attendance has positive relationships with TS longevity, TS webpage interactivity, industry association support and exhibition area. Diminishing returns are also found to these relationships, as evidenced by the statistically significant double-log coefficient estimates lying between 0 and 1 for TS longevity (␤1 ⫽ 0.28, p ⬍ 0.01), TS webpage interactivity (␤2 ⫽ 0.15, p ⬍ 0.05), industry association support (␤3 ⫽ 0.21, p ⬍ 0.05) and exhibition area (␤5 ⫽ 0.37, p ⬍ 0.01). These findings offer strong support for H1a, H2a, H3a and H5a, respectively, and reinforce the argument that market-based resources enhance exhibitor attendance by conferring reputational, customer linking and efficiency advantages for TS organizers. However, the incremental contributions of these resources to exhibitor attendance declined as the amount of their deployment rises. Contrary to what was predicted in H4a, exhibition duration has no significant effect on exhibitor attendance (␤4 ⫽ ⫺0.04, p ⫽ 0.60). It thus appears that exhibition duration is not an important TS attendance criterion from exhibitors’ point of view. Finally, the two covariates in the exhibitor model are significant. The industry coverage covariate is significant (␤6 ⫽ 0.28, p ⬍ 0.01), and, as expected, horizontal TSs attracted more exhibitors than vertical TSs. Similarly, the exhibit fee covariate is significant (␤7 ⫽ ⫺0.19, p ⬍ 0.01), and, as expected, higher exhibit fees lead to lower exhibitor attendances. The visitor model likewise achieves a good fit (R2 adjusted ⫽ 0.68) and confirms three of the five proposed relationships. As hypothesized, visitor attendance has positive relationships with TS webpage interactivity, exhibition duration and exhibition area. Diminishing returns are also found to these relationships, as evidenced by the statistically significant double-log coefficient estimates lying between 0 and 1 for TS webpage interactivity (␤2 ⫽ 0.16, p ⬍ 0.05), exhibition duration (␤4 ⫽ 0.25, p ⬍ 0.01) and exhibition area (␤5 ⫽ 0.52, p ⬍ 0.01). These findings offer strong support for H2b, H4b and H5b, respectively, and strengthen the argument that these resource variables help to attract more visitors by facilitating interactions and affording conveniences. Nevertheless, these efficiency and convenience advantages declined as the deployment of the corresponding resources intensified. Contrary to what was predicted in H1b, TS longevity fails to impact visitor attendance positively (␤1 ⫽ 0.1, p ⫽ 0.19). This may be an indication that visitors evaluate the reputation of TSs by using factors other than longevity such as exhibitors’ profile, TS organizers’ experience or word of mouth. The exact source of reputational cue from the visitors’ perspective needs to be investigated in the future. Similarly, contrary to H3b, industry association support fails to help increase visitor attendance (␤3 ⫽ ⫺0.04, p ⫽ 0.60). This could be because industry associations do not have the same level of relationships with visitors as they have with exhibitors. For instance, consumer visitors who make up a significant part of the visitor base for many TSs are seldom members of industry associations, as association membership is often reserved for institutional actors. Finally, both covariates in the visitor model are statistically significant. The industry coverage covariate is statistically significant (␤6 ⫽ 0.17, p ⬍ 0.05), supporting the idea that horizontal TSs attract more visitors than vertical TSs. Similarly, visitor orientation is statistically significant (␤7 ⫽ ⫺0.18, p ⬍ 0.05), and, as expected, b2c TSs attracted more visitors than b2b TSs.


6.2 Managerial implications The findings reported in the forgoing section undoubtedly demonstrate the instrumentality of market-based resources in TS management contexts. Market-based resources explained close to 70 per cent of the variance in TS attendance levels. The significant impact of market-based resources on TS attendance levels has to do with the various advantages that these resources confer to TS organizers in terms of configuring supportive TS environments. Particularly, market-based resources consisting of reputational (TS longevity), customer linking (industry association support, webpage interactivity) and physical resources (exhibition duration and exhibition area) were found to be critically important. Therefore, TS organizers could anticipate enhancing their attendance levels by capitalizing on these market-based resources. First, TS organizers could increase the number of exhibitors by highlighting the longevity of their show in promotional and interfacing works. Longevity enhances exhibitor attendance by acting as a cue for TS reputation. Exhibitors are gravitated toward established TSs, as these are perceived as more reputable and less risky. Second, TS organizers could leverage industry association support to boost the number of exhibitors. TS organizers could tap into the extensive market and policy linkages of industry associations to enhance their industry and policy profile as well to access a vast pool of qualified exhibitors. However, this strategy of increasing the number of exhibitors through industry associations would be particularly fruitful when existing levels of association support is small. Third, TS organizers could increase the number of exhibitors and visitors by improving the interactivity of their webpages. Interactive TS webpages contribute to TS attendance levels by facilitating learning and efficient information exchanges. However, this strategy of improving TS webpage interactivity to increase the number TS attendance levels would be more effective when the initial level of TS webpage interactivity is low. Fourth, TS organizers could increase the number of exhibitors and visitors by increasing their shows’ duration and floor space. TSs with relatively longer durations are particularly attractive for visitors, as these afford flexible visiting schedules. Similarly, TSs with relatively larger exhibition floors attract more exhibitors and visitors because such shows provide convenient spaces for interactions and exchanges. However, when TSs have high initial levels of show hours and floor spaces, adding more of these resources will only have smaller incremental effects on TS attendance levels due to diminishing returns. 6.3 Performance tests and future research Two tests were conducted to check the performance of the double-log specification in equations (3) and (4). First, the performance of the double-log specification was compared against an alternative semi-log specification, where the two dependent variables were log transformed, while the independent variables and the covariates assumed their original values. The performance comparison was conducted by computing adjusted R2 as fit statistics. In both the exhibitor and visitor models, the double-log specification yielded a much higher fit (adjusted R2 exhibitor ⫽ 0.67; adjusted R2 visitor ⫽ 0.68) than the semi-log specification (adjusted R2 exhibitor ⫽ 0.49; adjusted R2 visitor ⫽ 0.49). Therefore, in terms of fit statistics, the double-log specification is superior. Second, the predictive performance of the double-log specification was compared against the semi-log specification on a holdout sample (n ⫽ 21). The observations in the


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holdout sample were collected using the same procedures described earlier but were excluded from the estimation sample (n ⫽ 79). The predictive performance of the two alternative specifications was assessed by computing root mean square error (RMSE) and mean absolute error (MAE) (Ebbes et al., 2011). In both the exhibitor and visitor models, the RMSE (exhibitor ⫽ 0.356; visitor ⫽ 0.328) and the MAE values (exhibitor ⫽ 0.262; visitor ⫽ 0.285) for the double-log specification were smaller than the corresponding RMSE (exhibitor ⫽ 0.369; visitor ⫽ 0.454) and MAE values (exhibitor ⫽ 0.285; visitor ⫽ 0.402) for the semi-log specification. Therefore, in terms of predictive validity, the double-log specification is again superior. In the remainder of this section, limitations of the study will be pointed out and directions for future research formulated. First, this study inherited some of the limitations of its theory base. An often-raised weakness of the marketing resource literature is its inability to conclusively resolve the direction of causality between market-based resources and firm performance (Gibbert et al., 2006; Lockett et al., 2009; Priem and Butler, 2001). This limitation is more acutely felt in models designed to estimate the effect of different market-based resources on firm performance (Gibbert et al., 2006; Vorhies et al., 1999). Such models often prompt the question of is it the deployment of market-based resources that leads to higher firm performance or higher firm performance that leads to the ability to deploy market-based resources? This question directly applies to some of the current indicator resources, especially to TS longevity and exhibition area. Consequently, considerations of reverse causality deserve further attention in future research. For instance, an argument of reversed causality could be made, suggesting that higher TS attendance levels are what drive TS longevity and not the other way around. To the extent that TS attendance levels from previous editions keep TSs going into future editions, this argument has some merit. A similar argument of reversed causality can be made against exhibition area, suggesting that higher TS attendance levels are what drive exhibition area and not the other way around. Because the data set employed here was cross-sectional, it was not possible to conduct further analyses to verify the direction of causality implied above Therefore, these issues need to be resolved in the future using a longitudinal dataset. In addition to the issue of reverse causality, this study considered only those indicator resources that were readily measured with hard data and excluded those that did not meet this criterion such as TS organizers’ management experience and promotional capabilities. By applying alternative methodological designs, like multi-item survey responses, future research could determine the effect of the forgoing resources on TS attendance levels. Finally, this study ascertained TS organizers’ performance effectiveness using TS attendance figures from a single edition. As one of the anonymous reviewers pointed out, changes in TS attendance levels between two or more successive editions could serve as a more robust measure of performance effectiveness. This is a valid point, and future research might follow this approach for more robust results. References Barney, J. (1991), “Firm resources and sustained competitive advantage”, Journal of Management, Vol. 17 No. 1, pp. 99-120.


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