www.elsevier.com/locate/atoures
Annals of Tourism Research, Vol. 32, No. 4, pp. 905–924, 2005
Ó 2005 Elsevier Ltd. All rights reserved.
Printed in Great Britain
0160-7383/$30.00
doi:10.1016/j.annals.2004.07.012
TESTING THEORY OF PLANNED
VERSUS REALIZED TOURISM BEHAVIOR
Roger March
University of New South Wales, Australia
Arch G. Woodside
Boston College, USA
Abstract: This article probes how well one’s plans for doing, buying, and consuming discretionary tourism services relate to what is actually done. Using group level data, it includes an
empirical study of hypotheses comparing planned and actual consumption behaviors. The
main propositions tested are that realized consumption behaviors are greater in number than
planned and that the level of matching between planned and realized actions varies as a function of contingency factors of composition of the tourist group, product experience, and
motivations. Data from two large-scale surveys serve to examine the theory. The findings support the hypotheses partially and provide guidance for planning survey research and marketing management strategies. Keywords: consumer plans, services, unplanned behavior,
experience. Ó 2005 Elsevier Ltd. All rights reserved.
Résumé: La mise à l’essai d’une théorie pour comparer les comportements touristiques
planifiés et réalisés. Cet article examine à quel degré les projets pour faire, acheter et consommer des services discrétionnaires du tourisme se rapportent à ce que l’on fait vraiment. L’article utilise des données de niveau groupe et comprend une étude empirique des hypothèses
pour la comparaison des comportements de consommation projetée et réelle. Les principales
propositions qui sont mises à l’essai sont que les comportements de consommation réalisée
sont plus nombreux que ceux qui avaient été projetés, et que le niveau de correspondance
entre les actions projetées et réalisées varie en fonction des facteurs de contingence de la
composition du groupe touristique, de l’expérience du produit et des motivations. Des données de deux sondages à grande échelle servent pour examiner la théorie. Les résultats soutiennent les hypothèses en partie et fournissent des conseils pour la planification des
recherches par sondage et des stratégies de gestion de marketing. Mots-clés: projets de consommateurs, services, comportements imprévus, expérience. Ó 2005 Elsevier Ltd. All rights
reserved.
INTRODUCTION
Models of consumer behavior typically predict intention (or purchase decision) as the immediate antecedent of purchase (Engel,
Blackwell and Miniard 1993; Howard and Sheth, 1969; Peter and Olson
Roger March is Senior Lecturer in the School of Marketing, University of New South Wales
(Sydney 2052, Australia. Email <[email protected]>). His tourism research interests
include international distribution systems, Japanese behavior, and unethical issues. Arch
Woodside is Professor of marketing at Boston College. He is a Fellow of Royal Society of
Canada, Society for Marketing Advances, American Psychological Association, and the
American Psychological Society.
905
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TOURISM BEHAVIOR
1999). The resulting implication is that intention and subsequent consumption behavior are theoretically indistinguishable. Similarly, behaviors available within a given environment that are unplanned,
unintended, are not conceptualized in consumer behavior models.
Foxall labels marketing theory’s aversion to the study of unplanned
and impulsive behavior as ‘‘pathological’’ (2000:93).
The present article’s objective is to bridge this empirical gap and
offer insights into the similarities and differences between consumers’
planned and actual purchase and consumption behaviors. The empirical research setting examined focuses on vacation destination behavior. Using a between subjects quasi-experiment (Cook and Campbell
1979), the field study examines consumption behaviors that respondents plan to undertake, as reported in an entry survey to the destination, and the behaviors undertaken, as reported in an exit survey to the
same destination. The study investigates several behaviors (length-ofstay, spending, and number of activities undertaken) and examines
effects of contingency influences (group composition, product experience, and motivations) on the differences between planned and realized length-of-stay and spending.
The field study reported here is not the conventional approach to
planned and actual behaviors. Previous research into intentions and
consumption overwhelmingly focuses on planned behaviors, or intentions, and specifically with two aims: to improve the use of intention
measurement in its predictive power of future behavior and to influence purchasing. Though a multitude of factors and situations interfere
or constrain an individual’s ability to act upon his or her intentions
(Belk 1974, 1975; Filiatrault and Ritchie 1988), intention is still an
important construct found to relate significantly to actual behavior.
COMPARING INTENTIONS AND ACTUAL BEHAVIOR
The extant literature includes substantial empirical research into the
relationship between planned purchases and actual consumption. Typically, these studies aim to measure intentions for the purpose of predicting future consumption behavior. The US government conducted
studies and experiments concerning purchase intentions between the
40s and 70s (Young, DeSarbo, and Morwitz 1998). Many of these studies report significant relationships between intentions to buy durable
goods and subsequent purchase, using various econometric models
on panel data (Juster 1966; Tobin 1959). Kalwani and Silk (1982) demonstrate that factors such as type of product, type of measurement
scale, time from measurement of intent until actual behavior, and recency of the previous purchase influence the intention-behavior relationship. Many studies examine the relationship between purchase
intentions and behaviors for durable goods (Clawson 1971; Ferber
and Piskie 1965) and nondurable ones (Gormley 1974; Tauber 1975;
Warshaw 1980). Young, DeSarbo and Morwitz conclude, ‘‘Overall,
based on empirical evidence, intentions appear to almost always provide biased measures of purchase propensity, sometimes underestimat-
MARCH AND WOODSIDE
907
ing actual purchasing and other times overestimating actual purchasing’’ (1998:189).
Studies often focus on the predictive powers and accuracy of intentions. Most models of consumer behavior incorporate intentions as
an important predictor variable to forecast sales (Kalwani and Silk
1982; Morwitz and Schmittlein 1992). Few distinctions are made between buyer intentions and actions. Situational variables are used to
rationalize divergences between intentions and behavior. In the words
of Juster, ‘‘Purchases (actions) are directly related to (or predicted by)
intentions, modified by the incidence of unforeseen circumstances’’
(1964:66). This view remains both speculative and lacking in specifics—what unforseen circumstances affect intention-action gaps and
the effect size of such influences need examination. This article probes
the nature and size of such gaps as they relate to planning and doing
tourism behavior.
Lynch and Srull (1982) offer one reason for the apparent lack of
investigation into the ‘‘final stage’’ in the consumer consumption process. In their view, consumer research primarily is phenomenon, as opposed to theory, driven. For marketing practitioners, particularly in
advertising related fields, the predictive power of intentions to forecast
future consumption behavior accurately has obvious commercial appeal. This view builds on the assumption that consumers both attending to commercial messages and making plans have reciprocal
influences—intentions are worthy of study because they reflect benefit-seeking behavior that would enable destination strategists to craft
effective communication messages (Woodside and Jacobs 1985). Consequently, examining consumers’ planned strategies offers unique
strengths that relate especially to learning what brings tourists to a
destination the first-time as well as the second and future visits.
The concept of ‘‘unplanned’’ behavior is one dimension of the issue
regarding the relationship between intentions and actual behavior that
has been examined in marketing. Stern’s (1962) seminal article proposes four categories of unplanned purchases: ‘‘pure’’ impulse buying,
characterized by a total lack of preplanning; reminder impulse buying,
whereby purchases are sparked by previous personal experience or recall; suggestion impulse buying, where one sees the purchased product
for the first time and buys it; and planned impulse buying, typified by a
shopper entering a store with some specific items in mind, but with the
expectation and intention of making other purchases dependent on
such things as price and coupon specials. By the mid-80s, scholars
began to deconstruct the unplanned concept, and focus on its impulse
dimension (Rook and Hoch 1985; Rook and Gardner 1993). Though
an impulse purchase is unplanned, it is also includes substantial complexity in terms of antecedents, consequences, and subcategories of impulse behavior. Since the 80s an increasing number of scholars have
informed these impulse buying issues (Agee and Martin 2001; Beatty
and Ferrell 1998; Gardner and Rook 1987; Rook and Fisher 1995;
Weun, Jones, and Beatty 1998). However, the characteristics and antecedents of unplanned behavior in the broader sense remain
unexplored and unknown.
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TOURISM BEHAVIOR
The complexity of the ‘‘unplanned’’ concept needs explication.
Behavior can be unplanned yet done, either in the form of impulse
buying (purchase of a chocolate bar at the supermarket check-out
counter) or ‘‘unplanned purchases’’, when knowledge of and interaction with the task environment and time pressure combine to force a
decision that otherwise would have been foregone (Bettman 1979).
To complicate matters more, not all impulse buying may be totally unplanned. Rook and Hoch report that some people ‘‘plan on being
impulsive’’ as a shopping strategy (1985:25). Cobb and Hoyer (1986)
draw an interesting distinction between impulse and partial planners.
While both cohorts appear to be impulse purchasers because they
delay brand decisions until entering the consumption environment,
impulse planners act almost entirely in a spontaneous manner, while
partial planners exhibit careful insite purchase behavior by engaging
in detailed search and being price sensitive. Previous research into
planned, unplanned, and actual consumption was done mainly in
supermarkets (Bruce and Green 1991; Kollat and Willett 1967; Prasad
1975) thus limiting the insights that can be generalized into non-supermarket contexts.
Studies in the overall retailing sector, which includes malls as well as
supermarkets, consistently report that a significant proportion of what
is actually purchased is not planned. Moreover, in findings of particular relevance to leisure-destination research, the extent of unplanned
behavior increases under the following conditions: the more that the
consumption environment is unknown to the buyer (Bettman, Luce,
and Payne 1998); when customers regard consumption outcomes as
positive (Bagozzi and Nataraajan 2000); when few constraints exist
on their time and effort (Kollat and Willett 1967); when multiple items
are purchased, rather than just a few (Inman and Winer 1998; Kollat
and Willett 1967); and when the overall transaction involves a large,
rather than a small, amount of money (Prasad 1975). Thus, planned
versus realized strategy gaps are likely to be smaller versus larger
among consumers planning to stay only a few versus many nights in
a destination; and among tourists on a limited expenditure budget.
A large number of studies into unplanned behavior and impulse
behavior quantify the extent of unplanned purchases. In contrast,
few attempts have been made to quantify the differences in what is
planned and what is actually purchased. Abratt and Goodey found that
41% of respondents reported that they had spent more than their expressed spending intention. They suggest, ‘‘the proposition that consumers tend to spend more than they planned may hold’’
(1990:119). For a specific destination, it is important to learn what
activities are planned much more than done (if any) versus those unplanned but done frequently (if any), and what the causes and consequences of such combinations are. Explicating a theory of planned and
realized strategies that helps to answer such issues is likely useful for
guiding research and management practice.
The tourism literature includes several relevant studies for constructing a theory for explaining planned versus realized behavioral gaps.
For example, Stewart and Vogt surveyed the same tourists prior to
MARCH AND WOODSIDE
909
and during a vacation for a number of measures, including length-ofstay, activities, accommodation, and group composition. While they
found that people tend to plan more activities than they actuate, those
regarding length-of-stay, group, and transport mode were ‘‘carried out
as planned’’ (1999:91). For at least two reasons these results must be
treated with caution. First, significance tests were not applied. Second,
the same respondents were interviewed, thus creating two methodological problems: self-generated validity, whereby respondents attempt to
justify their earlier expressed intentions (Feldman and Lynch 1988)
and social desirability bias (Cobb and Hoyer 1986), in that impulse
or unplanned purchasing is underestimated in a person’s effort to
appear rational and goal oriented.
Perdue (1986) touches upon the subject in an exploratory investigation seeking to empirically verify the proposition that unplanned yet
realized behavior yields higher spending than the unplanned and
unrealized. He reports that consumers who purchase a product not
planned for are likely to express satisfaction with it as a means of justifying the purchase to themselves and other members of their group.
Ajzen and Driver (1992) use leisure activities as the research setting
for testing the theory of planned behavior. They found that the theory
is useful in predicting influences upon intentions and actual behaviors
from intentions. Their study has the limitation of being confined to
college students and in being limited to five leisure activities. As Ajzen
and Driver (1992) conclude, future research needs to examine other
recreation activities and to use more accurate and valid reporting
means. Here again, this report builds upon the previous work discussed
by examining influences in a real tourism/leisure setting, with a large
number of respondents and across a wide range of activities and
experiences.
In this context, existing models of consumer decisionmaking (Howard and Sheth 1969) focus mostly on tangible products, rather than
intangible services in tourism. Its product is experiential with emotional
undertones whose decision process differs vastly from the rational,
problem-solving scenario applied to many tangible goods. Mayo and Jarvis (1981) argue that tourism is a special form of consumption behavior
involving an intangible, heterogeneous purchase of an experiential
product. As a consequence, existing models omit important realities.
Um and Crompton suggest, ‘‘that perceptions of alternative destinations’ physical attributes in the awareness set . . . are susceptible to
change during the period of active solicitation of information stimulated by an intention to select a travel destination’’ (1990:437).
Finally, several tourism researchers argue that the benefits realized
from a consumption experience may be more useful to understand
than the benefits that consumers say they intend to seek (Dann
1981; Pearce and Caltabiano 1983; Shoemaker 1994; Woodside and
Jacobs 1983). The present report advances the proposition that learning both benefits sought and plans made, as well as benefits realized
and activities done, provides valuable information for building tourism
theory of antecedents and consequences of such behavior. Research
that investigates the process by which some intentions are actualized
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TOURISM BEHAVIOR
behavior and convincingly explains the influences resulting in unplanned as well as planned behaviors is likely to make a valuable contribution to the advancement of knowledge in the field of tourism.
Exploring Consumer Plans and Behaviors
The two hypotheses (as well as their rationales) relating planned and
actual behaviors focus on behavior within consumers’ ‘‘tourism
consumption systems’’ (Becken and Gnoth 2004; Woodside and Dubelaar 2002). A tourism consumption system is the set of related
thoughts, decisions, and behaviors by a discretionary tourist prior to,
during, and following a trip. ‘‘The central proposition in a theory of
[tourism consumption system] is that the thoughts, decisions, and
behaviors regarding one activity influence the thoughts, decisions,
and behaviors for a number of other activities’’ (Woodside and Dubelaar 2002: 120). The concept is similar but still distinct from Solomon’s
notion of consumption constellations. The latter are ‘‘sets of products and activities used by consumers to define, communicate, and perform social roles’’ (Solomon 1999:562). Distinct from this concept, a
tourism consumption system implies the likelihood of a contingent
causal chain of observable activities before and during discretionary
travel, for example, the decision by a Canadian couple to visit France
for two weeks might trigger a search for places to visit and accommodations.
H1: Realized consumption behaviors are greater in number than planned for a
set of customer activities related to a tourism consumption system.
Three contingencies common in consumer behavior and consumption plans are product experience, motivation, and in tourism, composition of the group. These were incorporated into the model as
moderating variables acting upon planned and realized behaviors.
First, product experience is critical when studying the dynamic choice
processes of consumers new to a market (Heilman, Bowman and
Wright 2000). Experience, which is the accumulation of routine and
habitual buyer behavior, allows for purposive and intelligent behavior
without deliberation (Katona 1975). Tourists who vacation at the same
place regularly are likely to engage in little pre-arrival planning, relying
instead on their accumulated knowledge and experience from previous visits (Fodness and Murray 1999).
Second, motivations underlying a leisure trip are likely to have significant influences on behavior (Morrison 1996). Tourists visiting friends
or relatives are more likely to rely on the advice of their hosts, less likely
to use product information, and thus more likely to deviate between
planned and eventual behaviors (Gitelson and Crompton 1983).
Leisure tourists, on the other hand, are more likely to engage in prearrival planning by obtaining information, particularly if they are
first-timers. Excitement and adventure seekers tend to look for more
information and undertake more activities (Gitelson and Crompton
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911
1983). Hence, their planned behavior is more likely to approximate
their eventual behavior.
Third, in the general marketing environment, the social setting
(presence or absence of others) that characterizes the consumption
of a product or service influences both planned and actual behaviors,
as it does other consumer behavior (Stayman and Deshplande 1989).
Fisher (2001) finds that greater collaboration led to higher decision
quality and smaller deviations between consumers’ planned and actual
expenditures. In leisure settings, the composition of the group heavily
influences the behavior of its members (McIntosh and Goeldner
1990). Leisure tourism is a product that is jointly consumed, and its
activities reflect direct and indirect influences of all group members
(Chadwick 1987). This phenomenon is noticeable particularly when
children are present (or absent). Taking children to a destination
likely requires greater planning and forethought than is required by
couples or tourists going without. Therefore, groups with children
are likely to plan their trip itinerary prior to, rather than after, arrival
in the destination (Fodness and Murray 1999). Further, larger groups
comprising friends will require greater coordination in order to meet
differential needs than will couples or individuals.
H2: The level of matching between planned and realized actions varies as a
function of the following contingency factors: group composition, product experience, and motivations.
Research Method
Two large-scale data files, from the 1992 face-to-face entry and exit
surveys to Prince Edward Island (PEI), Canada, were used to investigate
the research questions. The entry survey consisted of 2,239 individual
interviews and the exit survey 2,362. The long-interview method
(McCracken 1988) was employed for both data sets. The surveys were
undertaken by the Marketing Agency (a PEI government-sponsored
organization). While the data were collected over a decade ago, they
provide a rare ability for comparing planned versus realized tourism
behavior. Heretofore, the two data sets have never been used in a single
research project. The only previous use was a government descriptive
report profiling tourists’ demographics, attitudes, and behaviors (Marketing Agency 1993) and a study using only the exit interviews on the
impact of PEI’s 1992 advertising campaign on attitudes, behaviors,
and expenditures (Woodside, Trappey and MacDonald 1997). The data
were collected using 13-page entry and 12-page exit questionnaires.
The interviews were completed during the peak tourism season (May
22 to October 5, 1992), a period when over 95% of leisure tourists visit
PEI. The questionnaire was administered at all points of entry and exit
(ferry, airports, and cruise ships) in matching proportions to total trip
visits for each travel mode. Over 93% of all tourists to PEI arrive by one
of two ferries; 6% via the airport and 1% via cruiseships. The interviews
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TOURISM BEHAVIOR
were conducted at ferry wharves prior to boarding, at the province’s
major airport near Charlottetown, and on board selected cruiseships.
At the time of study, no ‘‘fixed-link’’ (bridge) existed connecting
PEI to the North American mainland.
A team of nine interviewers worked on three-day-on, two-day-off
schedules to ensure that weekdays and weekends were covered adequately. Respondents in the exit interviews were screened so as to leave
out those participating in the entry interviews a second time. A quota
sampling procedure was used to insure that the proportions of respondents from Canada, United States and Europe matched the population
of tourists from these three origins: 65% of completed interviews were
with Canadians; 31% from the United States; two-thirds of PEI leisure
tourists were estimated previously to be Canadian and about 30% were
estimated previous to the study to be Americans. The overall cooperation/completion rate for the exit questionnaire was 94%. Due mainly
to some nonresponses to some of the questions, the usable number
to test the propositions was close to 88% of the completed interviews.
The analytical approach is exploratory and empirical. Group-level
analyses (Bass, Tigert and Lonsdale 1968) were performed on data
from the two surveys. A quasi-experiment between-groups research design was made possible from the use of the two data sets (Cook and
Campbell 1979); this procedure ensures that the same participants
being asked earlier planning questions do not sensitize responses in
the second data set. Interviewing the same people twice (at the start
and end of their visits to PEI) likely would have increased their awareness, intentions, and behaviors toward PEI attractions, activities, and
destinations. The two data sets allow quantification of planned and unplanned behavior by tourists entering PEI and actual or unrealized
behavior by those leaving.
Study Findings
The great majority of tourism decisions are likely made while considering issues related to temporal and financial affordability: whether
tourists can afford to take time off; how much they can afford to spend;
which destination option best fits within their time constraints; which
destination option best fits within their financial budget constraints;
and when trade-offs are necessary, what choice heuristics should apply
in selecting among destination options being considered.
While the time a tourist allocates to a vacation is generally fixed (as is
confirmed below), the amount of money set aside for vacation purposes is more flexible. Or put another way, while most people have a
predetermined number of days they will or can be away from home,
the number of consumers with a specific monetary amount (say,
$1,500 for discretionary spending on non-essential items) is likely to
be much smaller. As found in the entry survey, more than one in three
(37%) did not state a specific budget for their trip. It is unlikely that all
the respondents who provided a monetary figure had that exact figure
in mind beforehand. Consumers are likely to have a ballpark figure
MARCH AND WOODSIDE
913
only in mind when considering the financial limits on spending prior
to departure and in the destination.
Nevertheless, among the respondents who could provide a monetary
figure for spending, significant differences occurred between the
planned budget for, and final trip expenditure, on PEI. Spending increased from an average stated budget of $388 per respondent
(n = 1,231; s.d. = 408) to $505 (n = 2,105; s.d. = 576) for stated spending in the exit survey (p = .001). Overall, the average reported spending
behavior is 30% higher than planned spending. Since realized spending was significantly greater than planned, this finding supports
hypothesis one.
Planned and Reported Length-of-Stay. Planned length, expressed in
terms of number of overnight stays, was 3.7 nights (n = 2,341;
s.d. = 5.5), compared to the reported realized average number of 4.2
(n = 2,138; s.d. = 4.9, p < .001). Expressed as a percentage, the difference between planned and reported length-of-stay behavior is 15%.
The significantly greater realized length-of-stay compared to the
planned supports hypothesis one.
What might account for the greater increase in spending more
money than time for the planned versus realized strategies? Some viewpoints from prior research help to answer this question. For example,
Stewart and Vogt (1999), comparing planned versus actual length-ofstay, found that the greatest concordance was in the 7+ day category,
in which 90% of respondents who planned to stay that many or more
days actually stayed that length of time. They conclude with the following self-evident truth, ‘‘If visitors changed plans, they were more likely
to lengthen than shorten their stay. . .’’ Tourists can be confronted with
a number of compelling reasons to shorten their holidays, such as
weather, illness, issues at home, or sheer boredom. Any compulsion
to stay longer must be accompanied by the capacity to extend their
stay.
Time is much less transferable and substitutable than, for example,
money (Leclerc, Schmitt and Dube 1994). If a taxi costs $50 more than
expected, consumption can be reduced in other areas to cover the loss.
But if the taxi ride from the airport takes an hour longer than expected, this may be difficult to recoup. Conversely, time saved cannot
be stored and used later, and hence is less attractive than money saved.
Individuals will spend substantially more money than planned, but are
unwilling or unable to substantially increase the amount of time spent
in the destination. One simple explanation could be that time is less
flexible than money, and that consumers are always more likely to engage in more unplanned spending than extend the amount of time
allocated to the particular task.
Planned and Realized Activities. Respondents were queried about their
intention and consumption of 13 leisure activities. Table 1 ranks the
planned activities, ranging from the most popular, sightseeing (81%
stating they intended to do sightseeing), to the least popular, nightlife
(5%). (Respondents were asked to name their intended activities in
two unaided stages: first, ‘‘What do you intend to do, while on the
Island?’’ and, after naming one activity the respondent was asked
914
TOURISM BEHAVIOR
Table 1. Comparison of Planned and Realized Activities
Activity
Sightseeing
Visiting museums and historical sites
Going to the beach
Lobster supper
General shopping
Antiques and handcrafts shopping
Live theater
Active sports
Land or harbour tour
Nightlife
Water sports
Golfing
Planned %
(n = 2,131)
81
36
22
25
21
16
14
8
6
5
11
9
Done %
(n = 2,239)
87
62
43
44
58
54
22
14
16
13
10
9
Chi-square
28.215
315.827
178.615
174.713
625.682
689.105
41.913
36.741
108.831
70.358
1.217
0.400
p<
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.672
0.842
‘‘Anything else?’’). The particularly large increases in done versus
planned behaviors found in Table 1 may reflect that doing certain
activities occurs because of their availability rather than tourists’ plans.
For example, antique and handicraft outlets are widespread throughout PEI.
Table 2 compares the differences between the planned and reported
activities. It orders the activities by the magnitude of increase between
planned and reported behaviors. It was hypothesized that vacationers
actually engage in a greater number of activities than they plan to, because they often find themselves in destination situations that include
convenient-to-do and previously unknown attractions/activities. An
independent-samples t-test was applied after recoding and combining
the data from the entry and exit surveys. The mean for intended attractions in the entry survey was 2.7 (s.d. = 2.7), compared to a mean of 6.1
(s.d. = 2.5, p < .001) in the exit survey. This finding confirms hypothesis
one.
No significant differences occurred between planned and realized
behaviors for two activities: water sports and golfing. These results
may be unsurprising since both sports require prior experience in
order to participate. But individuals without prior experience could
undertake all other activities. In general, activities represent an overwhelmingly unplanned behavior. This finding may partly be explained
by the leisure-oriented nature of Prince Edward Island as a destination.
The leisure-oriented activities of sightseeing and going to the beach
were easily the two most popular activities. Put another way, these were
‘‘top of mind’’ pull factors in attracting individuals to the destination.
Another noteworthy finding is the sharp increase for ‘‘general shopping’’ and ‘‘shopping for antiques and handcrafts,’’ from 1.6% and
0.9%, to 20% and 15%, respectively. This finding reflects a typical pattern of behavior across most cultures. While shopping tends not to be
reported as an intended holiday activity, it is often the main one cited
at the conclusion of a vacation.
MARCH AND WOODSIDE
915
Table 2. Ranking of Activities between Planned and Realized Behaviors
Activity
% Planned——% Done
% Difference
Behaviours
Shopping for antiques and handcrafts
Shopping in general
Land or harbour tour
Nightlife
Active sports
Visiting museums and historical sites
Lobster supper
Live theater
Going to the beach
Sightseeing
Water sports
Golfing
16
21
6
5
8
36
25
14
22
81
11
9
——
——
!
!
!
!
!
!
!
!
!
!
54
58
16
13
14
62
44
22
43
87
10
9
+235
+230
+171
+136
+80
+75
+67
+54
+48
+7
6
2
Contingency Influences on Planned and Realized Behaviors. While studies
examining the relationships between planned and actual purchase
behavior generally confirm a positive relationship (Manski 1990; Warshaw 1980; Young, DeSarbo and Morwitz 1998), the strengths of the
relationship differ from case to case, depending on the product category and contingencies inherent in the research setting. In this study,
the effects of three contingency influences are examined: product
experience, group composition, and motivation.
Research results support the conclusion that past experience affects
intentions (Fazio and Zanna 1981; Kozak 2001; Kozak and Rimmington 2000; Morwitz and Schmittlein 1992; Muthukrishnan 1995).
Product experience is critical when studying the dynamic choice
processes of consumers new to a market (Heilman, Bowman
and Wright 2000). Routine and habitual buyer behavior allows for
purposive and intelligent behavior without deliberation (Katona
1975). Tourists who vacation at the same place regularly are likely to
engage in little pre-arrival planning, relying instead on their accumulated knowledge and experience from previous visits (Fodness and
Murray 1999).
Table 3. Consumption Behaviors by Degree of Experience
Planned
Firsttimers
n = 1236
Spending
Lengthof-stay
$394
3.0
Moderately
experienced
n = 489
$432
3.8
Realized
Heavy
experienced
n = 637
Firsttimers
n = 1184
Moderately
experienced
n = 397
Heavy
experienced
n = 524
$352
4.8
$518
3.5
$532
4.6
$453
5.5
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TOURISM BEHAVIOR
Table 3 summarizes the planned and realized levels of spending and
length-of-stay for the three levels of experience. Planned comparisons
of means support a significant main effect of strategy (means for realized strategy higher than means for planned strategy, t-test results,
p < .05 for all six mean comparisons available from the table); a significant main effect is found for experience (p < .05 for all planned comparisons, for example, note how spending declines in Table 3 as
experience increases for both planned and realized strategies); and
no significant interaction effects—indicating that experience does
not significantly influence the differences between planned and realized spending and planned and realized length-of-stay.
Similar findings occur for the spending by ‘‘size of party’’ variables.
Figure 1 shows the influences of planned and realized behaviors by the
four levels of party size on spending while visiting PEI; Figure 2 indicates the same relationship for length-of-stay. In short, the interaction
proposition that greater experience or smaller group reflects significantly smaller differences between planned and realized consumption
behaviors is not confirmed.
The survey assumes that respondents formulated plans for a whole
range of trip activities (covering such aspects as accommodation,
places to visit, and things to do). This view is clearly not the case.
While respondents have the option of not answering these questions,
they are not explicitly asked whether they indeed had plans to begin
with. It can be safely assumed that not all behaviors investigated in
Figure 1. Strategy and Group Influences on Spending
MARCH AND WOODSIDE
917
the survey had been considered, formulated, or, in the case of a group
greater than one, discussed or mentioned before the survey was
administered.
CONCLUSION
This study reports the details of research findings with respect to the
relationship between planned and reported consumption behaviors
across two consumer samples. The key findings include empirical evidence supporting a contingency theory for understanding how realized
tourism strategy varies systematically from that planned. The changes
among activities done versus planned reflect what tourists actually find
available to do when in-destination rather than when arriving. Among
PEI tourists relatively few plan to engage in shopping during their Island stays; yet the majority do so. Consequently, the shopping reported
done likely reflects a cultural-sightseeing consumption system among
tourists. This cultural-sightseeing appears to be one of the two ‘‘key
drivers’’ for experiencing PEI as a unique destination brand. The other
key driver includes visiting museums and historical sites (PEI is recognized as the ‘‘birthplace’’ of the Canadian federation). These two key
Figure 2. Strategy and Group Influences on Length-of-Stay
918
TOURISM BEHAVIOR
drivers appear to offer the most effective brand positioning opportunity for marketing PEI as a leisure destination. Thus, rather than touting activities that call attention to the strengths of competing
destinations (such as beaches and water sports available in the Carolinas and Florida), the unique cultural heritage sites and unique product offerings by PEI’s master craft persons reflect the planned-done
conjunctive strength of the Island. Rather than concluding that studies
focusing on one strategy type (planned or realized) is best, the more
useful recommendation is that research combining data on tourists’
plans upon destination arrival and their realized behaviors offers unique and useful views toward understanding tourism and destination
marketing strategy. Research on planned strategy is suited uniquely
for gaining knowledge on how and why arriving tourists come to a specific destination. Research on realized strategy is suited for learning
benefits realized and for studying post-experience attitudes and intentions (satisfactions with specific services and the destination gestalt
experience).
Second, time often is a critical variable. Buehler, Griffin and Ross
(1994) found that, in general, people have a systematic tendency to
underestimate their own completion times, a phenomenon they label
‘‘planning fallacy’’. Applying this argument to a tourism setting, consumers may plan to do more than they can actually complete within
the time constraints of a trip away from home. However, the evidence
here refutes this logic. People engage in more activities and visit more
attractions than they had planned. Gross (1994) argues that responses
to time pressures are contingent upon the degree of intensity of
‘‘objective’’ time pressure (clock and calendar time) and ‘‘subjective’’
pressure (perceived urgency in response to the objective pressures of
clock or calendar deadlines). Another possible explanation for discrepancies between planned and actual behaviors may be that subjective
time pressures have an influence on consumers, who are cautious in
expressing intentions in an entry survey. Read and Loewenstein
(1995) argue that consumers compress future time intervals when making combined choices and hence overestimate the effect of satiation.
This factor helps explain the low levels of intended activity reported
prior to entry. While time issues are important factors to consider, it
would be na€ıve to assume—in the absence of further research—that
time is a critical factor in the discrepancies between planned and actual
behaviors.
Third, situational factors are an obvious explanatory variable. The
extent to which unforeseen events will change a person’s intention depends on how accurately people can predict how their preferences will
change (Simonson 1993). Using the logic of the theory of reasoned action, intentions would most likely match behavior the more the purchase behavior is within the volitional control of the individual.
Fourth, Shapiro and Krishnan (1999) state that consumers often forget
intentions. They argue that marketing models used to forecast sales
should incorporate memory as a variable to explain why some intentions do not lead to purchases. They also point out the complexity of
memory processes (Krishnan and Shapiro 1999). Memory that a per-
MARCH AND WOODSIDE
919
son had intended to do something is prospective (remembering to
remember), whereas memory for the content of the intended action
is retrospective (remembering what to remember). They found that
increasing the importance of an intention facilitated both prospective
and retrospective memory. Entry survey questions may ‘‘increase’’ the
importance of intentions. Individuals are likely to more easily remember activity-based intentions because of their contingency on cues and
their decoupling from ongoing behavior (Bagozzi and Dholakia 1999).
Fifth, the timing of intercept surveys likely influences the nature of
the responses. Wright and Weitz (1977) report that when the outcome
of a choice is to be experienced in the near future, subjects are more
averse to risk than for a more distant time. This finding suggests that
respondents are more conservative in their reporting plans upon arrival than if they are surveyed some days or weeks prior to entry. Sixth,
tourists and leisure consumers are confronted with multiple-option,
not single-option, decisions for many experiences and services. As
such, decisionmaking is more complex, involves higher risk, and is
more susceptible to change and adaptation. In deciding the composition of a holiday, consumers make multiple choices among the bundle
of destinations, bundle of activities and tours, all of which are interlaced with pre-arranged free time. Moreover, the relative importance
of each tourism element (from destination, accommodation, lengthof-stay to budget) may change as couples advance through the family
lifecycle (Cosenza and Davis 1981).
In this study, respondents were unlikely foresee or account for the
complexity of the cognitive decision tasks ahead when completing
the entry survey. Abdul-Muhmin (1999) highlights the difficulty of
understanding this complex task with his argument that consumers
may make multiple-item consumption decisions as a strategy to either
diminish cognitive dissonance or to test consumption or experiential
alternatives that normally would not be ordinarily selected.
Seventh, Weick (1998) suggests that behavior is not goal-directed but
goal-interpreted. People are more comfortable and better able to describe what they did rather than what they plan to do. In applying this
view of human behavior to the present study, two conclusions can be
drawn. First, reports by individuals of their consumption behaviors
immediately upon leaving the consumption space are likely to be fuller
and more detailed than reports of their intentions immediately prior
to entry. Second, and as a consequence of the first point, one may expect gaps between planned and reported behaviors and should also be
extremely cautious in drawing lessons at all about ‘‘planned’’’ behaviors. Many tourists might only be able to report that they plan to ‘‘have
fun’’ in the entry interviews without knowing or being able to retrieve
any details for such a plan. Consider the response in the exit survey to
the question regarding actual spending relative to budget. Only 7% of
respondents in the exit actually reported spending ‘‘over budget.’’ At
least two equally powerful explanations can be presented for this response. The theory and empirical work reported here supports Weick’s
(1998) view of behavior, since the great majority of respondents in
the entry survey did not craft a spending strategy for the impending
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TOURISM BEHAVIOR
duration on Prince Edward Island—and probably provided a ‘‘ballpark’’ figure for intended spending when surveyed. On the other
hand, the more widely held view of behavior might suggest that the
low figure of 7% reflects the desire of survey respondents to appear rational in their consumption behavior.
The nature and effect of questioning in the pre-consumption (entry
survey) and post-consumption (exit survey) phases also shed light on
discrepancies between reported intentions and actual behavior. Questions asked in the exit point elicit a cognitive response from respondents. The survey requests simple facts derived from very recent
memory—such as number of days stayed, places visited, attractions visited, and money spent. Affective reactions are not requested and may
not be retrieved. One can compare this situation with the entry survey.
Respondents are asked to make a series of choices among, for example,
attractions and activities. This forces them to cognize places, objects
and experiences, yet the reality is that the ‘‘decisions’’ (putting aside
the doubtful legitimacy of this nomenclature) reported in the survey
are much more likely to constitute affective reactions than be rationally
conceived goals. In a sense, there is a psychic gap between the asking of
the question and the moment in the consumption system that the decision to consume the product is considered (if in fact that moment does
arrive). The magnitude and influence of this psychic gap far exceeds
the time lapse between the surveying of intentions and the actualization of behaviors.
Tests of the competing theoretical propositions as to why planned
are often less than realized behaviors need to be examined in future
research. This study focuses on probing the extent of the differences
between planned and realized, not on providing a critical test as to
the efficacy of the multiple rationales found in the literature regarding
such differences.
In sum, this report complements and extends Young, DeSarbo
and Morwitz, who propose, ‘‘[I]ntentions appear to almost always
provide biased measures of purchase propensity, sometimes underestimating actual purchasing and other times overestimating actual
purchasing’’ (1998:189). Both studies to examine planned and realized behavior are valuable: research focusing on intentions is helpful
in particular for learning motivational and strategic planning drivers
that result in destination visits; research focusing on realized behaviors is helpful in particular for learning tourists’ reports on done
activities—and consequently what experiences likely encourage and
discourage repeat visits. Therefore, examining both planned and
realized strategies contributes to tourism theory and management
insight.
Acknowledgements—The authors are grateful for use of the data sets provided by the Tourism
Department, Province of Prince Edward Island, Canada, for the empirical analyses that this
article reports.
MARCH AND WOODSIDE
921
REFERENCES
Abdul-Muhmin, A.
1999 Contingent Decision Behavior: Effect of Number of Alternatives to be
Selected on Consumers’ Decision Processes. Journal of Consumer Psychology
8:91–111.
Abratt, R., and S. Goodey
1990 Unplanned Buying and In-Store Stimuli in Supermarkets. Managerial
and Decision Economics 11:11–121.
Agee, T., and B. A. S. Martin
2001 Planned or Impulse Purchases? How to Create Effective Infomercials.
Journal of Advertising Research (December):35–42.
Ajzen, I., and B. Driver
1992 Application of the Theory of Planned Behavior to Leisure Choice.
Journal of Leisure Research 24:207–224.
Bagozzi, R., and U. Dholakia
1999 Goal Setting and Goal Striving in Consumer Behavior. Journal of
Marketing 63:19–32.
Bagozzi, R., and R. Nataraajan
2000 The Year 2000: Looking Forward. Psychology and Marketing 17:1–11.
Bass, F., D. Tigert, and D. Lonsdale
1968 Market Segmentation: Group versus Individual Behavior. Journal of
Marketing Research 5:264–270.
Beatty, S., and M. Ferrell
1998 Impulse Buying: Modeling its Precursors. Journal of Retailing
74:169–191.
Becken, S., and J. Gnoth
2004 Tourist Consumption Systems among Overseas Visitors: Reporting on
American, German, and Australian Visitors to New Zealand. Tourism
Management 25:375–385.
Belk, R.
1974 An Exploratory Assessment of Situational Effects in Buyer Behaviour.
Journal of Marketing Research 11:156–163.
1975 Situational Variables and Consumer Behaviour. Journal of Consumer
Research 2:157–163.
Bettman, J. R.
1979 Memory Factors in Consumer Choice: A Review. Journal of Marketing
43:37–53.
Bettman, J., M. Luce, and J. Payne
1998 Constructive Consumer Choice Processes. Journal of Consumer Marketing 25:187–217.
Bruce, V., and P. R. Green
1991 Visual Perception. London: Lawrence Erlbaum Associates.
Buehler, R., D. Griffin, and M. Ross
1994 Exploring the Planning Fallacy: Why People Underestimate their
Task Completion Times. Journal of Personality and Social Psychology
67:366–381.
Chadwick, R.
1987 Concepts, Definitions, and Measures Used in Travel and Tourism
Research. In Travel, Tourism and Hospitality Research, B. Ritchie and C.
Goeldner, eds., pp. 101–116. New York: Wiley.
Clawson, C.
1971 How Useful are 90-day Purchase Probabilities? Journal of Marketing
Research 35:43–47.
Cobb, C. J., and W. D. Hoyer
1986 Planned Versus Impulse Purchase Behaviour. Journal of Retailing
62(Winter):384–409.
Cook, T., and D. Campbell
1979 Quasi-Experimentation. Boston: Houghton Mifflin.
922
TOURISM BEHAVIOR
Cosenza, R., and D. Davis
1981 Family Vacation Decision Making Over the Family Life Cycle: A
Decision and Influence Structure Analysis. Journal of Travel Research
20(4):17–23.
Dann, G.
1981 Tourist Motivation: An Appraisal. Annals of Tourism Research 8:187–219.
Engel, J. F., R. D. Blackwell, and R. W. Miniard
1993 Consumer Behavior (7th ed.). New York: Dryden Press.
Fazio, R., and M. Zanna
1981 Direct Experience and Attitude Behavior Consistency. Advances in
Experimental Social Psychology 14:161–202.
Feldman, J., and J. Lynch
1988 Self-Generated Validity and Other Effects of Measurement on Belief,
Attitude, Intention and Behavior. Applied Psychology 37:421–435.
Ferber, R., and R. Piskie
1965 Subjective Probabilities and Buying Intentions. Review of Economics and
Statistics 47:322–325.
Filiatrault, P., and J. Ritchie
1988 The Impact of Situational Factors on the Evaluation of Hospitality
Services. Journal of Travel Research 26(1):29–37.
Fisher, R.
2001 The Role of Collaboration in Consumers’ In-Store Decisions. Advances in
Consumer Research 28:251.
Fodness, D., and B. Murray
1999 A Model of Tourist Information Search Behavior. Journal of Travel
Research 37:220–230.
Gardner, M. P., and D. W. Rook
1987 Effects of Impulse Purchases on Consumers’ Affective States. In Advances
in Consumer Research, M. J. Houston ed. (Vol. 15). Provo, Utah: Association
for Consumer Research.
Gitelson, R., and J. Crompton
1983 The Planning Horizons and Sources of Information Used by Pleasure
Vacationers. Journal of Travel Research 22(1):2–7.
Gormley, R.
1974 A Note on Seven Brand Rating Scales and Subsequent Purchase. Journal
of Market Research Society 16:242–244.
Gross, B.
1994 Consumer Responses to Time Pressure: A Qualitative Study with
Homeowners in Foreclosure. Advances in Consumer Research 21:121–125.
Heilman, C., D. Bowman, and G. Wright
2000 The Evolution of Brand Preferences and Choice Behaviors of Consumers
New to a Market. Journal of Marketing Research 37:139–155.
Howard, J., and J. Sheth
1969 The Theory of Buyer Behavior. New York: Wiley.
Inman, J., and R. Winer
1998 Where the Rubber Hits the Road: A Model of In-store Consumer
Decision Making. Marketing Science Institute, Report 98-122 Cambridge:
Marketing Science Institute.
Juster, F. T.
1964 Anticipations and Purchases: An Analysis of Consumer Behavior. New
Jersey: Princeton University Press.
Kalwani, M., and A. Silk
1982 On the Relationship and Predictive Ability of Purchase Intention
Measures. Marketing Science 1:243–286.
Katona, G.
1975 Psychological Economics. New York: Elsevier.
Kollat, D., and R. Willett
1967 Customer Impulse Purchasing Behavior. Journal of Marketing 6:21–31.
Kozak, M.
2001 Repeaters’ Behavior at Two Distinct Destinations. Annals of Tourism
Research 28:785–808.
MARCH AND WOODSIDE
923
Kozak, M., and M. Rimmington
2000 Tourist Satisfaction with Mallorca, Spain, as an Off-season Holiday
Destination. Journal of Travel Research 39:259–268.
Krishnan, H., and S. Shapiro
1999 Prospective and Retrospective Memory for Intentions: A Two-Component
Approach. Journal of Consumer Psychology 8:141–166.
Leclerc, F., B. Schmitt, and L. Dube
1994 Foreign Branding and its Effects on Product Perceptions and Attitudes.
Journal of Marketing Research 31:263–270.
Lynch, J., and T. Srull
1982 Memory and Attention Factors in Consumer Choice: Concepts and
Research Methods. Journal of Consumer Research 9:18–37.
Manski, C.
1990 The Use of Intentions Data to Predict Behavior: A Best-case Analysis.
Journal of American Statistical Association 85:934–940.
Marketing Agency
1993 Visitor Survey of Prince Edward Island. Marketing Agency, Prince Edward
Island.
Mayo, E., and L. Jarvis
1981 The Psychology of Leisure Travel. Boston: CBI Publishing.
McCracken, G.
1988 The Long Interview. Newbury Park: Sage.
McIntosh, R., and C. Goeldner
1990 Tourism: Principles, Practices, Philosophies. New York: Wiley.
Morrison, A.
1996 Hospitality and Travel Marketing. Albany: Delmar.
Morwitz, V., and D. Schmittlein
1992 Using Segmentation to Improve Sales Forecasts Based on Purchase Intent:
Which ‘‘Intenders’’ Actually Buy? Journal of Marketing Research 29:391–405.
Muthukrishnan, A.
1995 Decision Ambiguity and Incumbent Brand Advantage. Journal of
Consumer Research 22:98–109.
Pearce, P., and M. Caltabiano
1983 Inferring Travel Motivations from Travelers’ Experiences. Journal of
Travel Research 22(1):25–30.
Perdue, R.
1986 The Influence of Unplanned Attraction Visits on Expenditures by TravelThrough Visitors. Journal of Travel Research 25(1):14–19.
Peter, J. P., and J. C. Olson
1999 Consumer Behavior and Marketing Strategy (5th ed.). Boston: Irwin
McGraw-Hill.
Prasad, V.
1975 Unplanned Buying in Two Retail Settings. Journal of Retailing 51:3–12.
Read, D., and G. Loewenstein
1995 Diversification Bias: Explaining the Discrepancy in Variety Seeking
between Combined and Separated Choices. Journal of Experimental Psychology: Applied (1):34–39.
Rook, D. W., and R. J. Fisher
1995 Normative Influences on Impulsive Buying Behaviour. Journal of
Consumer Research 22(December):305–313.
Rook, D., and M. Gardner
1993 In the Mood: Impulse Buyings’ Affective Antecedents. In Research in
Consumer Behavior, 6, J. Arnold-Costa and R. Belk eds., pp. 54–71. Greenwich:
JAI Press.
Rook, D., and S. Hoch
1985 Consuming Impulses. In Advances in Consumer Research, 12, M.
Holbrook and E. Hirschman, eds., pp. 23–27. Provo: Association for
Consumer Research.
Shapiro, S., and H. Krishnan
1999 Consumer Memory for Intentions: A Prospective Memory Perspective.
Journal of Experimental Psychology 5(2):169–189.
924
TOURISM BEHAVIOR
Shoemaker, S.
1994 Segmenting the U.S. Travel Market According to Benefits Realized.
Journal of Travel Research 33(1):8–21.
Simonson, I.
1993 Get Closer to Your Customers by Understanding How They Make
Choices. California Management Review 27:68–84.
Solomon, M.
1999 Consumer Behavior (4th ed.). Upper Saddle: Prentice Hall.
Stayman, D., and R. Deshplande
1989 Situational Ethnicity and Consumer Behavior. Journal of Consumer
Research 16:361–371.
Stern, E.
1962 The Significance of Impulse Buying Today. Journal of Marketing
26:59–62.
Stewart, S., and C. Vogt
1999 A Case-based Approach to Understanding Vacation Planning. Leisure
Sciences 21:79–95.
Tauber, E.
1975 Predictive Validity in Consumer Research. Journal of Advertising
Research 15:59–64.
Tobin, J.
1959 On the Predictive Value of Consumer Intentions and Attitudes. Review of
Economics and Statistics 41:1–11.
Warshaw, P.
1980 Predicting Purchase and Other Behaviors From General and Contextually Specific Intentions. Journal of Marketing Research 17:26–33.
Weick, K. E.
1998 The Social Psychology of Organizing. New York: McGraw-Hill.
Weun, S., M. A. Jones, and S. E. Beatty
1998 The Development and Validation of the Impulse Buying Tendency Scale.
Psychological Reports 82:1123–1133.
Woodside, A., and L. Jacobs
1985 Step two in Benefit Segmentation: Learning the Benefits Realized by
Major Travel Markets. Journal of Travel Research 24(1):7–13.
Woodside, A., and C. Dubelaar
2002 A General Theory of Tourism Consumption Systems: Conceptual
Framework and an Empirical Exploration. Journal of Travel Research
40:120–132.
Woodside, A., R. Trappey, and R. MacDonald
1997 Measuring Linkage-Advertising Effects on Customer Behavior and Net
Revenue: Using Quasi-Experiments of Advertising Treatments with Novice
and Experienced Product-Service Users. Canadian Journal of Administrative
Sciences 14:214–228.
Wright, P., and B. Weitz
1977 Time Horizon Effects on Product Evaluation Strategies. Journal of
Marketing Research 14:429–443.
Young, M., W. DeSarbo, and V. Morwitz
1998 The Stochastic Modelling of Purchase Intentions and Behavior.
Management Science 44:188–202.
Submitted 21 November 2003. Resubmitted 4 May 2004. Resubmitted 5 June 2004. Accepted
28 July 2004. Final version 21 December 2004. Refereed anonymously. Coordinating Editor:
Jeurgen Gnoth