Optimizing the Contact Efficiency in
Trade Shows through Chronic and
Situational Regulatory Fit
Abstract
Gopalakrishna & Lilien (1995) developed a three-stage model of trade show
performance, relying on different indices of performance at each stage: attraction,
contact, and conversion efficiency. However, extant trade show literature neglects to
address the relationship between exhibitors and visitors in a detailed way. Specifically,
previous studies attribute superior trade show performance to plentiful resources and
appropriate evaluations, but fail to address the influence of contact efficiency, which
plays the consequential role for deciding the success or failure of a trade show
performance. This study adopts the regulatory focus perspective and extends the
literature by proposing a regulatory fit effect on trade show contact efficiency in terms
of visitors’ chronic and situational regulatory focus. Overall, the empirical evidence
supports chronic regulatory focus as having a greater influence on contact efficiency
than situational regulatory focus. One major managerial implication for exhibitors is a
possible reallocation of its trade show marketing resources to exploit greater contact
efficiencies by anticipating visitors’ chronic regulatory focus.
Key words: Trade show; Performance; Contact efficiency; Chronic regulatory focus;
Situational regulatory focus.
1. Introduction
Trade shows are important promotional tools for marketing many products and
services. The Global Association of the Exhibition Industry (UFI) (2007) revealed
that the exhibition industry is still expanding. Regional, national, and international
trade shows constitute an international multibillion-dollar industry. The strong growth
associated with the use of trade shows as a substantial part of business marketers’
communication mix has placed increased decision making pressure on management to
determine the optimal number of shows to attend, which shows to attend, and how to
accurately assess the success of participating in a show (Blythe, 2002; Godar &
O'Connor, 2001; Smith, Hama, & Smith, 2003).
Regardless of the importance of trade shows, the research on factors or
relationships which influence trade show performance is still limited (Dekimpe,
François, Gopalakrishna, Lilien, & Bulte, 1997; Hansen, 2002; Kerin & Cron, 1987;
Li, 2007; Smith et al., 2003). Discussion about psychological factors involved in
buyer/seller contact is especially lacking. As these factors exert a great influence,
thorough research on buyers’ psychological states in trade show environments could
be important for making trade shows more successful.
Gopalakrishna & Lilien (1995) developed a three-stage model of trade show
performance, relying on different indices of performance at each stage; attraction,
contact, and conversion efficiency. The first stage of the model represents the
“attraction efficiency” of the booth. The attraction efficiency measures how
effectively the exhibitors attract target visitors. The second stage involves the contact
established by the booth staff with the interested visitor. This stage involves the
performance of the booth personnel, referred to as “contact efficiency.” In the third
stage, establishment of sales leads were addressed. A lead is a potential sale as
indicated by the visitor’s interest in a follow-up sales visit from the seller. Leads can
originate from existing as well as from new customers. Effectiveness here is termed
“conversion efficiency,” which reflects the ability of the salespeople to turn a contact
into a lead.
Among these, contact efficiency is not only the retention of attendees who are
attracted by exhibitors, but also the further business opportunity through comfortable
impersonal contact. The average contact at a busy show may last only 3 to 5 minutes
and a salesperson might interact with 20 or more prospective customers in an hour
(Resnick, 1991). Booth staff must effectively separate “lookers” from “buyers.” Most
importantly, the goal is effective interaction with attendees in such a short period of
time. This ultimately determines whether a buyer will seek ongoing contact with an
exhibitor, thereby developing into a sales lead. Despite the importance of this process,
however, previous literature had not put adequate focus on contact efficiency to
discover how these short contact windows can be optimized to improve trade show
performance.
In this paper we therefore carefully examine contact efficiency, employing the
theory of regulatory focus. We manipulated a trade show contact stage by creating
two presentations for representatives of different firms; potential “buyers” were
exposed to these presentations. By examining the choice of firm with which test
participants express an interest in ongoing contact, we can explore how the chronic
and situational regulatory fit effects on buyers affect contact efficiency.
2. Regulatory focus－chronic and situational
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Higgins (1997, 1998) developed the regulatory focus theory, which describes
important differences in the processes through which people approach pleasure and
avoid pain. Chronic personality characteristics such as the extent as well as the
accessibility of discrepancies between (1) the actual and ideal selves (as measures of a
chronic tendency to self-regulation with a promotion focus), and (2) the actual and
ought selves (as measures of a chronic tendency to self-regulation with a prevention
focus) determine the latent activation levels of promotion and prevention mechanisms,
respectively (Higgins, Klein, & Strauman, 1985; Higgins, Shah, & Friedman, 1997).
Self-regulation mechanisms can be experimentally induced by (1) rendering
positive (gain) or negative (loss) outcomes salient (Roney, Higgins, & Shah, 1995;
Shah, Higgins, & Friedman, 1998), (2) activating knowledge structures that are
related to nurturance needs or security needs (e.g., Friedman & Förster, 2001), (3)
priming the standards (ideals vs. oughts) with which people try to bring themselves
into alignment (Freitas, Liberman, & Higgins, 2002; Higgins, Bond, Klein, &
Strauman, 1986), and/or (4) activating approach or avoidance motor actions (Forster,
Higgins, & Idson, 1998; Friedman & Förster, 2001).
Chronic regulatory focus
Regulatory focus theory (see Higgins, 1997, 1998) proposes the existence of
distinct regulatory systems that are concerned with acquiring either nurturance or
security through goal attainment. Individuals’ self-regulation in relation to their hopes
and aspirations (ideals) satisfies nurturance needs. The goal is accomplishment and
the regulatory focus is promotional. Success and failure in a promotion focus are
experienced as the presence of positive outcomes (gains) and the absence of positive
outcomes (nongains), respectively. Individuals’ self-regulation in relation to their
duties and obligations (oughts) satisfies security needs. The goal is safety and the
regulatory focus is preventive. Success and failure in a prevention focus are
experienced as the absence of negative outcomes (nonlosses) and the presence of
negative outcomes (losses), respectively.
3. Chronic regulatory focus and contact efficiency
Applied to the matter at hand, consumers’ attitudes toward a product are more
favorable when its benefits fit their regulatory goals (Aaker & Lee, 2001; Cesario,
Grant, & Higgins, 2004). Higgins (2000) has described how people actually assign
greater monetary value to a chosen object when environmental cues induce a choice
process which is more congruent with their dispositional tendencies toward either a
promotion or prevention focus—independent of the value of the object itself. Also,
decision makers with different regulatory orientations value their decisions more
when they use decision strategies that suit their regulatory orientation (Avnet &
Higgins, 2003; Camacho et al., 2003; Higgins et al., 2003). Since prevention-focused
buyers’ behaviors are characterized by avoidance of losses and negative outcomes,
they will typically be drawn by exhibits having a prevention-focus for a new product
purchase. In contrast, promotion-focused buyers tend to focus on gains and thus may
be relatively more interested in exhibits featuring a promotion-focus.
H1. Promotion-focused buyers are more likely than prevention-focused buyers to
effectively contact exhibitors whose presentations are promotion-focused.
Conversely, prevention-focused buyers are more likely than promotion-focused
buyers to effectively contact exhibitors whose presentations are
prevention-focused.
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4. Situational regulatory focus and contact efficiency
Regulatory focus is determined both by situational and chronic factors (Higgins,
1997, 1998). Kark & Dijk (2007) proposed that situational regulatory focus can be
defined by work context characteristics including industrial environment (dynamic or
stable), and organizational structure (organic or mechanical). As inferred above
concerning a person’s choice process, the buyer employs the self-regulatory behavior
and adjusts the process of choosing a new supplier in accordance with situational
factors in a trade show setting; that is, buyers would modify their choices in accord
with situational regulatory focus, elicited by industrial and organizational contexts. As
a result, situational regulatory focus effect should influence contact efficiency and we
discuss the following situational regulatory foci, including external and internal
factors, which affect contact efficiency in a trade show setting:
5.1. External index: Environmental uncertainty
External factors affect whether people adopt more of a promotion versus
prevention focus (Brockner & Higgins, 2001). One external index by which buyers
make the contact choice is environmental uncertainty. In situations in which a firm’s
best course of action is unclear, imitating the behavior of other firms within their
network provides a low-cost solution to that uncertainty (Henisz & Delios, 2001).
Cost means loss for buyers and uncertain environments tend to make buyers do the
non-loss (prevention) strategy, as when they purchase directly from customers’ orders
in order to curtail risk. On the contrary, in the stable environment, buyers use gain
(promotion) strategies to obtain additional profit, as when they purchase in
anticipation of customer demand. Thus, buyers in highly uncertain environments were
motivated by prevention-focused presentations, and buyers in relatively certain
environments were motivated by promotion-focused presentations.
H2a. Buyers are more likely to maintain contact with exhibitors whose presentations
are promotion-focused when environmental uncertainty is low. Conversely,
buyers are more likely to maintain contact with exhibitors whose presentations
are prevention-focused when environmental uncertainty is high.
5.2. Internal index: formalization
Internal factors involving the buyer’s firm can also affect the buyer’s contact
choice, and are also taken into account in our research. First we’ll look at
formalization in the buyer’s firm.
Contextual variables are likely influential (Roney et al., 1995); for example,
organizational designs and structures that are characterized by a dynamic, change
oriented, and organic structural form correlate to a promotion-oriented context. In
comparison, organizational designs and structures that are characterized by a
mechanistic and bureaucratic structure that stresses the importance of rules,
regulations, stability, and standardization correlate to a prevention-oriented context
(Kark & Dijk, 2007); that is, the degree of formalization can affect regulatory
oriention. Hence, relying on the regulatory fit effect, it can be expected that buyers
from highly formalized organizational contexts are naturally motivated by
prevention-focused presentations, and buyers from relatively unformalized
organizational contexts are motivated by promotion-focused presentations.
H2b. Buyers from low formalized organizations can be expected to achieve higher
contact efficiencies with exhibitors whose presentations are promotion-focused;
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conversely, buyers from highly formalized organizations can be expected to
achieve higher contact efficiencies with exhibitors whose presentations are
prevention-focused.
5.3. Composite index: Performance improvement
The firm’s past performance is attributed to external and internal causes (Walsh
& Henderson, 1988). External causes include the strategies of competitors, customer
requirements, and competitive environment; internal causes include quality
management, supply base management, and customer relations practices (Tan,
Kannan, Handfield, & Ghosh, 1999). Thus, performance improvement of the firm is
the general reference of managers’ decision making.
In instances involving some history of poor performance, a substantial reduction
in research may be the best strategy to maintain public credibility; on the other hand,
managers are prepared to reinvest heavily where there a history of successful
performance (Walsh & Henderson, 1988). For example, the longer its tenure as a
high-performing producer, the more a firm invests in quality-enhancement programs
(Rob & Fishman, 2005). The reinvestment strategy is a typical feature of the
promotion focus and the investment-reduction strategy is a typical feature of the
prevention focus. Hence, higher investment in performance improvement is related to
situational promotion regulatory focus and lower investment in performance
improvement is related to situational prevention regulatory focus. Relying on the
regulatory fit effect, buyers who emphasize high performance improvement are
motivated to consider exhibitors’ promotion-focused presentations, and buyers who
give relatively less emphasis on performance improvement are motivated to consider
exhibitors’ prevention-focused presentations.
H2c. Buyers emphasizing performance improvement can be expected to achieve
higher contact efficiencies with exhibitors whose presentations are
promotion-focused; conversely, buyers who place relatively less emphasis on
performance improvement can be expected to achieve higher contact
efficiencies with exhibitors whose presentations are prevention-focused.
5. Chronic and situational regulatory focus effect on contact
efficiency
The average contact at a busy show may last only 3 to 5 minutes and a
salesperson might interact with 20 or more prospects/customers in an hour (Resnick,
1991). Researchers exploring psychological factors often approach time as a mental
construction having only subjective meaning (Bergadaà, 1990). During the short
contact periods involved in trade show contexts, buyers feel time pressure to decide
whether to proceed from the attraction stage to the contact stage. This time pressure
has been shown to restrict individuals’ information processing abilities (Suri &
Monroe, 2003). Severe time constraints typically force the abandonment of
established decision-making practice and canon, in favor of new approaches hastily
adapted to the immediate circumstances (Hansen & Helgeson, 1996). Besides time
constraint concerns, another important factor relates to the fact that this is, after all,
the contact stage, with the limited goal of obtaining pledges for further contact; not
commitment to purchase.
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Under these circumstances of time constraint and decision-making short of final
commitment, individuals are less likely to consider a great number of factors as they
go about processing information, but instead focus on general characteristics to search
out choices which are generally positive (Chaiken, Liberman, & Eagly, 1989).
This restriction of decision making factors under time constraints, coupled with
buyer awareness that decisions are not final, high pressure purchasing decisions,
combine to suggest that the operative focus during the contact stage is the chronic
regulatory focus.
We go on to argue that people’s chronic regulatory focus (Higgins, 1997) plays
an important role in directing people’s attention to information that fits their
regulatory orientation. Hence, in light of these further observations on the nature of
the contact stage, we expect buyers to make decisions more on the basis of chronic
regulatory focus rather than situational regulatory focus in the contact stage.
H3. Chronic regulatory focus has a more significant impact on contact efficiency in
the trade show environment than situational regulatory focus.
6. Methodology
7.1. Outline
We conducted two experiments to test our hypotheses. The first study attempts to
develop stimuli for participants to provide evidence for our proposed chronic
regulatory fit effect on contact efficiency. Specifically, Study 1 demonstrates that
promotion (prevention)-focused buyers prefer ongoing contact with promotion
(prevention)-focused exhibitors. Study 2 builds on this finding and shows the effect of
chronic regulatory focus and three situational regulatory foci on contact efficiency.
7.2. Study 1
7.2.1. Stimuli development
We manipulated regulatory focus via trade show display scenarios framed either
in promotion or in prevention terms. Based on in-depth interviews with several trade
show experts, we came up with a new product with the following attributes: (1)
Requiring repurchase an average of six times per year, (2) each purchase involving an
outlay of $10,000, (3) returning clients can pay cash on delivery (COD), while new
buyers must pay cash in advance, and (4) development expense and mould tooling
charge costs would be around $12,000; this is either “from scratch” in-house redesign
or the expense for getting your old supplier to release the mould tooling specs.
We designed two kinds of presentations by referring to Aaker & Lee (2001)’s
manipulation. The promotion-focused presentation exhibitor, with the firm name
“MHT,” emphasized the benefits that buyers could gain. The prevention-focused
presentation exhibitor, with the firm name “GQD,” emphasized the problems that
buyers could avoid. In our in-depth interviews with seasoned exhibitors, we discussed
general inquiries posed by existing or new customer/attendees. They included eight
prominently recurring issues: (1) supplier categories (“Are you the manufacturer or a
trading company?”), (2) suppliers’ main markets (“Who do you sell to?”), (3) price
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range, (4) delivery period (time from request to delivery), (5) exclusive agency (“Can
I get privileged distribution rights for a geographical area?”), (6) supplier monthly
capacity (“How many of these things do you make?”), (7) mould charge for custom
models, and (8) payment terms; typically interest in some kind of a “credit line”
arrangement. Among those issues, the most serious ones when new visitors consider
potential supplier are price, payment, and exclusive agency. Accordingly, the detail
statement of manipulation is as shown in Table 1.
7.2.2. Data collection and sample characteristics
This study has defined its population as middlemen that participate in
international trade shows to purchase from overseas suppliers and resell to their
domestic or foreign markets. A survey of personnel with purchasing experience was
conducted to obtain a base of potential participants for the present study. We
primarily sampled from the 2007 Mido Optical Fair catalog, listing more than one
thousand firms which attend international optical shows, like the Mido show (Milano,
Italy), Silmo optical show (Paris, France), Hong Kong optical show (Hong Kong), etc.
We made preliminary phone calls to identify participants willing to commit to our
study before we dispatched questionnaires. Largely because of competitive data
privacy concerns, our original base of 278 contactees got whittled down to 48 who
were willing to follow through on data collection, and completed questionnaires for
our study.
7.2.3. Procedure
Participants would be measured for regulatory focus by “Selves Questionnaire”
(Brockner, Paruchuri, Idson, & Higgins, 2002; Idson & Higgins, 2000). They were
initially provided with a definition of their ideal and ought selves. Their ideal self was
defined as the type of person they ideally would like to be, the type of person they
hoped, wished, or aspired to be. Their ought self was defined as the type of person
they believed they ought to be, the type of person they believed it was their duty,
obligation, or responsibility to be. Self-congruency scores were calculated as the
difference between self-guide extent ratings and respective actual ratings for ideal and
ought self-guides separately (Idson & Higgins, 2000). Specifically, each actual/ideal
extent rating was subtracted from its corresponding ideal extent rating. The resultant
differences (one for each attribute) were then summed such that a more positive score
means lower ideal congruency. Similarly, each actual/ought extent rating was
subtracted from its corresponding ought extent rating and then summed. A more
positive score means lower ought congruency.
Then, participants were instructed to take a 15-minute break from our task to do
something else unrelated to the experiment. Afterwards, participants were asked to
imagine themselves as the buyers of our manipulated new product in the trade show.
We presented participants with a list of features related to the presentation about price,
payment terms, and exclusive agency as shown in Table 1. Participants are required to
read this appeal and then complete their evaluation which was to indicate one
exhibitor with whom they would like ongoing contact, and then rate the presentation
on three seven-point scales, anchored at the ends by “bad/good,” “negative/positive,”
and “unfavorable/favorable.” Finally, they were required to complete some
demographic data and we gave them U.S. $35 coupon for their help.
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We averaged participants’ evaluations of the exhibitors on the four items to form
a brand attitude index for each of the two exhibitors (αMHT = .96 and αGQD = .93).
Promotion-focused participants’ attitude toward exhibitor MHT is significantly higher
than for GQD (M = 4.92 versus 3.53, p < .001), and prevention-focused participants’
attitude for exhibitor MHT is significantly lower than that for GQD (M = 4.18 versus
5.00, p < .001).
7.2.4. Measures
This study sought to find the relationship between chronic regulatory focus and
contact efficiency. We adapted the logistic model from Dhar & Nowlis (1999). The
dependent variable was the ongoing contact choice of either MHT or GQD and was
modeled as a function of the independent dummy variable, and the buyers’ chronic
regulatory focus—promotion vs. prevention focus. Our logistic regression analysis in
this and subsequent studies follows that of other research on similar choices (e.g.,
Dhar & Sherman, 1996; Nowlis & Simonson, 1997).
In addition, in order to control the effect of certain objective firm factors on
contact efficiency, such as “traditional vs. new-tech”, and “sales volume”, these were
entered as control variables into the logistic regression equation in this study.
7.2.5. Results
The logistic regression model had a predictive ability of 82.1% for contact
efficiency. Consistent with Hypothesis 1, the coefficient for chronic regulatory focus
was statistically significant (BCRF= 2.59, p<.01). These results provide evidence that
effect of chronic regulatory on contact efficiency is significantly positive; that is,
promotion- (prevention-) focused buyers prefer ongoing contact with exhibitors
whose presentations are characterized by gain (non-loss).
7.2.6. Discussion
Buyers who are motivated to process information within time constraints rely
more on regulatory focus when choosing one exhibitor over another for ongoing
business relations. However, as indicated in the literature review, contact efficiency is
affected by not only chronic but also situational regulatory focus. Hence, we added
four kinds of situational regulatory focus into our model to explore the relationship
and to understand whether the model combing chronic and situational regulatory
focus could have better predictive ability for contact efficiency.
7.3. Study 2
7.3.1. Data collection and sample characteristics
Besides the sampling difficulties mentioned regarding Study 1, we also suffered
additional sampling difficulties, because either (1) company policy would prohibit
free expression of company organizational information, or (2) they felt that the
overhead involved in providing required information for our study, over and above
the actual business of managing their running shows, was onerous. In total, 146
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completed questionnaires were returned and the resultant sample we felt adequately
covered four major industries, consisting of mechanical/electrical appliances,
chemical industry supplies, commodities, and optical import/manufacture. The large
majority of the respondent firms (56.2%) had more than 51 employees, while nearly
one-forth (26.0%) had 21~50 employees, and the rest (17.8%) had less than 20
employees. Besides this, more than half of the respondent firms’ (56.8%) volume was
more than US$3.3 million, while nearly one-forth (28.8%) was less than US$1.6
million, and the remaining (14.4%) was US$1.6~3.3 million. The respondents
consisted of a balanced mix of firm leaders with one-fourth of being owners, another
fourth being executives, another fourth being department managers, and the rest being
purchasing agents.
The cross-validation methodology is employed to examine the predictive power
of chronic and situational regulatory focus for contact efficiency in terms of sampling
variation. One simple use of the cross-validation idea consists of randomly splitting a
sample into two subsamples. We first randomly used 117 samples to build up our
logistic model, and then used another 29 samples to cross-validate our model.
7.3.2. Procedure
The participants for Study 2 were distinct from the Study 1 group, but were still
drawn from the same sample frame. They were instructed to identify their chronic
regulatory focus, as with the Study 1 group. Then, they were given a 15-minute break
to do something unrelated to the experiment. After the break, they were asked about
our sample firms’ situations including their impressions of environmental uncertainty,
formalization, and performance improvement. Participants were then manipulated as
in Study 1. They were then asked to imagine themselves as buyers in a trade show
environment and were provided with presentations which related prices, payment
terms, and exclusive agency terms for two exhibitors. They were required to read the
presentations and complete evaluations indicating one exhibitor with which they
would prefer ongoing contact. They were then asked to rate the presentations on three
seven-point scales, anchored by “bad/good,” “negative/positive,” and
“unfavorable/favorable.” Finally, they filled in some demographic data. As with the
Study 1 group, we gave each of them a US$35 gift coupon and a nice gift for their
help.
Unlike most trade show studies that use field surveys or tap performance
databases, this study is based on an experimental design. Therefore, the current study
seeks to exclude unnecessary characteristics that could skew observed variances in
contact efficiency apart from chronic and situational regulatory focus effects.
Specifically, participants were asked to absorb and assume a baseline of
organizational intrinsic and extrinsic factors applicable to our experimental shows
under consideration, consisting of competition and performance figures from recent
years. The participants were also asked to rate the firm’s trade show contact efficiency
on two fronts: choice for ongoing contact and general attitude towards the firm.
As with Study 1, we averaged participants’ evaluations for each of our two
manipulated exhibitors (αMHT = .96 and αGQD = .95). Promotion-focused participants’
attitude toward exhibitor MHT is significantly higher than that for GQD (M = 5.15
versus 3.78, p < .001), and prevention-focused participants’ attitude for exhibitor
MHT is significantly lower than that for GQD (M = 3.72 versus 4.85, p < .001).
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7.3.3. Measures
This study began by combining fieldwork on trade shows and insights proffered
by the literature on the psychology of industrial marketing to specify the domain of
each of the construct dimensions under investigation and to develop items that could
serve as indicators of three situational regulatory foci. We maintained our Study 1
approach adapting a dependent variable as a dummy variable and the same logistic
model as Study 1. The measures of three situational regulatory foci have acceptable
reliabilities and psychometric properties. Table 2 shows correlations between these
three variables. The specific operational terms used are shown in the Appendix.
Hypotheses 2a~2c suggest that situational regulatory focus has influence on the
buyer’s contact choice. Hypothesis 3 indicates that chronic regulatory focus has a
more positive effect on contact efficiency than situational regulatory focus in the trade
show environment. The dependent variable was the preference choice for further
contact between MHT or GQD, and was modeled as a function of the following
independent dummy variables: (1) the buyers’ chronic regulatory focus (promotionvs. prevention- focus), and (2) situational regulatory focus [uncertainty (high/low),
formalization (high/low), and performance improvement (high/low)].
In addition, as in Study 1, we introduced control variables into the logistic
regression equation. We used hierarchical regression to analyze the effect of chronic
and situational regulatory focus on contact efficiency and used another sample to do
cross-validation for our model.
7.3.3.1. Environmental uncertainty
Environmental uncertainty is defined as the degree to which perceived
instability of environments relates to a firm's business (Duncan, 1972; Tan & Li,
1996). We adapted the scale of environmental uncertainty from Fam & Yang (2006).
In this study, respondents were asked to rate their perceived uncertainty for the
following four items: (1) customers' buying habits, (2) nature of competition, (3) taste
and preference of customers, and (4) market activities of competitors. Each statement
was measured with a 7-point Likert scale with endpoints labeled as 1 = strongly
disagree to 7 = strongly agree.
7.3.3.2. Formalization
Formalization is the most important measurement of organizational structure.
The items of formalization used in our study were adapted from Ferrell & Skinner
(1988). In order to get more objective data, we used “employees” in replace of “I.”
Respondents were asked to rate their firm’s formalization for the following six items:
(1) if a written rule does not cover some situation, employees make up informal rules
for doing things as they go along, (2) there are many employees’ business practices
that are not covered by some formal procedure, (3) usually, employees’ contact with
this company and its representatives involves doing things “by the rule book”, (4)
contact with this company and its representatives are on a formal preplanned basis, (5)
employees ignore the rules and reach informal agreements to handle some situations,
and (6) when rules and procedures exist in this company, they are usually written
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agreements. Among these items, item (1), (2), and (5) are reversed. Each statement
was measured with a 7-point Likert scale with endpoints labeled as 1 = strongly
disagree to 7 = strongly agree.
7.3.3.3. Performance improvement
Performance improvement was measured by asking respondents to indicate the
extent to which their performance had improved over the past two years with respect
to 6 financial, market oriented, and operational measures of performance.
Self-reporting in this domain has by now become a validated, established practice (e.g.
Bourgeois & Eisenhardt, 1988; Conant, Mokwa, & Varadarajan, 1990; Powell, 1994).
The six-item scale of performance improvement was adapted from Cohen (2001). In
this study, respondents were asked to rate their firm’s performance improvements via
the following six items: (1) sales growth, (2) profitability relative to competitors, (3)
cash flow generating ability, (4) market share, (5) competitive position, and (6)
operational efficiency. Each statement was measured with a 7-point Likert scale with
endpoints labeled as 1 = strongly low to 7 = strongly high.
7.3.4. Results
Logistic regression analysis was used to assess the effects of chronic and
situational regulatory focus on the buyers’ choices between two exhibitors (see Table
3). The logistic regression model had a 79.5% predictive ability. Coefficient for
chronic regulatory focus was still consistent with Hypothesis 1 (BCRF= 2.35, p<.001).
Coefficient for uncertainty was consistent with Hypothesis 2a (BUN= -2.15, p<.05).
This confirms that buyers prefer ongoing contact with exhibitors whose presentations
are prevention-focused when they are in more uncertain environments. On the other
hand, buyers preferred ongoing contact with exhibitors whose presentations were
promotion-focused in less uncertain environments. The coefficient for formalization
was not consistent with Hypothesis 2b (BFO= -.52, p>.28). The coefficient for
performance improvement was consistent with Hypothesis 2c (BPE= 1.42, p<.05).
This means that buyers preferred ongoing contact with exhibitors whose presentations
are promotion-focused when those firms evince higher performance improvement. On
the other hand, buyers preferred ongoing contact with exhibitors whose presentations
were prevention-focused when those firms had lower performance improvement.
These results are also consistent with Hypothesis 3, and provide evidence that the
effect of chronic regulatory focus on contact efficiency is more positive than that of
situational focus.
We also did cross-validation for our logistic model by collecting another sample.
The cross-validation model had a 83.3% predictive ability and coefficients for
uncertainty and performance improvement were significant in our building model.
These results provide additional evidence that a model incorporating chronic and
situational regulatory focus has significant predictive power with respect to contact
efficiency.
7.3.5. Discussion
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The results suggest that the effect of situational regulatory focus on contact
efficiency deserves further attention. Highly uncertain conditions produced more
favorable evaluations for the exhibitor when his/her positioning addressed non-loss
concerns. However, conditions of low uncertainty produced preference for exhibitors
who provided presentations emphasizing gain. However, formalization does not
appear to have a significant situational regulatory focus effect on contact efficiency.
Performance improvement significantly stimulates the situational regulatory focus
effect on contact efficiency. Clearly, in this essential contact stage in the trade show,
chronic regulatory fit has the greatest impact on contact efficiency.
7. Conclusion
The purpose of this article is to further the current state of knowledge about how
fit influences decisions and to provide a better understanding of regulatory fit theory
as a source of value that applies to contact efficiency in trade show environments.
More specifically, this article proposes that if the exhibitor can anticipate the decision
maker’s chronic regulatory state, it increases the level of intention toward a decision
outcome. Moreover, we showed that the situational regulatory focus effect is not the
only factor of significance in the contact stage. Our results have shown that contact
efficiency is significantly impacted by environmental uncertainty and performance
improvement, with the former more significant than the latter. Formalization, on the
other hand, is not significant. Therefore, the external situational regulatory focus
effect is more significant than the internal one during the contact stage. The structural
dimensions of a given firm or situation have been suggested as impacting the
positioning of the buying center (Johnston & Bonoma, 1981). Contact stage response
in the trade show environment appears to be owned by individual buyers, not the
buying center. Hence, organizational factors, like structure and power, do not affect
the buyer’s decision in the contact stage.
The average duration of the contact stage in trade shows is as short as that of a
typical recruitment interview. This stage can be likened to a buyer’s “interview” with
an exhibitor. Correspondingly, a survey of the literature on interviewing is suggestive.
Interviewers’ pre-interview evaluations of applicants tend to be self-fulfilling
(Dipboye, 1982). In other words, time limitations make interviewers more likely to
choose target interviewees by their chronic conditions; less likely by the external
situation. These findings are important because of the unstructured manner in which
the selection interview is frequently conducted. The data gathered from such
interviews are typically biased and often unrelated to future job performance (Huffcutt
& Arthur Jr., 1994; McDaniel, Whetzel, Schmidt, & Maurer, 1994; Conway, Jako, &
Goodman, 1995). These biases include interviewers’ tending to favor applicants who
share their non-work-related attitudes, giving unduly high weight to negative
information, and allowing undue factors, such as interview ordering, to influence
evaluations. (Dipboye, 1982). It appears the same applies to the contact stage in trade
show environments: Limited time in the contact stage makes the chronic regulatory
focus effect more significant than the situational one on contact efficiency.
The value-from-fit phenomenon has also been shown to occur by means of
different types of choice strategies, such as progressive elimination strategy and full
evaluation strategy, and by examination of content-based information versus
feelings-based information (Avent & Higgins, 2006). Clearly, our results suggest that
12
the value derived from regulatory fit for contact efficiency in a trade show
environment mainly comes from a progressive elimination strategy. Buyers make
further contact decisions by chronic factors—regulatory focus, external situational
factors—uncertainty—and
composite
situational
factors—performance
improvement—although they appear to negate organizational factors—like
formalization.
8.1. Managerial implications
Our results illustrate that contact efficiency is enhanced when the buyer’s
chronic regulatory focus fits the exhibitor’s, and that external situational regulatory
focus has influence on contact efficiency. From an exhibitor’s perspective, these
findings have important implications for managers executing marketing strategies.
First, our study suggests that the chronic regulatory fit effect makes the securing of
pledges for future contact from buyers more efficient, i.e., the contact efficiency at the
trade show is higher when promotion (prevention)-focused exhibitors are exposed to
promotion (prevention)-focused buyers. Furthermore, high degrees of perceived
uncertainty within a particular industry tend to further enhance the effectiveness of
prevention-focused presentations, whereas perceived performance improvement tends
to enhance the effectiveness of promotion-focused presentations. The effects of
environmental uncertainty and performance improvement therefore open up
opportunities for enhancing contact efficiency. Second, chronic regulatory non-fit
situations diminish contact efficiency. When the exhibitor does not fit with the buyer
in this regard, the best strategy is to change the exhibitor to achieve a better fit
because doing so will tend to increase the buyers’ intention to ongoing contact with
the exhibitor. However, if the exhibit cannot be changed, our findings suggest that
compensation can be achieved through the application of external situational
regulatory focus variables (environmental uncertainty and performance improvement
due to external factors).
More broadly, our work signals other opportunities to enhance contact efficiency.
Any methods that stand to decrease buyer uncertainty are salutary. For example,
better integrating industrial information at the trade show or adroitly addressing
requests for particularly industry-savvy salespersons and managers can decreaser
buyer uncertainty. Other methods, like providing bottom-line prices, promoting
buyer-friendly payment terms, and messages that promote an image of industrial
stability, can decrease uncertainty. On the other hand, there’s a workable angle
involving enhancing uncertainty via the purposeful highlighting of industrial
information that highlights fluctuating prices and other instabilities, as well as via
supplier-oriented payment terms. Managerially, this exercise would exploit a chronic
regulatory non-fit effect which can be cultivated in complementary future
communications efforts. Third, our study highlights an approach to documenting the
effectiveness of a communications activity, as applied to the trade show environment,
in terms of contact efficiency. While the extent of impact may differ across firms and
in varied specific situations, such an exercise provides a useful approach for managers
to demonstrate accountability on the issue of contact efficiency by quantifying the
contribution of a specific activity within a communications system as shown in Table
4.
8.2. Research limitations and future research
13
Our study has several limitations, which we believe will provide useful avenues
for future research. First, this study considers the same new product exhibited by two
similar firms. Although it is tempting to generalize our results to other firms or to
other shows, to do so would be beyond the scope of our study. Replications of this
exploratory work in different types of shows and with different types of industrial
buyers would allow more dependable generalizations to be made.
Second, we looked at the typical communications mix in a business-to-business
marketing context; however, future studies may deem it necessary to include other
elements such as advertising and direct mail.
Third, our study focused on a new product to avoid the effects of prior,
real-world marketing activities. Because we did not track the profits of other products
exhibited at the show, we do not abstract possible positive or negative effects of the
larger show performance aside from our test subjects. Furthermore, the effects of
personal selling activities were not taken into account. Further research is needed to
extend these considerations to situations involving existing products.
Fourth, the measurement of sales effort was limited by our access to data. We
believe a more direct form of measuring contact efficiency that includes separating
the effects of culture and field would be valuable.
Fifth, although it is not easy to measure individuals’ chronic regulatory focus,
besides the “Selves Questionnaire” adopted by our study, other methods of
measurement taken from past studies, like “Event Reaction Questionnaire” (Higgins,
Friedman, Harlow, Idson, Ayduk, & Taylor, 2001) and “Promotion/Prevention Scale”
(Lockwood, Jordan, & Kunda, 2002) should be considered.
Sixth, future research about situational regulatory focus should include more
factors, like economic climate, leadership behavior, and development expectation, etc.
Our study just explored the effects of three representative factors on contact
efficiency.
Finally, our methodology is limited to dependent variables that necessarily only
test the buyer’s perspective. Future studies which manipulate experimental groups of
buyers should allow for the development of more robust models that take bilateral
cognition into account.
Appendix. Description of construct operational items used in this study
Construct
Environmental
Uncertainty
Formalization
Performance
improvement
Item
customers' buying habits
nature of competition
taste and preference of customers
market activities of competitors
legal, political and economic constraints
If a written rule does not cover some situation, employees make up informal rules for doing things as they go
along*
There are many things in employees’ business that are not covered by some formal procedure for doing it*
Usually, employees’ contact with this company and its representatives involves doing things “by the rule book”
Contact with this company and its representatives are on a formal preplanned basis
Employees ignore the rules and reach informal agreements to handle some situations*
When rules and procedures exist in this company, they are usually written agreements
Sales growth
Profitablity relative to competitors
Cash flow generating ability
Market share
Competitive position
Operational efficiency
14
*reversed item
References
Aaker, J., & Lee, A. (2001). “I” seek pleasures and “we” avoid pains: the role of
self-regulatory goals in information processing and persuasion. Journal of
Consumer Research, 28, 33–49.
Avent, T., & Higgins, E. T. (2006). How regulatory fit affects value in consumer
choices and opinions. Journal of Marketing Research, 43, 1-10.
Avnet, T., & Higgins. E. T. (2003). Locomotion, assessment, and regulatory fit: value
transfer from “How” to “What.” Journal of Experimental Social Psychology, 39,
525–530.
Bergadaà, M. (1990). The role of time in the action of the consumer. Journal of
Consumer Research, 17, 289–302.
Blythe, J. (2002). Using trade fairs in key account management. Industrial Marketing
Management, 31(7), 627-635.
Bourgeois, L. J., & Eisenhardt, K. M. (1988). Strategic decision processes in high
velocity environments: four cases in the microcomputer industry. Management
Science, 34(7), 816-835.
Brockner, J., & Higgins, E. T. (2001). Regulatory focus theory: implications for the
study of emotions at work. Organizational Behavior and Human Decision
Processes, 86(1), 35-66.
Brockner, J., Paruchuri, S., Idson, L. C., & Higgins, E. T. (2002). Regulatory focus
and the probability estimates of conjunctive and disjunctive events.
Organizational Behavior and Human Decision Processes, 87, 5–24.
Camacho, C. J., Higgins, E. T., & Luger, L. (2003), Moral value transfer from
regulatory fit: What feels right is right and what feels wrong is wrong. Journal of
Personality and Social Psychology, 84(3), 498–510.
Cesario, J., Grant, H., & Higgins, E. T. (2004). Regulatory fit and persuasion: transfer
from “Feeling Right.” Journal of Personality and Social Psychology, 86,
388–404.
Chaiken, S., Liberman, A., & Eagly, A. H. (1989). Heuristic and systematic
information processing within and beyond the persuasion context in Unintended
Thought, ed. James S. Uleman and John A. Bargh, New York: Guilford, 212-252
Cohen, J. F. (2001). Environmental uncertainty and managerial attitude: effects on
strategic planning, non-strategic decision-making and organizational
performance. South Africa Journal of Business Management, 32(3), 17-31.
Conant, J. S., Mokwa, M. P., & Varadarajan, P. R. (1990). Strategic types, distinctive
marketing competencies and organizational performance: a multiple
measures-based study. Strategic Management Journal, 11(5), 365-383.
Conway, J. M., Jako, R. A., & Goodman, D. F. (1995). A meta-analysis of interrater
and internal consistency reliability of selection interviews. Journal of Applied
Psychology, (October), 565-579.
15
Craig, C. S., & Douglas, S. P. (2000). Configurational advantage in global markets.
Journal of International Marketing, 8(1), 6-26.
DeCanio, S. J., Dibble, C., & Amir-Atefi, K. (2000). The importance of
organizational structure for the adoption of innovations. Management Science,
46(10), 1285-1299.
Deci, E. L., & Ryan, R. M. (1985). Intrinsic motivation and self-determination in
human behavior. New York: Plenum.
Dekimpe, M. G., François P., Gopalakrishna S., Lilien G. L., & Bulte C. V. (1997).
Generalizing about trade show effectiveness: a cross-national comparison.
Journal of Marketing, 61, 55-64.
Dhar, R., & Nowlis, S. M. (1999). The effect of time pressure on consumer choice
deferral. Journal of Consumer Research, 25(4), 369-384.
Dhar, R., & Sherman, S. J. (1996). The effect of common and unique features in
consumer choice. Journal of Consumer Research, 23, 193-203.
Dickson, V., & Lere, J. C. (2003). Problems evaluating sales representative
performance? Try activity-based costing. Industrial Marketing Management,
32(4), 301-307.
Dipboye, R. L. (1982). Self-fulfilling prophecies in the selection-recruitment
interview. Academy of Management Review, 7(4), 579-586.
Duncan, R. (1972). Characteristics of organizational environments and perceived
uncertainty. Administrative Science Quarterly, 2, 409 – 43.
Fam, K., & Yang, Z. (2006). Primary influences of environmental uncertainty on
promotions budget allocation and performance: a cross-country study of retail
advertisers. Journal of Business Research, 59(2), 259-267.
Ferrell, O. C., & Skinner, S. J. (1988). Ethical behavior and bureaucratic structure in
marketing research organizations. Journal of Marketing Research, 25, 103-109.
Fink, R. C., Edelman, L. F., & Hatten, K. J. (2006). Relational exchange strategies,
performance, uncertainty, and knowledge. Journal of Marketing Theory and
Practice, 14(2), 139-153.
Forster, J., Higgins, E. T., & Idson, L. C. (1998). Approach and avoidance strength
during goal attainment: Regulatory focus and the “goal looms larger” effect.
Journal of Personality and Social Psychology, 75, 1115–1131.
Freitas, A. L., Liberman, N., & Higgins, E. T. (2002). Regulatory fit and resisting
temptation during goal pursuit. Journal of Experimental Social Psychology, 38,
291–98.
Friedman, R. S., & Förster, J. (2001). The effects of promotion and prevention cues
on creativity. Journal of Personality and Social Psychology, 81, 1001–1013.
Galaskiewicz, J., & Wasserman, S. (1989). Mimetic processes within an
interorganizational field: an empirical test. Administrative Science Quarterly,
34(3), 454–479.
Garbarino, E. C., & Edell, J. A. (1997). Cognitive effort, affect, and choice. Journal
of Consumer Research, 24, 147-158.
16
Godar, S. H., & O’Connor, P. J. (2002). Same time next year—buyer trade show
motives. Industrial Marketing Management, 30(1), 77-86.
Gopalakrishna, S., & Lilien, G. L. (1995). A three-stage model of industrial trade
show performance. Marketing Science, 14(1), 22-42.
Hansen, D. E., & Helgeson, J. G. (1996). Choice under strict uncertainty: processes
and preferences. Organizational Behavior and Human Decision Processes, 66(2),
153-164.
Hansen, K. (2002). Measuring performance at trade shows: scale development and
validation. Journal of Business Research, 57, 1-13.
Henisz, W. J., & Delios, A. (2001). Uncertainty, imitation, and plant location:
Japanese multinational corporations, 1990-1996. Administrative Science
Quarterly, 46(3), 443–475.
Higgins, E. T. (2000). Making a good decision: value from fit. American Psychologist,
55, 1217–1230.
Higgins, E. T. (1997). Beyond pleasure and pain. American Psychologist, 52,
1280–1300.
Higgins, E. T. (1998). Promotion and prevention: Regulatory focus as a motivational
principle. Advances in Experimental Social Psychology, 30, 1–46.
Higgins, E. T., Bond, R. N., Klein, R., & Strauman, T. (1986). Self-discrepancies and
emotional vulnerability: How magnitude, accessibility, and type of discrepancy
influence affect. Journal of Personality and Social Psychology, 51, 5–15.
Higgins, E. T., Friedman, R. S., Harlow, R. E., Idson, L. C., Ayduk, O. N., & Taylor,
A. (2001). Achievement orientations from subjective histories of success:
promotion pride versus prevention pride. European Journal of Social Psychology,
31, 3-23.
Higgins, E. T., Idson, L. C., Freitas, A. L., Spiegel, S., & Molden, D. C. (2003).
Transfer of value from fit. Journal of Personality and Social Psychology, 84,
1140–1153.
Higgins, E. T., Klein, R., & Strauman, T. (1985). Self-concept discrepancy theory: a
psychological model for distinguishing among different aspects of depression
and anxiety. Special issue: Depression. Social cognition, 3, 51–76.
Higgins, E. T., Shah, J., & Friedman, R. (1997). Emotional responses to goal
attainment: Strength of regulatory focus as moderator. Journal of Personality
and Social Psychology, 72, 515–525.
Huffcutt, A. I., & Arthur Jr., W. (1994). Hunter and Hunter (1984) revisited:
interview validity for entry-level jobs. Journal of Applied Psychology, (April),
184-190.
Hutchinson, K., Alexander, N., Quinn, B., & Doherty, A. M. (2007).
Internationalization motives and facilitating factors: qualitative evidence from
smaller specialist retailers. Journal of International Marketing, 15(3), 96-122.
Idson, L. C., & Higgins, E. T. (2000). How current feedback and chronic
effectiveness influence motivation: everything to gain versus everything to lose.
European Journal of Social Psychology, 30, 583-592.
17
Idson, L. C., Liberman, N., & Higgins, E. T. (2000). Distinguishing gains from
nonlosses and losses from nongains: a regulatory focus perspective on hedonic
intensity. Journal of Experimental Social Psychology, 36, 252-274.
Johnston, W. J., & Bonoma, T. V. (1981). The buying center: structure and interaction.
Journal of Marketing, 45, 143– 156.
Kark, R. & Dijk, D. V. (2007). Motivation to lead, motivation to follow: the role of
the self-regulatory focus in leadership processes. Academy of Management
Review, 32(2), 500-528.
Kerin, R. A., & Cron, W. L. (1987). Assessing trade show fuctions and performance:
an exploratory study. Journal of Marketing, 51, 87-94.
Li, L. Y. (2007). Marketing resources and performance of exhibitor firms in trade
shows: a contingent resource perspective. Industrial Marketing Management,
36(3), 360-370.
Li, L. Y. (2006). Relationship learning at trade shows: its antecedents and
consequences. Industrial Marketing Management, 35(2), 166-177.
Locke, E. A. & Latham, G. P. (1990). Work motivation and satisfaction: light at the
end of the tunnel. Psychological Science, 1(4), 240-246.
Lockwood, P., Jordan, C. H., & Kunda, Z. (2002). Motivation by positive or negative
role models: regulatory focus determines who will best inspire us. Journal of
Personality and Social Psychology, 83(4), 854-864.
Markman, A. B., Baldwin, G. C., & Maddox, W. T. (2005). The interaction of payoff
structure and regulatory focus in classification. Psychological Science, 16(11),
852-855.
McDaniel, M. A., Whetzel, D. L., Schmidt, F. L., & Maurer, S. D. (1994). The
validity of employment interviews: a comprehensive review and meta-analysis.
Journal of Applied Psychology, (August), 599-616.
Nowlis, S. M., & Simonson, I. (1997). Attribute-task compatibility as a determinant
of consumer preference reversals. Journal of Marketing Research, 34, 205-218.
Orth, U. R. (2005). Consumer personality and other factors in situational brand choice
variation. Brand Management, 13(2), 115-133.
Pawar, B. S., & Eastman, K. K. (1997). The nature and implications of contextual
influences on transformational leadership: a conceptual examination. Academy of
Management Review, 22(1), 80-109.
Porter, M. E. (1986). Changing patterns of international competition. California
Management Review, 27(2), 9-40.
Powell, T. C. (1994). Untangling the relationship between strategic planning and
performance: the role of contingency factors. Canadian Journal of
Administrative Science, 11(2), 124-138.
Prahalad, C. K., & Doz, Y. L. (1987). The multinational mission: balancing local
demands and global vision. New York: The Free Press.
Resnick, K. (1991). 8 steps to scale success. Business Marketing, (Fall), A20-21.
Rob, R., & Fishman, A. (2005). Is bigger better? Customer base expansion through
word-of-mouth reputation. Journal of Political Economy, 113(5), 1146-1162.
18
Roney, C. J. R., Higgins, E. T., & Shah, J. (1995). Goals and framing: How outcome
focus influences motivation and emotion. Personality and Social Psychology
Bulletin, 21, 1151–1160.
Shah, J., Higgins, E. T., & Friedman, R. (1998). Performance incentives and means:
How regulatory focus influences goal attainment. Journal of Personality and
Social Psychology, 74, 285–293.
Shamir, B., & Howell, J. M. (1999). Organizational and contextual influences on the
emergence and effectiveness of charismatic leadership. Leadership Quarterly,
10(2), 257-283.
Smith, T. M., Hama, K., & Smith, P. M. (2003). The effect of successful trade show
attendance on future show interest: exploring Japanese attendee perspectives of
domestic and offshore international events. Journal of Business & Industrial
Marketing, 18(4/5), 403-418.
Suri, R., & Monroe, K. B. (2003). The effects of time constraints on consumers
judgments of prices and products. Journal of Consumer Research, 30, 92-104.
Tan, J, & Li, M. (1996). Effects of ownership types on environment – strategy
configuration in China’s emerging transitional economy. Advance International
Company Management, 11, 217– 50.
Tan, K. C., Kannan, V. R., Handfield, R. B., & Ghosh, S. (1999). Supply chain
management: an empirical study of its impact on performance. International
Journal of Operations & Production Management, 19(9/10), 1034-1052.
The
Global Association of the Exhibition Industry (UFI) (2007).
http://www.ufinet.org/.
Van-Dijk, D., & Kluger, A. N. (2004). Feedback sign effect on motivation: Is it
moderated by regulatory focus? Applied Psychology: An International Review,
53(1), 113-135.
Wallace, J. C., Chen, G., & Kanfer, R. (2005). Development and validation of a
work-specific measure of regulatory focus. Paper presented at the 20th Annual
Conference of the Society for Industrial/Organizational Psychology, Los Angeles,
CA.
Walsh, J. P., & Henderson, C. M. (1988). An attributional analysis of decisions about
making commitments. Journal of Social Psychology, 129(4), 533-549.
Wang, J., & Lee, A. Y. (2006). The role of regulatory focus in preference construction.
Journal of Marketing Research, 43, 28-38.
Wernerfelt, B. (1984). A resource-based view of the firm. Strategic Management
Journal, 5(2), 171-180.
Zahay, D., & Griffin, A. (2004). Customer learning processes, strategy selection, and
performance in business-to-business service firms. Decision Sciences, 35(2),
169–203.
Table 1
Manipulation of presentation with representatives of two firms
19
Presentation with MHT’s representative
Presentation with GQD’s representative
price
You: Your price is a little higher than GQD’s.
MHT: As we know, our price could be the same as our
competitor; moreover, you will get 5% discount
if you can buy in total amount $200,000 a year.
Accordingly, our price should be lower than
others.
payment
You: How about your payment term? I know the
general term for new supplier is requested by
cash in advance.
MHT: If you agree to pay 30% deposit about $3,000
after receipt of our sales confirmation, then you
can pay the balance one month after receipt of
goods.
exclusive agency
You: May I have this model exclusively in our
country?
MHT: That’s great. If you would like to share our
research expense and model tooling charge about
$5,000, then we will keep it for you.
Table 2
Inter-correlation for key study constructs
Variable
Environmental uncertainty X1
Formalization X2
Performance improvement X3
You: After I check the quotation with MHT, your price
is a little higher.
GQD: It looks like true, but we actually don’t charge
3% handling charge even you ordered amount is
below the minimum quantity. You can compare it
with other competitors. Don’t worry about our
prices.
You: How about your payment term? Our suppliers give
us cash on delivery. We do this business over 25
years.
GQD: As you know, the general payment term for new
buyer is cash in advance, but you can make it by
cash on delivery if you would like to pay 1%
interest rate each mouth.
You: Do you offer this model to other importer in our
country? Could you keep it exclusively for our
firm?
GQD: Yes, we can discuss your request. Our condition
is that we need to collect the research expense and
model charge about $6,000 first; then, we will
return that amount whenever your ordered quantity
reaches $60,000.
X1
X2
-0.03
-0.16
-0.14
Table 3
20
X3
Results of the hierarchical logistic regression analysis
Study 1
Study 2
Dependent variable: contact
Controls
Full model
Controls
Full model
choice: MHT=1, GQD=2
β
β
β
β
Control variables
S.E.
S.E.
S.E.
S.E.
Industry
0.23*
0.12
0.33*
0.17
-0.05
0.06
-0.13*
0.08
Turnover
-0.47*
0.27
-0.55*
0.32
-0.31**
0.13
-0.41**
0.16
β
β
β
β
Independent variables
S.E.
S.E.
S.E.
S.E.
Chronic regulatory focus:
2.59***
0.96
2.35***
0.58
promotion=1, prevention=2
Environmental uncertainty:
-2.15**
0.93
high=1, low=2
Formalization: high=1, low=2
-0.52
0.49
Performance improvement:
1.42**
0.60
high=1, low=2
-2 log-likelihood
44.44
34.68
147.29
111.64
Cox and Snell R2
0.19
0.37
0.05
0.31
Nagelkerke R2
0.26
0.50
0.07
0.42
Model χ2
8.36
18.12
6.22
41.87
Percent correctly classified
66.7
82.1
64.3
79.5
***p<0.01; **p<0.05; *p<0.1
β, unstandardized regression coefficients; S.E., standard error of the coefficients
Table 4
Four communication strategies of exhibitors with buyers
21
Promotion-focused exhibitor
Prevention-focused buyer
Promotion-focused exhibitor
Promotion-focused buyer
1.
2.
Change the exhibitor
Decreasing-uncertainty strategy
(1) providing bottom-line price
(2) providing buyer-oriented payment term
(3) providing industrial stable messages
3. Improving-performance strategy
(1) new product can improve productivity
(2) new product can be produced quickly
Prevention-focused exhibitor
Promotion-focused buyer
1.
1.
2.
1.
3.
2.
Decreasing-uncertainty strategy
(1) providing bottom-line price
(2) providing buyer-oriented payment term
(3) providing industrial stable messages
Improving-performance strategy
(1) new product can improve productivity
(2) new product can be produced quickly
Prevention -focused exhibitor
Prevention -focused buyer
Change the exhibitor
Increasing-uncertainty strategy
(1) providing fluctuating price
(2) providing supplier-oriented payment term
(3) providing industrial unstable messages
stabilizing-performance strategy
(1) new product has stable market
(2) new product has standard to produce
22
2.
Increasing-uncertainty strategy
(1) providing fluctuating price
(2) providing supplier-oriented payment term
(3) providing industrial unstable messages
stabilizing-performance strategy
(1) new product has stable market
(2) new product has standard to produce