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Tourism Management 26 (2005) 815–832
www.elsevier.com/locate/tourman
Building and testing theories of decision making by travellers
Ercan Sirakayaa,, Arch G. Woodsideb
a
Department of Recreation, Texas A & M University, Parks and Tourism Sciences, 256A Francis Hall, College Station, TX 77843 2261, USA
b
Boston College, USA
Received 17 April 2003; accepted 25 May 2004
Abstract
How does the tourism literature model major recreational travel decisions? What influences do the ‘‘grand models’’ in consumer
research have on tourist destination choice models? This article provides building-block propositions for creating useful theories of
decision making by travelers via a qualitative review of the tourist decision-making literature. The grand models of decision-making
in consumer research inform the propositions advanced. The article describes trends in developing traveler destination choice
models. Along with examining decision-making propositions from the literature, the article covers important issues in need of
resolution for making advances in understanding, describing, and predicting tourist decision-making.
r 2004 Elsevier Ltd. All rights reserved.
Keywords: Consumer behavior theory; Tourism behavior; Decision-making models; Behavioral and choice-sets models
1. Introduction
Scholars from a variety of social science disciplines
focus on how individuals go about making decisions.
The utility of this work is evident in the field of
marketing, in which a substantial body of decisionmaking literature builds from since the 1950s. A
systematic and in-depth understanding of buying
processes is the main goal of pioneering models of
consumer behavior (see Howard, 1994; Runyon, 1980).
Nicosia (1966), Engel, Kollat, and Blackwell (1968),
Howard and Sheth (1969) and Gilbert (1991) provide
the earliest and most influential models, the ‘‘grand
models,’’ of consumer behavior. These models explain
decisions relating to tangible, manufactured, products.
Although not designed to explain service purchase
decisions, the grand models were used by tourism
scholars as a starting point for explaining the process
used to purchase tourism services. The tourism literature
Corresponding author. Tel.: +1-979-862-8819; fax: +1-979-8450446.
E-mail address: esirakay@rpts.tamu.edu (E. Sirakaya).
0261-5177/$ - see front matter r 2004 Elsevier Ltd. All rights reserved.
doi:10.1016/j.tourman.2004.05.004
now offers substantial conceptual and empirical works
to describe tourists’ destination choice processes by
empirically probing the following issues. What are the
travelers’ psychological processes during judgment or
choice tasks (i.e., motivation studies)? Which choices are
made among the alternatives considered and what cues
are more important on the judgment or on the choice of
a specific destination?
In general, this literature reports that tourists follow a
funnel-like procedure of narrowing down choices among
alternate destinations. Decision-making can be broken
down into a series of well-defined stages: (a) recognition
that there is a decision to be made, (b) formulation of
goals and objectives, (c) generation of an alternative set
of objects from which to choose, (d) search for
information about the properties of the alternatives
under consideration, (e) ultimate judgment or choice
among many alternatives, (f) acting upon the decision,
and (g) providing feedback for the next decision (Carroll
& Johnson, 1990; Einhorn & Hogarth, 1981; Engel,
Blackwell, & Miniard, 1986; Huber, 1980). Evidently,
this decision-making process is influenced by both
psychological or internal variables, for example,
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attitudes, motivation, beliefs and intentions, and nonpsychological or external variables (e.g., time, pull
factors and marketing mix). Given the centrality of the
selection decision process to tourists’ behavior, a clear
understanding of the complexities and interrelationships
of these variables is an important research agenda.
This article reviews and integrates the main conceptual and empirical work that has been reported in the
tourism literature. This integration helps to identify
strengths, limitations, and knowledge gaps in the
literature. Consequently, the review develops a set of
research propositions to help guide future research. The
goal is to increase sense making of tourism decisionmaking by offering theory-based propositions to guide
research. The aim of the paper is not to compulsively
annotate the past, but rather to summarize the field’s
collective understanding of decision processes of potential tourists using a critical review of the literature.
Throughout the article, ‘‘tourism service’’ is used as a
generic, umbrella term embracing both the intangible
(service) and tangible aspects (goods) of a destination.
A major task in all areas of science is the development
of theory.... Scientists have known for centuries that a
single study will not resolve a major issue. Indeed, a
small sample study will not even resolve a minor
issue. Thus, the foundation of science is the culmination of knowledge from the results of many studies
(Hunter, Schmidt, & Jackson, 1982, p. 10).
Meta-analysis is a quantitative method for combining
findings (e.g., estimating the average and variance of an
effect size for a given hypothesis tested across several
independent studies, see Woodside & Dubelaar (2003)
for a meta-analysis related to tourism science) in order
to draw conclusions about the overall association
among variables (Rosenthal, 1987; Doucouliagos,
1995). According to Hunter and Schmidt (1990), one
of its major benefits is that it facilitates the digestion of a
large volume of empirical literature on a given subject by
condensing numerous studies into one study. Therefore,
it is easier to refer to, for example, Woodside and
Lysonski (1989), than to refer to a long list of studies,
reporting different models, hypotheses, propositions
and results. The approach used in this study broadens
the meta concept for the purpose of synthesizing and
advancing theory; an approach that we label, ‘‘metatheory,’’ that is, creating a set of associated propositions
based on prior contribution to theory, with the metatheory enriching understanding and identifying previously unreported nuances in the discipline. Thus, the
following discussion does not include a true metaanalysis across studies but serves to identify areas for
future meta-analysis undertakings as well as new
empirical studies that examine the proposed theoretical
advances.
2. Advancing consumer decision-making in tourism
behavior
Consumer decision-making research has grown exponentially during the past three decades. Theories such
as the expected utility theory (von Neumann &
Morgenstern, 1947), prospect theory (Kahneman &
Tversky, 1972), regret theory (Bell, 1982); satisfying
theory (Simon, 1956); The theory of reasoned action
(Ajzen & Fishbein, 1980) and its derivative theory of
planned behavior (Ajzen, 1985, 1987) have been developed and tested in a variety of contexts. The range of
contexts (e.g., well-defined to ill-defined choice situations) within which these decision-making theories are
used is too broad to specifically deal within a single
manuscript. A particular theory is likely to explain a
specific aspect of an individual’s decision in a given
context. Multiple decision theories when used together
are likely to explain a wider range of decision behavior
across an expanded range of contexts. So far, however,
no single unifying theory has emerged across disciplines
to describe, explain, or predict consumer decisions, and
it seems unlikely that individual decision processes fit
neatly into a single decision theory.
Abelson and Levi (1985) categorize decision-making
literature on three continua: structure versus process
orientation, risk free versus risky choice models, and
normative versus descriptive models. Abelson and Levi
suggest that risk-free decisions involve preferences,
whereas risky decisions include probabilities. A continuum of choice environments exists that ranges from
well-defined to ill-defined choice situations. Well-defined
choice situations include both risky and risk-free
decisions, while ill-defined choice situations generally
involve risky decisions because of the uncertainty of the
outcome. A majority of tourism decisions may be illdefined choice situations where outcomes have unknown
probabilities, because of the intangible and experiential
nature of tourism. Normative and descriptive decision
models differ in their conceptualizations of what a
decision maker does, and there is sometimes a tendency
to explain, ‘‘how individuals should choose (normative
models) versus how individuals choose (descriptive
models)’’ (Abelson & Levi, 1985, p. 232). A key
difference between normative and descriptive models
revolves around whether tourists are looking for
optimum decisions or simply accepting a satisfying
solution for a wide array of reasons.
Most human decisions are not perfectly rational,
because they are influenced by a multitude of factors,
which may constraint or motivate them to act irrationally (Bettman, Luce, & Payne, 1998). Decision biases
occur often in the decision process. Such biases occur, in
part, due to the use of heuristics or ‘‘rules of thumb’’
which are shortcuts used to simplify decisions (Tversky
& Kahneman, 1971, 1973, 1974; Kahneman, 1973;
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Kahneman & Tversky, 1979). In general, tourism
models view decision-makers as functional (or utilitarian) people (Homo-Economicus), although some acknowledge the role of constraints on tourism decisions
(for example, Um & Crompton, 1990; Woodside &
Lysonski, 1989).
Type of involvement and level of decision-making are
the two variables widely used to explain differences in
consumers’ decision processes. Purchase involvement is
the level of concern for or interest in the purchase
process, triggered by the need to consider a particular
purchase, and involvement ‘‘is influenced by the interaction of individual, product and situational characteristics’’ (Hawkins, Best, & Coney, 1995, p. 425). Purchase
involvement relates to the type of decision-making.
Extensive problem solving is associated with high
involvement purchases, whereas habitual decision-making is associated with low involvement purchases
(Hawkins et al., 1995). Limited decision-making process
is a level between habitual and extensive decisionmaking, where the decision process is not as complex
and highly involved as extensive decision-making, yet
not as simple as habitual decision-making. Most tourism
service purchases are considered to be high-involvement,
extensive decision-making purchases, because of the
relatively high costs, both monetary and non-monetary,
involved in these decisions. For example, planning a
pleasure trip to another country involves a relatively
high perceived risk of making a bad decision, investing a
significant amount of time searching for information,
and a considerable monetary outlay. However, low
involvement is likely when decision-makers have prior
experience about the service (Teare, 1992). Prior
experience leads to a more cursory information search,
more confidence in the decision choice, and less
perceived risk (Woodside, MacDonald, & Trappey,
1997).
3. Information-processing theory and grand models of
consumer decision-making
Information-processing theory is central to all consumer behavior models (Bettman et al., 1998; Gabbott
& Hogg, 1994). This theory states that the consumer
decision-making process involves five main stages: (1)
problem recognition, (2) information search, (3) alternative evaluation and selection, (4) outlet selection and
purchase, and (5) post-purchase processes (Hawkins et
al., 1995). Consumer behavior theorists believe that
psychological mechanisms underline each of these
stages. For example, problem recognition essentially
represents a discrepancy between a consumer’s desire
and his/her perceived state (Urbany, Dickson, & Wilkie,
1989). In this stage, the inputs for the process are
significant, symbolic and social–environmental stimuli
817
(Howard & Sheth, 1969). During information search,
alternative evaluation, and selection, and post-purchase
evaluation, the consumer unconsciously utilizes a
number of psychological processes (i.e. beliefs, motives,
attitudes). In the alternative evaluation stage, the
consumer may use decision rules to evaluate and choose
a final service offering. If the evaluation is not successful
or complete, the decision stays inconclusive and the
search restarts from the beginning. After a purchase, the
consumer continues evaluating his/her decision, which
may provide inputs for future decisions. Representation
of the consumer decision process using these principles
was a characteristic of the early pioneering models
proposed by Howard and Sheth (1969), Nicosia (1966)
and Engel et al. (1968). These three models are
considered the grand models of consumer behavior,
and many tourism models have been based upon them.
When reviewing decision-making models, Gilbert
(1991) suggests that the grand models share six common
points. First, they perceive consumer behavior to be a
constant decision-making process. Second, the behavior
of the individual consumer is emphasized. Third,
behavior is treated as a functional (or utilitarian)
concept that can be explained. Fourth, a buyer is viewed
as an individual who searches, evaluates, and stores
information. Fifth, buyers narrow down the range of
information in time, and choose from the alternatives
they developed during the decision-making process.
Sixth, feedback from the final purchase is included in the
models to emphasize the effect of the decision on future
purchases.
4. Foundational travel decision models
Our analysis of behavioral approaches in tourist
decision-making focuses on frequently cited models
utilized in tourism research. An analysis of the foundational models of travel decision-making (Mathieson &
Wall, 1982; Mayo & Jarvis, 1981; Middleton, 1994;
Moutinho, 1987; Schmoll, 1977; Um & Crompton, 1990;
Van Raaij & Francken, 1984; Wahab, Crampon, &
Rothfield, 1976; Woodside & Lysonski, 1989) reveals
that these models were successful in providing insights
into the specific nature of tourism purchase behavior
(Gilbert, 1991). These models are common, in that, the
traveler’s decision-making process was approached as a
functional decision-making activity that is influenced by
a number of psychological and non-psychological
variables.
Table 1 displays the key propositions, major contributions, and limitations of these models in the
tourism decision-making literature.
One of the first foundational models of travel
decision-making is that of Clawson and Knetsch
(1966). These two economists proposed a five-phase
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Table 1
Evaluation of decision-making models in tourism
Key proposition(s)
Major contribution(s)
Limitation(s)
Wahab, Crompon,
Rothfield
1976
A tourist is a rational decision maker (Homo
Economicus) who tries to maximize the utility
and, thus, assess costs and benefits of his/her
actions before committing themselves to a
purchase
There are unique elements in a tourism product
which differentiate them from other products
Tourism purchase decisions are risky, require
extensive problem solving, advance planning
Recognition of unique product aspects of
tourism
Heavy dependency on grand models in setting
up the theory base (Gilbert, 1991)
Integration of psychological and economic
theories into one comprehensive model
Mostly focused on individual as the decisionmaking entity neglecting interpersonal, social
and family influences
Inclusion of variables such as needs, motivations,
destination image, spontaneity of purchase
decision, influence of risk and uncertainty,
influences family and friend that define unique
aspect of tourism into tourism decision process
models
Considers most decisions as perfectly rational
Schmoll
Mayo and Jarvis
1977
1981
Tourist is a rational decision maker within his/
her capabilities and limited information
Traveler decision processes are affected by four
components: travel stimuli, personal and social
determinants, exogenous variables
Decision process involves several successive steps
Travelers utilize either routine, impulsive or
extensive decision-making styles when making
choices
Decisions are dynamic, are prone to chance
according to circumstances
Understanding travel decisions requires an
analysis of effects of social and psychological
factors
Traveler decision-making process is a function of
four sets of variables (travel opportunities,
communication effort, customer goals and
intervening variables)
Decision-making process can be mapped and
traced through successive stages
Relates theoretical concepts to real world
Explicitly specifies the relationships between
various components and shows which factors
have influence on choice decisions
Draws attention to the influence of constraints in
travel decisions
Travel decisions are a function of social and
psychological factors
The model is not reflexive and thus not dynamic.
It neglects the outcome’s role in influencing the
personality of the consumer for the next decision
(missing reflexive loop)
Lack of parsimony
Difficult to operationally define certain variables
Based on grand models that traditionally ignore
unique characteristics of services
Operational definitions used on some variables
are very unclear
Low predictive ability due to internal conflicts
between statements
Emphasizes the role of group and family in
choice decisions
Omission of relevant variables (e.g., external
stimuli)
No formal testable propositions developed
Attention to the role of constraints in travel
decisions
Empirical tests are difficult due to
operationalization problems
Successfully combines variables which are
commonly believed to be the determinants of
tourist behavior
Low explanatory and predictive ability
Lack of parsimony
Lack of causality and temporal order
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Authors
Moutinho
1987
Travel decisions are far more affected by external
forces, especially social influences such as role
and family influences, reference groups, social
classes, culture and subculture
Tourism services are purchased in a sequence
and not always as a tour package
Destination choice is seen as a compulsory
subdecision among other travel related decisions
Matieson and Wall
1982
Travel distance is not considered as a cost to
tourists as some tourist may enjoy the travel part
Van Raaij and
Francken
1984
Views a tourist as a rational decision-maker who
wants to maximize utility
Views travel decision-making as a process
consisting of various stages such as formation of
a need or desire for travel, information search,
travel decisions, travel preparations and
experience and evaluation of trip
Joint decision-making is the central part of
tourists’ decision process
Household-related variables plan an important
role in vacation decisions
Involvement and memories plays an important
role in destination choice decisions
Decision-making is a sequential activity
Woodside and
Lysonski
1989
Omission of relevant variables such as
perception, memory, personality and
information processing.
Thus, low explanatory and predictive power
Lack of parsimony (very complex)
Difficult to quantify
Attention to joint decision processes and
household-related variables
Explicit recognition of the interaction of
household-related variables (i.e., lifestyle, power
structure, role, decision-making style) with
individual-related factors (attitude, aspirations,
etc.)
The importance of post-purchase evaluation on
decision-making styles later
The model is dynamic in that it recognizes the
outcome’s role in influencing the personality of
the consumer for the next decision (reflexive
loop)
Parsimony, simple but theoretically sound
perspective on tourists’ decision processes
Undermining the role of individual decisions
Hypothetical associations among decision
factors
Lack of specificity of variables
Lack of operational definitions of constructs
Lack of dynamism of the model in that the
consumer does not change his behavioraccording
to his/her decision experience
Limited description and testing of some of the
constructs and the relationships in the model (i.e.
affective associations).
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Post-purchase evaluations play an important role
in subsequent decisions later
Destination choice is a result of a categorization
process. Awareness of a tourism product will
transfer the same from long-term memory to
Successfully integrates many theories of
consumer behavior literature into tourist
decision-making model
Includes cognitive distance as an important
factor in decision-making
The model is reflexive and thus very dynamic. It
recognizes the outcome’s role in influencing the
attitudes set and subsequent behavior of the
consumer for the next decision (reflexive loop)
A behavioral model that successfully integrates
theories in various social science disciplines
including that of psychology, economics and
sociology
Recognizes the importance of destination
characteristics on image formation and
subsequent decision-making process
Does not specifically focus on destination choice
process
The model premises at times are not very clear,
especially when he considers destination choice
decisions and other travel related decisions
Empirical tests are difficult due to
operationalization problems
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Recognizes unique features of a tourism product
Conceptually sound (well formed)
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Post-purchase evaluations have an impact on
subsequent purchase behaviors
Correctly identifies temporal order of variables
that affect the purchase behavior
Unclear relationship between travel stimuli and
the rest of the model
Suffers from lack of parsimony (very complex)
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Table 1 (Continued)
Authors
Year
Key proposition(s)
working memory causing that product to be
chosen over other possible products
Cognitive and emotional factors mediate the
relationship between choice sets and the actual
choice
Choice is affected by the interaction of intention
to visit and situational variables
1992
Human behavior is the function of intentions
and perceived behavioral control over the
behavior
Intentions are formed with the influence of three
conceptually independent determinants: attitude
toward behavior, subjective norm and perceived
behavioral control, all of which are assumed to
interact with each other.
Leisure decisions can be considered a part of a
general human behavior theory (theory of
planned behavior) that involves cognitive as well
as affective components.
Um and Crompton
1990
Attitudes play an important role in destination
decision processes
Interaction between constraints and image are
integral for destination choice decisions
Integration of various disciplinary knowledge
into one comprehensive model of tourist
decision-making
Addition of variables that were overlooked by
previous models (e.g., affective associations,
traveler destination preferences, situational
variables and their place of impact)
Size of the consideration set is small (three to five
destinations).
Successful application of the theory of planned
behavior leisure situations
Exploratory nature of the study with a relatively
small and non-representative sample.
Improved prediction and understanding of
leisure behavior by going beyond the original
theory (addition of two constructs): (1) the role
of involvement and (1) the role of mood and
affect
Theoretically sound explanation
Use of cross-sectional survey data
Lack of empirical support in actual choice
processes.
The premise that intentions to perform leisure
activities are different than other types of human
behavior seems to be ‘‘a leapfrogged’’ argument
without sufficient justifications for doing so
Originality is low
A very narrow presentation of leisure activities
The tie between the variables ’’involvement’’ and
’’mood/affect’’ and the constructs in the original
theory are not clear
Conceptualization, operationalization and
empirical testing of attitudes in real destination
choice processes
Efficiency in the operationalization of the
dependent variable (eliminated the need for
measuring behavioral intentions)
Potential traveler’s awareness sets and evoked
A very general explanation of leisure choice
behavior
A direct application of a human behavior theory
rather than a specifically designed study that
considers leisure choice situations.
Measurement problems of the theoretical
constructs
Sampling problems
Accuracy and validity of self-reported leisure
activities
Untested relationships in the model
Lack of attention to emotions and joint decision
processes
Mostly cognition and individual traveler-based.
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Intentions are assumed to capture the
motivational factors that influence the behavior
Limitation(s)
E. Sirakaya, A.G. Woodside / Tourism Management 26 (2005) 815–832
Ajzen and Driver
Major contribution(s)
sets were identified longitudinally, confirming
earlier claims that destination choice sets narrow
down over time (funneling effect)
Provision of a simplistic but theoretically sound
decision process model.
Tourist choices are not always rational (utility
maximizing)
Interactions by the members of the travel party
play an important role in decision-making
Destination choice is one of many travel related
decisions one has to make
Use of a qualitative data to offer insights into
decision-making styles of individuals
The role of travel party can play in travel
decisions
Recognizes individual decision-making styles
Mostly focused on individual as the decisionmaking entity
The model is not reflexive and thus not dynamic.
It neglects the outcome’s role in influencing the
personality of the consumer for the next decision
(missing reflexive loop)
Difficult to operationally define certain variables
Destination choice is subsumed under many
travel-related decisions (i.e., destination and
mode of travel)
Sources : Wahab et al. (1976); Schmoll (1977); Mayo and Jarvis (1981); Moutinho (1987); Mathieson and Wall (1982); Van Raaij and Francken (1984); Woodside and Lysonski (1989); Ajzen and
Driver (1992); Um and Crompton (1990); Woodside and MacDonald (1994).
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1994
Measurement problems (lack of comparison of
at the abstract level, generation of destination
attributes by two seemingly different
populations, experts and tourists which may
produce noncomparable lists...we don’t know
what abstraction level is used by actual decisionmakers)
The model is not reflexive and thus not dynamic.
It neglects the outcome’s role in influencing the
personality of the consumer for the next decision
(missing reflexive loop)
Lack of tracing the actual decision-process
(measuring decisions after such decisions have
been already made)
Unsubstantiated assumption about the linearity
of relationships between perceived inhibitors and
facilitators
Operationalization of attitudes as the difference
between perceived facilitators and perceived
inhibitors
Heavy reliance on Grand Models
Suffers from lack of parsimony (very complex)
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Woodside and
MacDonald
Marginalization of socialization process.
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outdoor recreation experience model to delineate vacation experiences and the decisions involved in the
process. Their five-stage travel model involved modeling
decision processes of travelers from a macro-perspective
starting with the anticipation phase, followed by travel
to actual site, on-site experiences and activities, travel
back, and concluding with recollection of experiences.
Each of the phases in the model begs for an explanation
of how an individual reaches the ultimate decision
phases such as the site selection decision. Since the
authors did not elaborate on how the individual
decisions are made at the micro level, a direct
comparison of their model with the rest of the
models—the focus of this paper—cannot be made.
Although its predictive power regarding individual
destination choice decisions is limited, at the macro
level it has been used successfully to predict aggregate
demand to travel sites. This section of the review focuses
on choice models instead.
Wahab et al. (1976) propose a model that delineated
tourists’ decision-making process based on the realization that tourist behavior is a rational decision activity.
In other words, a potential traveler assesses the costs
and benefits of his/her actions before committing
themselves to a purchase. In addition, this model asserts
that tourism services have unique characteristics that
differentiate them from other products (e.g., intangibility, involve risks). This model is similar to Nicosia’s
model, in that it explicitly recognizes the impact of the
seller on tourists’ decision-making process, yet the
emphasis was still on the tourist. According to Wahab,
Crampon, and Rothfield’s model, tourism firms affect
tourist(s) behavior, the consumer in turn, affects how
firms make marketing-related decisions.
The second model worthy of discussions is the model
proposed by Van Raaij and Francken (1984). Their
‘‘vacation-sequence’’ model resembles that of Engel et
al. (1968). A distinguishing feature of Van Raaij and
Francken’s model is its emphasis on the importance of
family member influence on the decision-making process
for tourism service purchases. The decision process for
the purchase and consumption of a tourism service is
composed not only of individual factors but also
household-related factors. The interaction of individual
household and socio-demographic factors results in the
vacation sequence or the decision process. The major
premise is that in every sequence of the decision process
the behavior and role of different family members might
differ. A major contribution of this model is its
recognition of the interaction of household-related
variables (i.e., life-style, power structure, role, decisionmaking style) with individual-related factors (attitude,
aspirations and so on). Past research on family decision
behavior in tourism showed the dominance of joint
decisions versus husband or wife dominance in the
process (Filiatrault & Ritchie, 1980; Nichols & Snepen-
ger, 1988). Jenkins’s (1978) research suggested that the
role of family members differs with respect to the type of
decision activity. For example, husbands were found to
influence the timing of the vacation and monetary
decisions. Children were influential in the selection of
activities and duration of vacation. Referring to
early research on the same subject, Gitelson and
Kerstetter (1994) argued that friends and relatives were
constantly providing information to the decision-making process, and therefore may play an important part in
directly shaping behavior. Thornton, Shaw, and Williams (1997) assess the nature of group decision
behavior and the role of children on the travelers’
decision process. They conclude that children are
influential in directing decisions by their needs and
negotiating abilities. In an attempt to assess whether
gender has a role in the decision-making process,
Zalatan (1998) demonstrates that there were significant
differences between wives and husbands involving
different tasks, before and after the trip. For example,
before the trip, wives were more influential on nonfinancial decisions while husbands were more dominating on financial decisions.
The third model that drew much attention is the
model developed by Woodside and Lysonski (1989).
Based on an extensive review of several social science
disciplines, the authors proposed a model that presented
the decision process of a traveler as a categorization
process of destinations from which the preferences,
intentions, and the final choice result. Specifically,
before forming preferences, a traveler places all destinations familiar to him/her into the first of a series of
four mental sets. Marketing and personal variables
influence this process. Then, from these mental sets,
final preferences emerge through the possible influence
of affective associations (defined as positive or negative feelings associated with a destination). Finally,
the choice is a function of intention to visit a destination where situational variables act more as moderators
between intentions and the choice. In their study,
respondents successfully recalled destinations from
long-term memory and placed them into four mental
sets. Respondents’ consideration sets included a surprisingly small set of alternative destinations, usually
ranging from 3 to 5 destinations with an average of
4.2 destinations. Positive associations relate more
with destinations in the consideration set than those
in other sets. Moreover, respondents’ preference
for a destination was found to correlate with its rank
order of mentioned destinations. Research results also
suggest that past experience did not influence the
categorization of destinations into a consideration set.
The hypotheses of the study tested the influence of
marketing variables on destination categorization and
the influence of preference structure on intentions to
visit.
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The original Woodside and Lysonski’s model (1989)
and a recent extension (e.g., Woodside & MacDonald,
1994; Woodside & Dubelaar, 2003; Becken & Gnoth,
2004) are two of the more influential models in tourism
literature. A general systems framework of consumer
choice decisions by Woodside and MacDonald (1994;
also see Woodside & Dubelaar, 2003; Becken & Gnoth,
2004) emphasizes the interactions between members of a
travel party, activities and travel decisions. According to
Decrop (1999), the tourism psychology framework by
Woodside and MacDonald (1994) is in sharp contrast
with the rationality paradigm. One of the key assumptions of the model is ‘‘that the activation of initial travel
choices (due to ‘‘triggering events’’) spreads over time to
related travel choices (Decrop, 1999, p. 122).’’
Woodside and King (2001) present a general purchase
consumption system (PCS) framework, which they
describe as useful for mapping travelers’ choice decisions before and during a trip and evaluating their
actual experiences that may influence future trip choices.
PCS is a sequence of mental and observable steps a
consumer undertakes to buy and use several related
service offerings whereby some of the services purchased
lead to a purchase sequence involving further purchases.
Woodside and King assert that qualitative research
observation and analytical techniques are useful for
developing and validating complex and interactive
models such as the PCS. Their findings support the
view that travelers’ decision-making behaviors are based
on many variables in relationships that are interactive
rather than linear. The studies by Bansal and Eiselt
(2004) and Lue, Crompton, and Stewart (1996) support
this complementary, multidimensional view of travel
planning and behavior.
A final behavioral model included in this discussion is
the theory of planned behavior as applied to leisure
choice situations (Ajzen & Driver, 1992). Although not
every leisure activity is considered a tourism activity, the
application of the theory of planned behavior proves to
be useful for destination choice situations. The theory of
planned behavior is the extension of Fishbein and
Ajzen’s (1975; Ajzen & Fishbein, 1980) theory of
reasoned action that is widely considered the dominant
attitude-behavior model. With the addition of perceived
behavioral control in the theory of planned behavior,
Ajzen (1987) argues that the predictability of intentions
is significantly improved. This theory asserts that human
behavior is the function of intentions and perceived
behavioral control over behavior. Attitude toward the
behavior, subjective norm, and perceived behavioral
control interact with each other and influence intention
formation. These three constructs summarize many
essential elements contained in most tourism decision
models, namely the traveler attitudes, family and friend
influences (subjective norm) and the role of past
experience and constraints (perceived behavioral con-
823
trol). Ajzen and Driver applied this model to predict
leisure activity choices and were able to prove the
usefulness of this theory in understanding leisure choice
behavior by relating tourist intention to actual choice
behaviors.
In summary, aforementioned foundational models
contribute to the formation of a sound base for further
inquiries in decision-making. Travel-related decisions
involve high risks due to the very nature of tourism
services and thus require risk reduction strategies such
as extensive information search strategies. So far, the
assumptions throughout the models have been that
decision-makers exhibit rationalistic behavior in their
choices among alternative destinations. They will select
a destination, which offers the greatest utility subject to
individual or social constraints. The selection process is
a funnel-like one, in that travelers narrow down choices
among alternatives and are influenced both by sociopsychological factors and non-psychological. A synthesis of variables used in explaining choice decisions and
the formation of choice sets can be categorized into four
groups: (1) internal variables (i.e., attitudes, values,
lifestyles, images, motivation, beliefs and intentions,
personality characteristics of a buyer, lifecycle stage, risk
reduction methods, information search behavior); (2)
external variables (i.e., constraints, pull factors of a
destination, marketing mix, influences of family and
reference groups, culture and subcultures, social class,
household-related variables such as life-style, power
structure, role, group decision-making style); (3) the
nature of the intended trip (party size, distance, time,
duration of trip); and (4) trip experiences (mood and
feelings during the trip, post-purchase evaluations). The
ultimate choice of a destination will depend on the
nature of interaction among these variables.
5. Behavioral and choice-set approaches to decisionmaking in tourism
Extensive, complex and risky decisions, such as the
purchase of a tourism service, occur in stages. While
passing through these stages, the decision-maker is
influenced by both functional (or utilitarian) and
emotional elements (Mansfeld, 1992). For instance, the
exact cost of a tour package might be considered a
functional (or utilitarian) element, whereas promotional
messages, and family and friend influences, act as
emotional elements. Because of the intangible nature
of tourism experiences, probabilities will usually be
attached to alternatives under consideration (Mansfeld,
1992; Mathieson & Wall, 1982). Both ’’behavioral’’ and
‘‘choice-set’’ approaches have been adopted in explaining how this process occurs.
Behavioral approaches suggest that tourists are
motivated by a number of factors to collect information
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about different alternatives, which may meet their needs.
The individual assesses and eliminates these alternatives
to reach a final decision (Mansfeld, 1992). Behavioral
models, in general, assume utilitarian decision-makers
who can evaluate outside information to which they are
exposed, search for additional information to make
better decision, create alternatives in their minds and
make a final choice from those alternatives. The main
purpose of behavioral models is to identify the decision
stages decision-makers pass through and illustrate this
process by identifying the inside and outside factors
influencing this process. Choice-set models attempt to
illustrate the same process in a different way, while
implicitly accepting the main assumptions of the
behavioral models. The destination choice model
(Crompton, 1992) examines the decision process and
suggests that decisions are sequential in nature and are
comprised of sets. This model also promotes the use of
multiple decision strategies. Choice-set approaches
propose that a tourist first ‘‘develops an initial set of
destinations, widely known as an awareness set, then
eliminates some of those destinations to form a smaller
late consideration or evoked set and finally selects a
destination from the late consideration set’’ (Crompton,
1992, pp. 421–422). In other words, a potential traveler
generates a series of choice sets with an ever-decreasing
number of remaining alternatives in a funnel-like
process over time, until a final choice is determined.
Choice-set models possess practical advantages over
behavioral models by, for example, allowing destination
marketers to identify the market potential, while
segmenting the target market based on the choice sets
of target population. For example, a destination
marketer from a foreign country may want to know
what share of the potential tourists in the United States
considers it as a possible destination to visit or have
placed it in their evoked or reject set.
5.1. Choice sets approaches to tourism decision-making
Choice-set models have received substantial attention
in tourism decision-making literature because of their
practical use for destination marketers. The concept of
choice sets was first introduced by Howard (1963) in
consumer behavior literature. Howard and Sheth (1969),
Narayana and Markin (1975), Brisoux and Laroche
(1981), and Spiggle and Sewall (1987) elaborate the
concept. According to the theory, a potential traveler
first develops a set of destinations from his/her early
consideration or awareness set. The destinations are
chosen from a large number of destination alternatives,
comprising of all the destinations available, which is also
known as the ‘‘total set.’’ The number of alternatives is
then reduced to shape his/her late consideration or
evoked set. Finally, one resort is selected from the
evoked set as the final choice. One criticism that can be
levied against the choice set theory is that they may tend
to be deterministic in nature (Ben-Akiva & Bruno,
1995).
Howard (1963) introduces the concepts of awareness,
unawareness and evoked sets. He suggests that all
brands belong either to the consumer’s awareness set or
unawareness set. An awareness set is comprised of all
brands, or alternatives, that the buyer may be aware of
at any given time, while unawareness set encompasses all
the brands that the buyer is unaware. Howard defines
the evoked set as the collection of brands the buyer
actually considers in his purchase decision process.
Howard and Sheth (1969) further refine the evoked set
as the brands that the buyer considers acceptable for his
next purchase. Narayana and Markin (1975) redefine
the evoked set and included all brands that may be in the
buyer’s awareness set. Narayana and Markin introduce
the concepts of inert and inept sets. An inert set is made
up of the brands that the consumer has neither positive
nor negative evaluation. The inept set encompasses the
brands that the buyer has rejected from his purchase
consideration, either because he has had unpleasant
experience or because he has received negative feedback
from other sources. Spiggle and Sewall (1987) contribute
an important extension to the concept of choice sets.
They present a model for retail decision-making that
built upon and extended the evoked-set concept
previously investigated by Narayana and Markin
(1975). Spiggle and Sewall’s model includes five new
choice sets, which were hypothesized as being the
subsets of an evoked set. The new sets include the (1)
action set, (2) interaction set, (3) inaction set, (4) quiet
set, and (5) reject set. Action set was defined as ‘‘all
stores toward which a consumer takes some action—she
or he goes at least as far as making a visit to the store
site’’ (p. 99). The interaction set includes ‘‘all of the
stores in which a consumer allowed himself or herself to
be exposed to personal selling. The inaction set
comprises of all the stores in evoked set that a consumer
does not visit. Quiet set composes stores that consumers
visit and leave before interacting with a sales clerk. The
reject set is made up of the stores that are originally in
the evoked, action, or interaction sets and toward which
a consumer’s evaluation is transformed from positive to
negative during purchase deliberation’’ (p. 101).
The choice set approach in the destination choice
process was initiated as an alternative and more
practical perspective to behavioral approaches, which
were generally criticized as being too complex and
difficult to test empirically. Rather than being strong
theoretical exercises, choice-set research seeks to bring
to light more applicable results to destination choice
behaviors. The work of Woodside and Sherrel (1977)
was the first attempt to conceptualize choice sets for
leisure travel. Woodside and Sherrel define choice sets in
a tourism setting and confirm the categorization of
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destinations in potential travelers’ minds. Arguing their
particular usefulness in tourism, they introduce the
awareness-available and awareness-unavailable sets instead of a complete awareness set. The available set
included the destinations, which the traveler believes he
or she has the ability to visit during some period (i.e., a
year). Furthermore, they propose that determining the
available sets might be more reasonable because of the
large number of destinations in the awareness set. Their
study, at a South Carolina Welcome Center, indicated
that the average number of vacation destinations is 3.4
in evoked sets, 1.4 in inept sets and 0.9 in inert sets of the
subjects.
Um and Crompton (1990) propose a theoretical
framework for the destination choice process using
choice-set structure. This approach is simpler and more
theoretically and methodologically sound compared to
many other approaches in tourism decision research.
Um and Crompton’s framework asserts that destination
selection is a three-stage process including (1) composition of awareness set, (2) evoked set, and (3) final
destination selection, where the latter is a condensed
form of the former. The awareness set of destinations in
the potential traveler’s mind is formed through passive
information from the outside environment, whereas the
evoked set emerges with the active information searching from external sources including past experience,
media, family, friends and others. The active choice
process starts after an awareness set is developed with
the influence of internal inputs that comprise the sociopsychological set of the traveler (i.e. motives, values,
attitudes). At this point, situational constraints play an
important role before the traveler creates his/her evoked
set.
This framework is useful for assessing the role of
attitudes in the decision process—where attitudes are
operationalized as the difference between perceived
facilitators and inhibitors, measured with 17 instruments
on a total of 100 respondents. A difference between
facilitators and inhibitors was hypothesized to show a
positive attitude toward selected destination(s) in the
evoked set. The role of situational constraints was also
tested via their consideration as part of the inhibitors.
The research was conducted using a longitudinal
approach, which measured the magnitude of the
differences between perceived facilitators and inhibitors,
before and after the actual destination selection. Results
of the study suggest that the attitude toward a
destination is an important indicator of whether a
potential traveler will select a particular destination
from the awareness set or not. The study is unique in the
sense that it attempted to measure the effectiveness of
attitudes in an actual choice situation.
Crompton (1992) provides a further analysis of choice
sets along with an extensive literature review. Crompton
reorganizes the functions of choice sets, reconceptualizes
825
the awareness-available and -unavailable sets, and
adopts some newly proposed sets from the marketing
literature, such as action, inaction, and interaction
sets into tourism literature. Crompton and Ankomah
(1993) provide a series of propositions related to the
early consideration set, late consideration set (also
known as awareness and evoked sets) and final decision.
To widen the span of choice-set study in tourism, the
authors develop testable propositions based on conceptualizations from empirical studies in marketing
and management. Early consideration propositions
dealt with the size of set and the relationship between the level of awareness and probability of selection
of the destinations in the set. Late consideration set
propositions questioned the size and the factors that
affect the size of the late consideration set. Final
propositions focus on decision rules and other factors
that influence the selection of a particular destination
over others.
Ankomah, Crompton, and Baker (1996) analyze the
influence of cognitive distance on the allocation of
vacation destinations in different choice sets. They
define cognitive distance as an individual’s mental
representation of a physical distance from one point to
another, which is influenced and shaped by internal
(memory and beliefs) and external sources (society and
culture, destination-related factors). They test the effect
of cognitive distance on the assignment process as one of
the situational constraints. Their findings suggest that
individuals regard cognitive distance as an important
factor in a decision process. In addition, study
respondents’ distance estimates to destinations in the
late set were more accurate than those destinations in
the reject set. The distance to destinations in the action
set was more underestimated than the destinations in the
inaction set.
According to the evidence from the related literature
about behavioral and choice-set approaches, the following summary propositions provide guidance for further
advancing tourism theory:
Proposition 1: Consumers follow a funnel-like procedure to narrow down choices among alternatives.
Choices of destinations are affected by a number of
psychological or internal variables (i.e., attitudes,
images, motivation, beliefs and intentions, personality
characteristics of a buyer) and non-psychological or
external variables (i.e., time, pull factors, marketing
mix).
Proposition 2: Destination choice decisions are sequential in nature and comprise sets. Choice sets
decrease in numbers over time until the final choice is
made. Internal and external factors vary in degree of
influence during this reduction stage.
Rather than several empirical data analyses, the
greatest support for P1 and P2 is based on published
theoretical models and frameworks. The meta-theoretical
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view represented by P1 and P2 needs empirical confirmation via meta-analytical reports.
5.2. Characteristics of tourism service offerings and their
neglected role in decision-making
In the 1980s, four key characteristics distinguish the
production, consumption, and evaluation of services
from manufactured goods: intangibility, inseparability,
heterogeneity, and perishability (Zeithaml, Parasuraman, & Berry, 1990). First, services are mostly
intangible in that they are not physical, objects, rather
they are performances or experiences. The implications
of this view are that the values offered cannot be
communicated easily by the tourism service provider,
evaluating a service in terms of its potential to fulfill
identified needs is difficult for potential travelers.
However, according to Crozier and McLean (1997),
services may not have to be entirely intangible. Very few
pure services exist; most of them can be positioned on an
intangible dominant (e.g., travel agency services) or
tangible dominant continuum (e.g., restaurant meal) to
reflect the extent to which the service element is essential
to the product. Second, services are heterogeneous; they
differ substantially across providers because of human
inconsistencies involved in providing the service. This
characteristic of service makes it challenging for
providers to deliver consistent quality of service. Third,
services are inseparable, which means that the purchase
and consumption of services occur at the same time.
Managing the traveler mix and quality control can pose
challenges for the management. Fourth, perishability of
services means that services cannot be stored and
consumed at a later point in time, so selling the service
as soon as it is produced becomes a priority; otherwise
revenue is lost (Zeithaml, Parasuraman, & Berry, 1985).
Tourism services have unique features that often
differentiate them from non-tourism services. For
example, tourists purchase and consume a service at a
different location from where they live (Sirakaya,
McLellan, & Uysal, 1996). Consumption of a tourism
service, for example, a vacation in the mountains, takes
a longer time than the consumption of many other
service offerings; tourists often receive no tangible
return on their investment except souvenirs and the
purchase frequently is not spontaneous but requires
preplanning. Moreover, Wahab et al. (1976) note that
the perceived risk often is high in tourism purchase
decisions, which suggests that tourists will be relatively
highly involved in information search in order to reduce
uncertainty involved in the purchase. The ultimate
choice of a final destination depends more or less on
the quality and quantity of information available to and
used by the tourist (Fodness & Murray, 1997, 1998;
Gitelson & Perdue, 1987; Raitz & Dakhil, 1989;
Snepenger, Meged, Snelling, & Worral, 1990; Snepenger
& Snepenger, 1993; Van Raaij, 1986; Etzel & Wahlers,
1985; Perdue, 1985). Consumer information search
strategies can be grouped into three sets (Fodness &
Murray, 1998): where, when, and how the search takes
place. In decisions related to tangible-dominant services,
information search may include pre-purchase trial or
observation of others, but intangible-dominantservices
such as tourism require different risk-reduction strategies (Guseman, 1981; Crozier & McLean, 1997). These
search behaviors include reliance on testimonials,
endorsements and personal recommendations (Murray,
1991).
Evidence from the service marketing literature indicates that these characteristics of tourism service
offerings also necessitate a different, at least an
emphasis, shift of decision-making process. For example, information search seems to be more important and
different and some stages might be omitted if there is not
much information available on the alternatives. While
the traditional six-stage decision-making process (recognition, formulation, alternative generation, information search, judgment or choice, action, and feedback) is
common to many consumer decision-making models,
more recent knowledge about how decisions for
purchases of services differ from manufactured goods
challenges this traditional approach. View many of the
traditional models and their derivatives with some
skepticism since none of them are confirmed empirically
(Crozier & McLean, 1997). Moreover, the traditional
models of consumer behavior as adapted to tourism
have not accommodated differences between the purchase of products and services (Cowell, 1991).
Barnes (1986) suggests that a four-step decision
process was applicable in the context of services: (1)
problem recognition, (2) limited personal source search,
(3) purchase/consumption, and (4) evaluation of service.
Subsequently, Gabbott and Hogg (1994) conceptualized
the consumer decision-making process in the context of
real-estate services as having three broad steps: information search, comparison of alternatives, and postpurchase evaluation. Both of these models recognize
that consumers engage in limited personal source search
and put more emphasis on post-purchase evaluation,
since they often ‘‘lack information on price, amount of
time needed to secure the service, or even the environment in which the service is delivered is like’’ (Barnes,
1986, p. 42). Because of the unique characteristics of
services (e.g., lack of standardization and difficulty in
quality control), the perceived financial and emotional
risks associate highly with many service decisions. In
these high-risk situations, word-of-mouth or personal
information sources are more influential than impersonal media sources in decisions. Unlike product-based
decisions where many alternatives may be generated for
possible purchase, according to Barnes (1986) and
Crozier and McLean (1997), the known alternatives
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for service offerings are fewer. Indeed, in a tourism
context, Woodside and Lysonski (1989) identify this set
to be a small set of alternative destinations, usually
ranging from 3 to 5 destinations with an average of 4.2
destinations. However, Crompton (1992) argues that a
relative small set of alternative is typical of findings in
products also. Many times, consumers are unaware of
service alternatives; therefore they may skip alternative
evaluation stage and put more emphasis on post
evaluation (Crozier & McLean, 1997). Since many
tourism destination-choice models have been derived
from traditional consumer behavior models (grand
models), they failed to incorporate all these unique
circumstances of services (e.g., intangible dominant
products, differences in steps in decision-making) in
modeling travelers’ decisions. Accordingly, a call for
unique approaches for modeling tourist decisions is long
overdue. Accordingly, the preceding discussion results in
Propositions 3–5.
Proposition 3: Tourists’ decision-making reflects the
unique characteristics of services, that is, intangibles,
inseparability, heterogeneity, and perishability. When
making decisions, tourists’ engage in limited search of
personal sources to create a set of alternative destinations. (3a) In order to reduce the perceived risk, tourists
engage in extensive information search regarding their
initial set of alternatives. (3b) In this search, they give
most credence to personal rather than to nonpersonal
sources of information.
Proposition 4: Prior experience reduces the extensity
and intensity of the information search.
Proposition 5: Level of involvement influences the
decision rules used to arrive at the ultimate choice
decision.
The consumer and tourism research literatures support the view that a strong negative relationship occurs
between prior experience and the extent of information
search (see Moutinho, 1987; Urbany et al., 1989;
Perdue, 1985). However, additional theoretical work
and empirical reports are needed to help understand
heavy search behavior by visitors with extensive prior
travel behavior experiences to the destination areas that
they are about to visit, as well as non-search behavior
exhibited by some leisure first-time visitors to a given
destination area. The exceptions to the significant
negative main effect between experience and search are
too numerous to ignore theoretically and practically.
Involvement level may be approached from enduring
and situational perspectives (see Hoyer & MacInnis,
2004). Enduring involvement exists when the traveler
shows interest in leisure travel as an avocation over a
long period of time. Situational involvement reflects
temporary commitment with an activity; both travelers
with high and low levels of involvement are likely to
experience situational involvement while actively engaged in planning an imminent trip. Both enduring and
827
situational involvement levels are likely to influence the
decision rules—the heuristics—applied by leisure travels. For example, travelers with high enduring travel
involvement are likely to be cognizant of alternative
opportunities and expenditure-saving options compared
to travelers with low enduring travel involvement, since
the former are likely to be cognitively vigilant to
information related to these issues versus the later.
Additional theoretical and empirical work is necessary
to probe the possibilities for developing the involvement-related propositions in tourism research.
6. What lies ahead? Discussion and implications for
future research
A new sub-field of marketing emerged during the
1980s, pointing out the fundamental differences between
marketing of products and services. A substantial
number of articles refer to four key characteristics that
distinguish the production, consumption, and evaluation of services from manufactured goods—intangibility, inseparability, heterogeneity, and perishability
(Zeithaml et al., 1990). In addition to these generic
differences, tourism posits characteristics that make it
even more unique in the service–product continuum. A
tourist is expected to be highly involved in the
information search for tourism service purchases, than
many other product or service purchases, because of
high-perceived risk factor. The consumer often seeks
ways to reduce uncertainty involved in the purchase of a
vacation in an environment where such information is
scarce. As opposed to tangible-dominant products
where information search may include pre-purchase
trial or observation of others, intangible-dominant
products require different risk-reduction strategies
(Guseman, 1981; Crozier & McLean, 1997). Destination
revisitation (repurchase) may come to mind; however,
this is less relevant to tourists where purchase is usually
infrequent. Another strategy that comes to mind is
reliance on testimonials, endorsements and personal
recommendation (Murray, 1991). Therefore, a different
perspective on the travel decision-making process was
needed because of the inability of the grand models to
reflect on the differences between services and tangible
products.
Although various tourism scholars address this need
(e.g., see Um & Crompton, 1990; Woodside & Lysonski,
1989; Woodside & MacDonald, 1994), a significant
portion of the developed models still do not move
beyond borrowing the main concepts from the grand
models, which were fundamentally developed for
manufactured products, not service intensive industries
like tourism. Thus, most of the models developed in
tourism should be viewed with a critical eye. The current
state of decision-making research in tourism lacks a
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consistent perspective that reflects the unique characteristics of tourism services.
The aim of the process-oriented research is to clarify
the process that travelers go through to reach a final
decision to purchase a tourism service, such as a vacation
package. The consumer behavior literature generally
concludes that consumer decision-making process for
nonroutinized purchases, like the purchases of tourism
services, is comprised of five stages: (1) problem
recognition, (2) information search, (3) evaluation, (4)
purchase and (5) post-purchase evaluation (Engel et al.,
1986). However, view the ubiquitous use of the traditional consumer decision processes and their derivatives
with a degree of questioning, since ‘‘none of the existing
decision models have been validated by empirical data for
service offering (Crozier & McLean, 1997).
Nonetheless, in analyzing and presenting the nature of
this process, tourism researchers apply complementary
perspectives for modeling: a broad, behavioral, perspective and a narrower, choice-set perspective. Researchers
focusing on the broader behavioral perspective attempt
to illustrate the decision process of travelers with
contingent psychological variables before focusing on
categorization of destinations in travelers’ minds,
whereas those who adapt the choice-set perspective
focus from the start on the nature and size of choice sets
in each step within the decision process.
Studies in the 1990s show that tourism researchers
aptly conceive a choice-sets approach to travelers’
decision process studies (Crompton, 1992; Crompton &
Ankomah, 1993; Ankomah et al., 1996). From a broader
behavioral perspective, Gilbert (1991, p. 101) argues, ‘‘...
much of the written material explaining different aspects
of the decision-making process of travelers is general in
nature or unsubstantiated empirically.’’ Considering most
if not all of these attempts are behavioral approaches,
these models are too complex and generalized for
empirical analysis (Bagozzi, 1984; Jacoby, 1978). The
choice-sets approach offers a rather simple and practical
perspective to understanding the travelers’ decision
process. These advantages stimulate the increased application of this approach in this field.
The choice-sets approach provides practical advantages (Crompton, 1992). For example, the choice-sets
structure, with a survey approach, allow destination
marketers to ‘‘identify the percentage of a target market
in each choice set and assess their success in transforming people in each set into visitors to their destination’’
(p. 431). Since most of the choice sets are associated with
positive, negative, or neutral feelings, marketers may
make an overall assessment as to how their target
market perceives their destination. However, choice-set
models consider the decision-making process as monolithic because they almost become immune once the
initial sets have been processed. Time and situational
factors such as availability of ‘‘last-minute’’ information
(e.g., the safety or security of the destination, or a newly
promoted destination) have been marginalized. When
tested in real-world situations, choice-set models may
act more like probabilistic models rather than deterministic models. Accordingly, the following proposition
helps guide research efforts in this area.
Proposition 6: (a) Initial ‘‘first-blush’’ consideration
sets are highly limited in size (i.e., no8; e.g., see
Woodside & Sherrel, 1977); (b) revisions occur to such
consideration sets in a dynamic process as consumers
move mentally toward making commitment and rejection decisions; (c) consumers are able to easily report
intention probabilities to visit alternatives in consideration sets and these probabilities are revised dynamically.
Moreover, the literature on behavioral decisionmaking suggests that decision-making styles are individualistic (Sirakaya et al., 1996). Therefore, developing a
model that fits all decision-makers and every decision
situation may not be realistic. Priori segmentation of
travel markets according to trip purpose (such as
pleasure vacation versus family and friends, leisure
travel versus business) is an approach useful for future
models. Different segments might have dissimilar
methods of approaching problem solving and the
decision-making. For example, a potential traveler
who is interested in traveling to a location where she/
he has friends or relatives might follow different
decision-making rules (i.e., low-involvement, less-risky
conditions) than a person who is taking a pleasure
vacation trip for the first time to a new location (highinvolvement, high perceived risk).
A posterior, sentiment-based, segmentation proposal
by Chen (2003) is a useful alternative, as well as
complementary method to priori segmentation. Chen
employs chi-square automatic interaction algorithm
(CHAD) in a decision tree framework to create mutually
exclusive segments of persons known to have visited a
destination. CHAD’s main objective to tourism psychological research is to maximize differences in sentiments
and behaviors between segments using the minimum
number of splits possible among respondents. In Chen’s
study, the CHAD analysis created four segments useful
for future research for advancing theory and tourism
strategic management:
Pundit tourists: mostly freely independent travelers;
likely to recommend their destination to others; most
will use Internet for future trip planning (23% of
n ¼ 261).
Individualistic tourists: similar to pundits, except most
will not use the Internet (36%).
Negative/neutral recommenders: all report being unwilling to offer a positive recommendation to visit the
destination (23%).
Recommend the visit but are dissatisfied visitors
(18%).
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Such results focus attention on the potentially critical
importance of psychological outcomes and actions
related to the primary destination visited, as well as
the distinguishing power of using a relatively new
information technology. Such findings provide credence
to backward segmentation theory in tourism research
(i.e., creating segments starting with travel outcomes
rather than starting with demographic characteristics)
and segmenting based on use/nonuse of information
sources. Wickens (2002) also demonstrates the backward segmentation approach for developing tourism
theory by segmenting 86 British holidaymakers who
visited Chalkidiki, Greece, by their summary views
about their destination experiences.
The socialization process of individuals is a variable
receiving little attention in theory-building in tourism
(for an exception, see Wickens, 2002). There is a strong
indication that children’s leisure socialization plays an
important role in what type of activities they participate,
in addition to how and where they travel when they
become adults (Woodside, MacDonald, & Burford,
2004). Recent consumer behavior literature suggests that
emotions and feelings play an important role in
processing information. Models that are not dynamic
have neglected the importance of these variables.
With the exception of Wahab and Pigram (1997) and
Wansink and van Ittersum (2004), the role of the travel
party has been marginalized in most tourism behavior
models. An individual may not care where they travel as
long as they are with friends, thus they may give up
decision control to a friend. This individual would then
analyze alternatives and make the travel decisions. Even
though the decisions may be made in a social setting
with a group of individuals, each playing a specific role,
most research focuses on the psychological variables,
not social variables. Family and significant individuals
are two important mediators of decisions. The decisionmaking style of groups (family) is an important area for
future research as group interactions and family roles
may influence what product/destination will be chosen.
The treatment of an individual decision maker, as if
they were in a vacuum, is common to all decisionmaking models. These models accept that other
individuals affect the decision-maker but do not address
active interaction with other individuals or sources
along the decision-making process. Tourism mostly
occurs in social situations. It is a social activity that
involves family, relatives, friends and others (if in a
group travel); thus, a different approach is needed. The
existing models lack the integration of these issues into a
single unique model that is theoretically sound, complex, and still useful for practical purposes.
We conclude with several recommendations for future
research. First, future research on tourism decisionmaking adopting multiple approaches is bound to create
desk-top models that have both theoretical and practical
829
value for tourism suppliers. Simplified and field-specific
models should be created and empirically tested to fill
the gap in this area. Statistical methods that allow model
testing (i.e. structural equation modeling, path analysis)
should be utilized to test the nature of a complete model.
Secondly, different purchase and use situations should
be considered, in order to gain a better understanding
about the nature of the decision process of travelers. For
example, there can be tourism purchases where very
little functional decision-making is involved. In addition, the role of emotions should also be considered. In
essence, pleasure travelers are buying and consuming
experiences where emotions play an important role
from beginning to end. Thirdly, decision-making models
that consider the individual as the decision-making
entity remain limited because many tourism service
purchases heavily involve joint decision-making processes (Teare, 1992). Family, group, and external
sources impact an individual’s evaluation (weighing) of
alternative attributes. Models that account for the role
of joint decisions are more generalizable than individual-based models.
Tourism researchers treat availability of an alternative
destination as an observable variable. However, it is
difficult to fully observe the set of alternative destinations an individual considers before making a final
choice. Because decision-making is a dynamic process,
research focusing on understanding and describing the
dynamic nature of the decision itself is needed (Aukers,
1999). Process-tracing methodologies could provide a
valuable tool in exploring the process between decision
inputs and decision outputs. The Exhibit summarizes a
more detailed account of research issues useful for
examining for a new framework in tourism decisionmaking.
Exhibit
Research issues for advancing understanding of tourism
decision-making
The influence of tourism service characteristics on
decision-making
Do the decision-making stages change according to the
nature of tourism product? How does decision-making
process change for tourism services?
Risk reduction strategies and their influence on decisionmaking policies
Do consumers of tourism services/products or
destinations rely more on personal than nonpersonal
sources? If yes, at what stage they become more
important?
How do consumers reduce perceived risk involved in
tourism decisions?
How do consumers use nonpersonal sources of
information in their decision processes?
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The efficacy of choice sets in travelers’ choice process
What cues do consumers use as major criteria for
selecting among the few alternatives from their evoked
sets? What is the role of pricing as a cue for evaluating
tourism services?
What are the efficacies of developing ‘probabilistic’
choice sets rather than deterministic models?
Decision rules and their effect on choice behavior
What decision styles are used under what circumstance?
How do decision styles vary across tourism products
and destination types?
Under what circumstances do consumers act rationally,
maximizing benefits while minimizing costs?
Under what circumstances do consumers use shortcuts
in their decision-making styles? What are their
implications for marketing?
What decision models are used under what
circumstances? What is the efficacy of the choice-set
models versus behavioral models of decision-making?
Underlying variables affecting choice behavior
What role do household-related variables (i.e., life-style,
power structure, family roles, decision-making style)
play in decision-making? How are decisions are made
within a group. And, what decision styles are used when
making group decisions rather than an individual
decision. What are the ramifications of the same for
consumer behavior theory of tourist decisions?
How are choice-set models impacted by situational
factors such as availability of ‘‘last-minute’’ information
(e.g., the safety or security of the destination, or a newly
promoted destination)? How and under what
circumstances does the final choice change and what are
the ramifications of this from a modeling perspective?
What is the nature of relationship between children’s
leisure socialization and their decision-making policies
later when they become adults?
Decision-making is complex and recognized only
recently as often being an unconscious process (for a
review on this point, see Zaltman, 2003); thus DM is a
process not fully developed theoretically. Decisionmaking researchers face the difficult task of measuring
and understanding a process that is unobservable and
for which consumers are only partially aware. The goal
of decision research is to understand how decisions are
made consciously as well as unconsciously (Carroll &
Johnson, 1990). Carroll and Johnson argue, ‘‘If decision
making were easy to understand (or easy to do), there
would be no need for such elaborate research efforts’’
(p. 19). From our perspective, travel marketers and
destination developers must understand the tourist
decision process, in order to develop effective marketing
strategies because decision behavior (buyer behavior) is
the structure upon which marketing must hang. There-
fore, development of tourist decision models that
incorporate a wide array of real world influences and
bridge the gap between behavioral and choice-set
approaches using the probability theory will remain
critical in tourism consumer behavior research.
Acknowledgements
We are grateful to Steven Aukers, John L. Crompton,
and Teoman Duman for helpful comments on earlier
versions of this article. The authors acknowledge the
insightful comments by anonymous Tourism Management reviewers to earlier drafts of the article.
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