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1999 37: 220Journal of Travel ResearchDale Fodness and Brian Murray

A Model of Tourist Information Search Behavior  

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FEBRUARY 1999JOURNAL OF TRAVEL RESEARCH

A Model of TouristInformation Search Behavior

DALE FODNESS ANDBRIAN MURRAY

This research empirically examines, for the first time, thecorrelates of tourist information search behavior. A model isspecified and tested in which tourist information searchstrategies are related to search contingencies, individual(tourist) characteristics, and behavioral search outcomes.Using survey data from a large sample of leisure travelers,tests of association showed substantial support for hypothe-sized relationships. Tourist information search strategieswere found to be the result of a dynamic process in whichtravelers used various types and amounts of informationsources to respond to internal and external contingencies invacation planning. A discussion of the key findings of themodel provides a rich source of managerial implications.

The purpose of this article is to expand the concept oftourist information search by taking an explicit account of se-lected relevant correlates of tourists’ choices of informationsources. Proceeding under the general assumption that thecombination of information sources used by tourists repre-sents information search strategies (Snepenger et al. 1990;Fodness and Murray 1998), the article is organized as fol-lows. First, building on a review of previous research in con-sumer behavior and tourism, we develop a model composedof tourist information search strategies, search contingen-cies, tourist characteristics, and search outcomes. Relation-ships suggested by the model are cast as testable hypotheses.Second, we describe the sample, survey instrument, and data.Third, quantitative techniques used to analyze the data andtest the hypotheses are described, and results of the analysesare reported. Finally, we present a general discussion of theresults, explore managerial implications of the study find-ings, and outline directions for future research.

A MODEL OF THE TOURIST INFORMATIONSEARCH STRATEGY PROCESS

We propose a model of tourist information search strat-egy within the tradition of previous consumer research.Beatty and Smith (1987), Moore and Lehmann (1980), Bett-man (1979), Newman (1977), and others have proposed sys-tematic relationships among consumer search, the marketenvironment, situational variables, potential payoff, knowl-edge and experience, individual differences, conflict andconflict resolution, and cost of search. Likewise, Maute andForrester (1991), Selnes and Troye (1989), Urbany (1986),Brucks (1985), Kiel and Layton (1981), and Furse, Punj, and

Stewart (1984) have empirically explored linkages betweensearch activity and consumer characteristics. Srinivasan andRatchford (1991) and Punj and Staelin (1983) also haveattempted to construct and test comprehensive models ofsearch behavior. No similar models exist in the tourismliterature.

Our proposed framework (Figure 1) addresses thisresearch gap by incorporating three forces driving individualtourists to develop unique information search strategies: con-tingencies, tourist characteristics, and outcomes of search.The model also incorporates prior research on the dimen-sionality of information search strategies (Fodness andMurray 1998). In the sections that follow, we offer a series ofhypotheses suggested by our model and test them with uni-variate statistics. Readers will note, however, that the modelin Figure 1 implies interrelationships that cannot be testedwith univariate statistics. For example, we postulate thatinformation search strategy will vary as a function of the pur-pose of trip (H3), and we empirically verify this. However,following the flow of the arrows in the model, it implies thatpurpose of trip also will influence Search Outcomes (H7→H10) and Tourist Characteristics (H5, H6). Clearly, thesemore complex relationships are beyond the scope of univari-ate analyses and this study. We recommend that the discreterelationships that we postulate and empirically validate inthis study provide the basis for a future investigation of thedynamics among the model’s four main elements. Detaileddescriptions of the model’s constructs, their first-order rela-tionships, and associated univariate hypotheses follow.

Before proceeding, readers are reminded of the limita-tions of any modeling effort and are cautioned not to viewFigure 1 more literally than is warranted. For example, it isimpossible for a discrete effect (Search Outcomes) to pre-cede its cause (Information Search Strategies). Yet, themodel clearly identifies an indirect effect of outcomes onprocesses. This relationship is basic learning theory: overtime, the results of past cause-effect relationships influencefuture cause-effect relationships. Again, analyses of thesehigher order relationships are not included in this study,which limits itself to first-order relationships.

Dale Fodness is manager of market research at Dallas/FortWorth International Airport. Brian Murray is an assistant professorof management at the University of Texas at San Antonio.

Journal of Travel Research, Vol. 37, February 1999, 220-230© 1999 Sage Publications, Inc.

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Information Search Strategies

The literature suggests that, in any given purchase situa-tion, there are at least three distinct strategies for informationsearch: spatial, temporal, and operational (for a comprehen-sive review, see Fodness and Murray 1998). The spatialdimension of information search strategy reflects the locus ofsearch activity: internal (accessing the contents of memory)or external (acquiring information from the environment).The temporal dimension represents the timing of searchactivity. Search can be either ongoing, building up a knowl-edge base for unspecified future purchase decisions, or pre-purchase, in response to a current purchase problem. Thethird dimension is operational, reflecting the conduct ofsearch and focusing on the particular sources used and theirrelative effectiveness for problem solving and decisionmaking.

Support for a tripartite theory of tourist informationsearch strategies was found in an associated study in whichthe researchers used multidimensional scaling (MDS) andcluster analysis to explore underlying dimensions of leisuretravelers’ perceptions of information sources and to confirmthe categories of tourist information search strategies pre-dicted by the literature, respectively (Fodness and Murray1998). In that study, 585 automobile travelers were askedwhich information sources they used to plan their pleasuretrips to Florida from a list of 11 sources identified from the

tourism literature: auto clubs, brochures from services suchas hotels and attractions, commercial guidebooks, friends orrelatives, highway welcome centers, local tourist offices,magazines, newspapers, official state travel guides, personalexperience, and travel agencies. Fully 68% of the respon-dents reported using more than one of these informationsources, as indicated in Table 1.

The results of MDS applied to the preceding data pro-vided empirical evidence that spatial, temporal, and opera-tional dimensions underlie leisure travelers’ perceptions ofinformation sources used for trip planning. The first of threeMDS dimensions derived clearly was spatial. It separated aninternal strategy (use of personal experience) from an exter-nal strategy composed of one or more of the remainingsources. The temporal dimension distinguished an ongoingstrategy comprised of magazines and/or newspapers from aprepurchase strategy that might include one or more of theother sources. The operational dimension manifested itself interms of differentiating information sources that tended to beused in combination with other sources from those that wereused as the sole source for trip planning. Commercial guide-books, state travel guides, and brochures all tended to be usedin conjunction with three or more other sources. Personalexperience, travel agencies, and friends or relatives were thethree sources most likely to be used alone. The former groupof sources clearly served to complement other sources or, inother words, to contribute to trip planning. The latter sources

JOURNAL OF TRAVEL RESEARCH 221

FIGURE 1MODEL OF THE TOURIST INFORMATION SEARCH STRATEGY PROCESS

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appeared to be decisive in that they were used as sole sourcesof information on where to go, what to do, where to eat,where to stay, and so on.

The results of cluster analysis applied to the data con-verged with those of the MDS to provide empirical supportfor the idea that leisure travelers could be classified into ho-mogeneous groups on the basis of their information searchstrategies, which were defined by the unique combination ofsources used to plan their trips. As Table 2 indicates, thethree information search strategies are not mutually exclu-sive. Seven unique information strategies were identified.Four of the clusters (3, 5, 6, and 7) suggested a strategy con-sisting of the use of a single, decisive source (personal expe-rience, friends or relatives, auto clubs, and travel agencies,respectively, along with contributory sources). The threeother clusters documented strategies based on a combinationof related contributory sources (brochures and guidebooks;highway welcome centers, local tourist offices, and statetravel guides; and magazines and newspapers), sometimesalong with the use of a single, decisive source (auto clubs).

Information SearchStrategies and Contingencies

To paraphrase Ajzen and Fishbein (1980), tourists con-sider the implications of their choices before they decide toengage in a given information search strategy or, alterna-tively, before they choose to use any given informationsource. Thus, it becomes critical to understand the factorsunderlying search strategy choice. Whereas the quantity andavailability, as well as the perceived costs and benefits, ofinformation in the marketplace will determine choices tosome extent, Figure 1 suggests some general contingenciesaffecting choice of spatial, temporal, and operational searchstrategies that can be drawn from the literature. Reflecting anintention to be illustrative rather than all-inclusive, we dis-cuss two such factors: situational influences and productcharacteristics.

Behavior always occurs within the context of some situa-tion. In the study of consumer behavior, Belk (1974) definedsituational influences as those arising from factors that are

particular to a specific time and place and that are relativelyindependent of consumer and product characteristics. Exam-ples include physical surroundings, social settings, time, task(type of decision to be made), and antecedent states such asmoods and physical conditions (Belk 1975). Turning to theliterature of information search, there is some conjec-ture—but little hard evidence—of the influence of situationalvariables on information search. Two exceptions are the typeof purchase decision making required and composition of thetraveling party.

Nature of decision making. The leisure traveler, like con-sumers of other products, can approach a product decisionthrough routine, limited, or extended problem-solving be-havior (Moutinho 1987). In the case of routine problem solv-ing, travel decisions are made quickly and with little apparenteffort. Weekend visits to a nearby park or recreation area orperiodic visits to friends or relatives constitute routine leisuretravel decisions for many. Previsit (prepurchase) informationsearch probably is unnecessary if past experiences providean adequate basis for decision making. Limited decisionmaking, however, requires somewhat more time and effort.In leisure travel planning, limited decision making may oc-cur when the traveler plans variations to regular travel behav-ior such as taking a new route or engaging in a new activity ata familiar destination. Limited prepurchase search of both in-ternal (past experience) and external sources (brochures fromhotels and attractions) might be expected, but the traveler’sown past experience probably is largely decisive. When ex-tensive problem solving is needed, such as when planning afirst-time cruise, European vacation, African safari, orround-the-world trip, there is considerable time and effortdevoted to information search. Such a search would, by na-ture, be prepurchase, emphasizing primarily external sourcesbecause the trip would be unfamiliar. It also might be ex-pected that the leisure traveler undertaking extensive prob-lem solving might rely heavily on at least one decisivesource, such as travel agents or knowledgeable friends orrelatives, as well as on a wide variety of contributory sources,such as commercial guidebooks, brochures, and travel maga-zines, to reduce the perceived risks of an unfamiliar trip.

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TABLE 1

INFORMATION SOURCES USED BY TRAVELERS SURVEYED

Users of Each Information Source Who . . .

Used That Used ThatUsed Only Source and Source and Average

Total Sample That Source One Other ≥ Two Others Number of(n = 585) (n = 163) (n = 167) (n = 242) Sources Used

Information Source # % Rank # % Rank # % Rank # % Rank Mean Median

Automobile clubs 200 34.2 3 27 16.6 3 64 38.3 3 108 44.6 3 3.09 3Brochures from hotels,

attractions, and the like 128 21.9 4 8 4.9 5 27 16.2 4 92 38.0 4 3.73 4Commercial guidebooks 70 12.0 8 5 3.1 7 6 3.6 10 58 24.0 7 4.24 4Friends or relatives 281 48.1 1 42 25.8 2 82 49.1 1 156 64.5 2 3.10 3Highway welcome centers 263 45.0 2 8 4.9 5 80 47.9 2 174 71.9 1 3.47 3Local tourist offices 58 10.0 9 3 1.8 11 5 3.0 11 50 20.7 8 4.26 4Magazines 86 14.7 6 5 3.1 7 15 9.0 6 65 26.9 6 4.14 4Newspapers 54 9.2 10 4 2.4 10 7 4.2 9 42 17.4 9 4.35 4Official state travel guides 85 14.6 7 5 3.1 7 11 6.6 8 68 28.1 5 4.26 4Personal experience 102 17.5 5 58 35.6 1 21 12.6 5 23 9.5 11 1.89 1Travel agency 48 8.2 11 10 6.1 4 13 7.8 7 25 10.3 10 3.0 3

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Thus, this study hypothesized that significant differences ininformation search will be based on the nature of the decisionmaking facing the leisure traveler.

Hypothesis 1 (H1): Choice of information search strategywill vary as a function of the type of decision makingrequired: routine, limited, or extended problem solv-ing. (a) For routine problem solving, strategies willtend to emphasize ongoing rather than prepurchase

sources, internal rather than external sources, and de-cisive rather than contributory sources.(b)For limitedproblem solving, strategies will reflect a greater useof prepurchase than ongoing sources and both internaldecisive and external contributory sources.(c) Incases of extended problem solving, strategies will beprepurchase and characterized by a number of con-tributory sources used to supplement external, deci-sive sources.

Traveling party composition. The social setting (presenceor absence of others) that characterizes the consumption of aproduct also influences information search, as it does otherconsumer behavior (Stayman and Deshpande 1989). The be-havior of leisure travelers is heavily influenced by the com-position of the traveling party (McIntosh and Goeldner1990). Leisure travel is a product that often is jointly con-sumed, and leisure travel activities reflect the influence (bothdirect and indirect) of all those traveling together (Chadwick1987). In general, traveling parties can be composed of sin-gle individuals, persons from different households travelingtogether, and persons from the same household traveling to-gether. This latter category frequently is subdivided intofamilies traveling with children and couples traveling with-out children. The travel-related behaviors of the two groupsdiffer significantly. Traveling with children, for example, en-tails greater planning efforts to coordinate schedules andmeet differential needs. A further breakdown of the couplescategory frequently is made in tourism research to differenti-ate between younger, middle-aged, and retired couples. Re-tirees often are active, experienced travelers without sched-ule conflicts who tend to engage in less information searchthan do younger or middle-aged couples. Based on the forgo-ing, we hypothesized the following:

Hypothesis 2 (H2): Choice of information search strategywill vary as a function of the traveling party composi-tion: families traveling with children, younger cou-ples traveling without children, and retired couplestraveling without children.(a) For families travelingwith children, search strategies will tend to emphasizeprepurchase rather than ongoing sources, externalrather than internal sources, and a combination ofboth decisive and numerous contributory sources.(b) For younger couples without children in the trav-eling parties, strategies will reflect a greater use ofprepurchase rather than ongoing sources and decisiverather than contributory sources.(c) For retired cou-ples, strategies will be characterized by ongoing, in-ternal, decisive sources.

Information Search Strategiesand Product Characteristics

Features of the product clearly affect information search.For example, consumer search differs between goods andservices. Because consumers have greater difficulty in evalu-ating service quality before purchase and, therefore, mightperceive greater risk in buying intangible-dominant productssuch as touristic experiences, they adopt different search pat-terns (or strategies) to reduce perceived risk (Engel, Black-well, and Miniard 1995). A recent empirical study found thatconsumers relied more heavily on personal sources of infor-mation for decisions involving services (Murray 1991).

JOURNAL OF TRAVEL RESEARCH 223

TABLE 2

CHARACTERISTICS OF THE SEVEN INFORMATIONSEARCH CLUSTERS

Cluster SearchNumber Strategy Description

1 Prepurchase Prepurchase, external strategymix (11%) Heavy use of a wide variety of

contributory sources; minimal useof decisive sourcesUsed an average of 3.6 sources

2 Tourist Prepurchase, external strategybureau (8%) Most frequent users of state travel

guides and local tourist offices ascontributory sources; limited useof auto clubs as decisive sourcesUsed an average of 4.1 sources

3 Personal Ongoing (personal experience),experience internal strategy

(14%) Almost completely reliant onpersonal experienceLowest average source usage:1.3 sources

4 Ongoing Ongoing (magazines and(4%) newspapers), external strategy

Heaviest use of magazines andnewspapers as contributorysources; limited use of auto clubsand travel agencies as decisivesourcesHighest average source usage:5.6 sources

5 On-site Ongoing or prepurchase, external(27%) strategy

Greatest reliance on friends orrelatives as decisive sourcesUsed an average of 2.4 sources

6 Automobile Prepurchase, external strategyclub (24%) Highest use of auto clubs as

decisive sources; also heavy useof friends or relativesModerate use of contributorysources including brochures,guidebooks, newspapers, andstate travel guidesUsed an average of 2.4 sources

7 Travel Prepurchase, external strategyagency Most frequent users of travel(12%) agents as decisive source; limited

use of contributory sourcesincluding brochures, guidebooks,newspapers, and state travelguidesUsed an average of 1.6 sources

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The proposed model (Figure 1) incorporates two impor-tant factors that characterize the vacation product: purpose oftrip and mode of travel. Testable hypotheses for each factorare developed from the discussion of the literature thatfollows.

Purpose of trip. The purpose of the trip is perhaps thegreatest influence on the traveler’s behavior (Morrison1996). Primary purposes for travel fall into four main catego-ries: business, visiting friends or relatives (VFR), other per-sonal business, and pleasure (Chadwick 1987). However,splitting the travel market into two main groups, businesstravel and leisure travel (which subsumes both pleasure tripsand visits to friends or relatives), is standard practice (Morri-son 1996). It is generally agreed that the needs, wants, andbehaviors of business and pleasure/VFR travelers are quitedifferent (McIntosh and Goeldner 1990). The same distinc-tion also is true in the leisure travel submarkets of pleasuretravelers (vacationers) and VFRs. We hypothesized that theinformation search behaviors of the two groups would bequite different as well. Given that the friends or relatives atthe destination represent an important and accessible sourceof information to the traveler, VFR travelers are less likely toconduct extensive search prior to their trips (Gitelson andCrompton 1983), perhaps even engaging in ongoing searchesas they plan their upcoming visits with their hosts over ex-tended periods of time. Vacationers, on the other hand, aremore likely to engage in prepurchase, external search using acombination of contributory and decisive sources if they arefirst-time visitors. People who vacation at the same placeregularly, however, probably engage in little prepurchasesearch, relying instead on their accumulated knowledge frompast visits. Thus, we hypothesized the following:

Hypothesis 3 (H3): Choice of information search strategywill vary as a function of the purpose of the trip: to va-cation or to visit friends or relatives.(a) When thepurpose of trip is to vacation, strategies will tend toemphasize prepurchase rather than ongoing sources,external rather than internal sources, and a mixture ofdecisive and contributory sources.(b) When the pur-pose of the trip is to visit friends or relatives, searchstrategies will reflect a greater use of ongoing ratherthan prepurchase sources, external rather than internalsources (specifically friends or relatives), and deci-sive rather than contributory sources.

Mode of travel. The major means of leisure travel inNorth America are commercial airplane and personal auto-mobile as well as, to a lesser extent, bus, rail, and water trans-portation (Chadwick 1987). The data used to explore themodel’s relationships included only the “drive market”; thus,our hypothesis is restricted to that single mode. A compre-hensive mode of travel comparison would have includedcategories such as air, train, bus, and automobile. Thus, whatis really being tested in this hypothesis are variations acrossdifferent types of vehicles. Each type of vehicle, however, in-volves unique traveler behaviors and associated informationneeds that are largely related to autonomy. For example,those traveling by recreational vehicle (RV) or in trucks/vansoutfitted for camping have a wider range of options at theirdestinations. In addition, RV travelers generally are more ex-perienced travel consumers and are more likely to have per-

sonal experience on which to base their trip planning. Thus,we hypothesized the following:

Hypothesis 4 (H4): Choice of information searchstrategy will vary as a function of the mode of travel:car, RV, or trucks/vans.(a)For those traveling by per-sonal automobile, strategies will tend to emphasizeprepurchase rather than personal sources, externalrather than internal sources, and decisive rather thancontributory sources.(b) For RV travelers, strategieswill tend to reflect ongoing rather than prepurchasesources, internal rather than external sources, and de-cisive rather than contributory sources.(c) For thosetraveling by truck or van, strategies will be character-ized by prepurchase, external sources and heavy useof contributory sources to supplement decisivesources.

Information Search Strategyand Tourist Characteristics

Information search strategies are not isolated from otheraspects of the consumer’s behavior. As our model (Figure 1)suggests, information search strategies both affect and areaffected by characteristics of the tourist. For example, adop-tion of search strategy frequently is dependent on knowledgederived from past experience. Also, changes in householdstructure often bring about changes in information search fora variety of products including home improvement, tools,appliances, furniture, entertainment, dining out, travel,sports equipment, automobiles, and clothing (Wilkes 1995).

Family life cycle. In a number of studies, researchers havesuggested that the series of relatively predictable stagesthrough which the family unit evolves (life cycle) is mean-ingfully related to consumer behavior (Wilkes 1995). Lei-sure travel patterns also have been found to be associatedwith the life stages of the family (Fodness 1992; Moutinho1987). In general, the predictions made for the three catego-ries of traveling parties should hold for family life cycle aswell. Accordingly, we hypothesized the following:

Hypothesis 5 (H5): Choice of information search strategywill vary as a function of the stage of the family lifecycle: households with children, younger householdswithout children, and retired households.(a) Forhouseholds with children, strategies will tend to em-phasize prepurchase rather than ongoing sources, ex-ternal rather than internal sources, and a combinationof both decisive and numerous contributory sources.(b) For younger households without children, strate-gies will tend to reflect prepurchase rather than ongo-ing sources, approximately equal use of internal andexternal sources, and decisive rather than contribu-tory sources.(c) For retired households, strategieswill be characterized by ongoing, internal, decisivesources.

Socioeconomic status. The different social classes dem-onstrate distinct preferences for a variety of products includ-ing leisure activities (Kotler and Armstrong 1995; Morrison1996). The exact role and measurement of social class, how-ever, continues to be controversial among consumer re-searchers (Boone and Kurtz 1995). Whereas social class

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typically is a multivariate construct determined by thingssuch as occupation, sources of income, accumulated wealth,highest level of income achieved, place of residence, andfamily history, some have argued that income alone suffices(Boone and Kurtz 1995).

In this study, we hypothesized that socioeconomic status,as defined by income, influences information search. Travel-ers at lower income levels might be expected to engage inmore search to offset their relatively greater perceived risk(van Raaij 1986). Higher income levels, on the other hand,have been found to be positively associated with greater lev-els of information search including the use of destination-specific sources (Gitelson and Crompton 1983).

Hypothesis 6 (H6): Choice of information searchstrategy will vary as a function of higher or lower so-cioeconomic status.(a) For travelers with lower so-cioeconomic status, strategies will tend to emphasizeprepurchase rather than ongoing sources, externalrather than internal sources, and a combination ofboth decisive and numerous contributory sources.(b)For travelers with higher socioeconomic status,strategies will tend to reflect ongoing rather than pre-purchase sources, both internal and external sources,and decisive rather than contributory sources.

Information Search Strategiesand Search Outcomes

From the consumer’s perspective, the most immediateobjective behind the development and implementation ofsearch strategies is to facilitate the purchase decision-makingprocess. Scholars, however, often frame search outcomesmore broadly and ascribe the primary motivation behindinformation search to the desire to make better consumptionchoices (Engel, Blackwell, and Miniard 1995). In our model,we take an even broader approach and emphasize the multi-dimensionality of search outcomes by adopting a cost-benefit perspective. The basic proposition is that consumerswill expend effort in search so long as the perceived benefitsexceed the perceived costs (Maute and Forrester 1991; Punjand Staelin 1983; Selnes and Troye 1989; Srinivasan andRatchford 1991).

The consumer perceives costs of search activities asresource expenditures—the time and money required toundertake search—as well as the cognitive effort required toprocess the information required (Srinivasan and Ratchford1991). Whereas the literature frequently has cited decreasedperceived risk as a desired outcome of search (Murray 1991),Bloch, Sherrell, and Ridgway (1986) proposed additionaldifferential outcomes for prepurchase and ongoing searches.For prepurchase search, better choice decisions, increasedproduct and market expertise, and heightened satisfactionwith purchasing have been suggested as outcomes. Ongoingsearch, on the other hand, has been believed to result in fur-ther purchasing efficiencies, personal influence (in terms ofopinion leadership), and impulse buying. Such outcomessuggest interactions with consumer characteristics. Desiredoutcomes no doubt are a function of the environmental influ-ences affecting the consumer (e.g., culture, social class, fam-ily). Conversely, each of the ongoing search outcomes couldinfluence future purchasing expertise, involvement, andattitudes.

There is little hard evidence on how various potential out-comes are actually weighed by the consumer. Clearly, how-ever, the literature suggests both short-term (quantity andquality of information acquired) and long-range (purchasesatisfaction) considerations as important criteria for evaluat-ing potential outcomes of search strategies. To the extent thatsuch factors figure into search strategy formulation, they arelikely to vary in importance and relevance across consumers.

It is important to remember that the acquisition and use ofinformation sources is a means and not an end to consumerbehavior. The primary motivation behind information searchis the desire to make better consumption choices (Engel,Blackwell, and Miniard 1995). The quality of purchase deci-sions is measured from the consumer’s perspective in termsof service quality, satisfaction/dissatisfaction, positive rec-ommendations to others, and repurchase intentions (brandloyalty). But are these the appropriate criteria by which tomeasure the impact of information search activities?

Although information search itself influences purchasebehavior and satisfaction, there also are intervening variablesaccording to the consumer decision-making process model.Depending on which model is chosen, the direct effect ofinformation may be mediated by evaluation and selection ofalternatives and trial use. So, although purchase satisfactionmay indeed be a result of information search, there are moredirect outcomes of information search as well.

The literature commonly identifies these in terms ofquantity and quality of alternatives identified, the “consid-eration set” of alternatives perceived to be available to theconsumer (Engel, Warshaw, and Kinnear 1991). Leisuretravelers develop their consideration sets through informa-tion search activities, as discussed previously. The size of theconsideration set is posited to be a function of informationsearch. It also has been suggested that there is a positive rela-tionship between the size of the consideration set and theextent of consumption for certain categories. Certainly, itprobably is not the case for most car buyers that the more oneknows about cars, the more one purchases. But in the case ofleisure travel, a bundled product, it has been shown that themore activities and opportunities one is aware of at theintended destination, the more one consumes (Chadwick1987; McIntosh and Goeldner 1990; Moutinho 1987). Inaddition, Etzel and Wahlers (1985) found a positive relation-ship between increasing levels of information search andincreasing travel expenditures.

Therefore, we hypothesized that more extensive informa-tion search would be related to higher levels of consumptivebehavior. However, we did not address causal flow. For ex-ample, a traveler might be staying longer because informa-tion search revealed more things to do. It is equally likely thatthe anticipation of a longer trip stimulated more informationsearch. Similarly, visiting a greater number of destinationsand attractions and spending more money while travelingcould have either resulted from or caused more extensivesearch. Investigation of these causal questions must awaitfurther study.

Hypothesis 7 (H7): Choice of information search strategyis related to the traveler’s length of stay such thathigher levels of information search are positively as-sociated with longer stays.

Hypothesis 8 (H8): Choice of information search strategyis related to the number of destinations visited by the

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traveler such that higher levels of information searchare positively associated with more overnight stops.

Hypothesis 9 (H9): Choice of information search strategyis related to the number of attractions visited by thetraveler such that higher levels of information searchare positively associated with more attraction visits.

Hypothesis 10 (H10): Choice of information search strat-egy is related to entertainment expenditures such thathigher levels of information search are positively as-sociated with higher travel-related expenditures.

Thus, tourist information search strategies are believed tobe the result of a dynamic process in which travelers use vari-ous types and amounts of information sources to respond tointernal and external contingencies in vacation planning.

METHOD

Survey of Visitors to FloridaTraveling by Automobile

Automobile travelers who stopped at official Florida wel-come centers and completed a short, self-administered wel-come center evaluation (which included their names andaddresses) constituted the sampling frame for data collec-tion. Of the approximately 1,800 visitors who completed thewelcome center evaluation in the period January throughJune 1990, a random sample of 1,000 were mailed surveys. Atotal of 716 surveys were returned (71.6%), and of these, 585(58.5%) were usable for the purposes of this study. Nonre-sponse bias could not be directly assessed because the sur-veys were completed anonymously. However, a comparisonof the responses to all items on the questionnaire for eachweek of returns provided an indirect assessment of nonre-sponse bias. Armstrong and Overton (1977) suggested thatlate respondents are similar to nonrespondents. This analysisrevealed no differences at thep < .05 level in the data acrosstime.

The self-report mail questionnaire used in this study wasmodeled after the person-to-person questionnaire used by theFlorida Division of Tourism in its ongoing Domestic Tour-ism Exit Survey Program. Unfortunately, the Florida Divi-sion of Tourism survey asked only limited questions regard-ing information sources, so it could not be used in this study.It was possible, however, to make a detailed comparison

between the official Florida data and the data collected forthis study. Overall, the match between the two samples wasquite good in terms of demographic and behavioral charac-teristics, even though auto travelers who did not stop at offi-cial welcome centers were not included in our sample. Pre-vious research from other states, likewise, has documentedthe lack of significant differences between out-of-state trav-elers who use welcome centers and those who do not (How-ard and Gitelson 1989).

Measures

The response variables needed to operationalize theinformation search strategy construct and to test the associ-ated hypotheses included (1) information sources used,(2) decision type, (3) purpose of trip, (4) traveling partycomposition, (5) mode of travel, (6) stage of family lifecycle, (7) socioeconomic status, (8) length of stay, (9) desti-nations visited, (10) attractions visited, and (11) entertain-ment expenditures. These variables are commonly measuredin tourism research and have been addressed in a number ofprevious studies (Ritchie and Goeldner 1987). In the presentstudy, measurement conformed with standard practice.

ANALYSES AND RESULTS

Contingency FactorsAffecting Information Search

Four contingency hypotheses were tested using chi-square analysis. The results are presented in Tables 3 and 4.These hypotheses predicted that there would be statisticallysignificant differences among leisure travelers classified bytheir information search strategies with respect to their deci-sion types (H1), traveling party composition (H2), purposeof trip (H3), and mode of travel (H4). Support was found forall contingency hypotheses.

H1 predicted that choice of information search strategywould vary as a function of the length of the pre-trip planningperiod. Table 3 shows that the Pearson chi-square statistic(recommended for large samples) was significant,χ2 =27.19,p < .007, supporting H1.

H1a, H1b, and H1c made specific predictions about howdecision type (as operationalized by pre-trip planning) wouldaffect choice of strategy. H1a predicted that a routine

226 FEBRUARY 1999

TABLE 3

SITUATIONAL INFLUENCES HYPOTHESIZED TO AFFECT CHOICE OF SEARCH STRATEGY (PERCENTAGES)

Decision Type (Pre-Trip Planning Period) Traveling Party Composition(χ2 = 27.19, p < .007) (χ2 = 24.76, p < .016)

CouplesRoutine Limited Extended Family (no children,

Search Strategy (< 1 month) (1-6 months) (> 6 months) with Children not retired) Retirees

Prepurchase mix 8.0 10.6 12.7 14.8 7.4 10.3Tourist bureau 7.2 8.0 7.6 3.0 13.1 6.7Personal experience 13.6 10.9 19.8 14.8 14.8 13.3Ongoing mix 2.4 5.3 5.1 3.7 2.8 5.9Friends or relatives 37.6 27.5 16.6 22.2 28.4 28.1Auto club 18.4 23.9 30.0 25.2 17.1 28.5Travel agent 12.8 13.9 8.3 16.3 16.5 7.0

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decision would be associated with an ongoing, internal orexternal strategy, using a decisive source. Table 3 demon-strates support for H1a, as travelers facing routine traveldecisions were most likely to use their friends or relatives toplan for their trips. As an information search strategy, friendsor relatives represent an ongoing, external source whoseinput is decisive. Next, H1b predicted that a limited decisionwould be associated with a prepurchase strategy, incorporat-ing both internal and external sources. A decisive sourcewould be used and, if present at all, one or two contributorysources would be used as well. Substantial support was foundfor H1b. Although use of internal sources was not a distin-guishing factor of those facing limited travel decisions, theirstrategy included the use of a single, decisive source (autoclubs or travel agents) and a smaller number of supportingcontributory sources. Finally, H1c predicted that an extendeddecision would require a prepurchase, external search using adecisive source supplemented by an above-average numberof contributory sources. Table 3 shows that those travelersundertaking extended travel decisions were most likely tohave used either a personal experience strategy or an autoclub strategy. In the case of the personal experience strategy,although it was not predicted, it could be interpreted as aneffect of the heavy repeat visitor component of the sample.Those travelers who return to the same destination year afteryear (which is typical of many visitors to Florida) mightengage in a form of ongoing search. These travelers mightnever really stop looking for or thinking up new ideas fortheir subsequent Florida trips. The use of auto clubs, a deci-sive source, partially supports H1c, although a greater use ofcontributory sources was expected. The average number ofsources used in the auto club strategy was 2.4. Thus, Table 3shows strong support for the general hypothesis that decisiontype affects information search. Results of specific predic-tions about the nature of these effects were mixed. Effectswere found as predicted for H1a and H1b. The test of H1cfailed to support our prediction but generated a reasonablealternative interpretation.

H2 predicted that choice of information search strategywould vary as a function of the traveling party composition.The results reported in Table 3 are supportive. Search strat-egy appeared to vary by the nature of the traveling party,χ2 =24.76,p < .016. These results appear to confirm the powerfuleffect that the presence of children has been found to have onconsumer behavior in other product categories (Wilkes1995). H2a predicted that the search strategies of families

traveling with children would be characterized by the use ofprepurchase, external sources and a decisive source supple-mented by an above-average use of contributory sources.Their use of auto clubs and travel agents supports H2a. H2bpredicted that couples traveling without children would use asearch strategy composed of prepurchase, external, decisivesources. Table 3 shows that they were the heaviest users oftourist bureaus, a strategy that was characterized by the useof prepurchase, external governmental sources (welcomecenters, local tourist offices, and state travel guides), and adecisive source, auto clubs. Thus, H2b is supported. H2c pre-dicted that retired couples, as experienced travelers, wouldbe most likely to use an ongoing, internal, decisive searchstrategy. The results in Table 3 support this prediction.

H3 predicted that choice of information search wouldvary as a function of the purpose of trip. General support wasfound for this hypothesis. Table 4 reports a significant Pear-son chi-square statistic,χ2 = 24.99,p < .000. The specificeffects of trip purpose on search strategy choice predicted byH3a and H3b were tested next. H3a predicted that for thissample of primarily repeat visitors to Florida, when their pur-pose of trip was to vacation, their search strategy would beinternal (based on past experience), ongoing (indicating highinvolvement), and decisive. H3b predicted that when theirpurpose of trip was to vacation, the strategy used would beongoing, external, and decisive. In other words, their primarysource of trip planning information would be their friends orrelatives. Table 4 shows strong support for both H3a andH3b. Those traveling to vacation were the most likely to relyon their personal experience—an ongoing, internal, decisivestrategy—to plan their trips. Those traveling to visit friendsor relatives used them to help plan their trip. Thus, the resultsof H3, H3a, and H3b strongly supported the idea that purposeof trip affects information search.

H4 predicted that choice of information search strategywould vary as a function of type of vehicle used. The Pearsonchi-square statistic was significant,χ2 = 20.83,p < .05, sup-porting H4. H4a predicted that travel by car would be associ-ated with a prepurchase, external, decisive strategy. Table 4offers mixed support for this proposition. Those traveling bycar were somewhat more likely to use travel agents than werethose traveling by other modes, but the former also weremore likely to use their friends or relatives. H4b predictedthat RV travelers would be more likely to use an ongoing,internal, decisive strategy. Table 4 shows that this was thecase. These travelers were the most likely to base their travel

JOURNAL OF TRAVEL RESEARCH 227

TABLE 4

PRODUCT CHARACTERISTICS HYPOTHESIZED TO AFFECT CHOICE OF SEARCH STRATEGY (PERCENTAGES)

Purpose of Trip Mode of Travel(χ2 = 24.99, p < .000) (χ2 = 20.83, p < .05)

Visit Friends RecreationalSearch Strategy Vacation or Relatives Car Vehicle Truck or Van

Prepurchase mix 11.5 8.0 8.2 10.7 16.4Tourist bureau 8.7 4.7 8.2 10.7 3.9Personal experience 16.8 6.0 13.3 21.3 11.5Ongoing mix 4.4 5.3 5.2 4.0 2.9Friends or relatives 24.1 34.0 27.9 25.3 23.1Auto club 22.3 30.0 23.0 24.0 30.0Travel agent 12.2 12.0 13.6 4.0 12.5

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planning on personal experience. Finally, H4c predicted thatthose traveling by truck or van would use a prepurchase,external strategy with a heavy emphasis on contributorysources to supplement a decisive source. H4c was supported,as these travelers were active users of travel agents and autoclubs supplemented by a mixture of prepurchase sources(brochures and guidebooks).

Thus, the results of the contingency hypotheses solidlysupport the relationships predicted in the model betweencontingency factors and information search. Decision type,purpose of trip, traveling party composition, and mode oftravel (defined as vehicle type) all were found to be related tochoice of information search strategy.

Tourist CharacteristicsAffecting Information Search

Two hypotheses regarding the effects of tourist charac-teristics were tested using chi-square analysis. The results arepresented in Table 5. These hypotheses predicted that therewould be statistically significant differences among leisuretravelers classified by their information search strategy withrespect to their stage of family life cycle (H5) and income(H6). Support was found for H6. The results of the test of H5,stage of family life cycle, were not significant.

H5 predicted that choice of information search strategywould vary as a function of the stage of family life cycle. Testresults (Table 5) revealed no significant association at the .05level between information search and stage of the family lifecycle,χ2 = 18.70,p < .096, thus failing to support H5 (i.e.,that the stage of the family life cycle would influence infor-mation search). The failure to support H5 precluded furtherdiscussion of H5a, H5b, and H5c. The test of H6 was sup-ported, however, finding information search to be signifi-cantly influenced by socioeconomic status, as measured byincome,χ2 = 15.04,p < .020.

H6a and H6b made specific predictions about howincome level would affect strategy choice. H8a predicted thata lower income would be associated with a combination ofprepurchase and external sources, both decisive and con-tributory. H6b predicted that a higher income would be asso-ciated with an ongoing, internal, decisive strategy. Table 5shows the opposite results for each prediction. A median splittechnique was used to differentiate higher from lowerincome levels.

The search strategy that distinguished those travelerswith lower incomes was reliance on their friends or relatives.

The search strategy that differentiated those with higherincomes was the use of governmental tourist informationsources: welcome centers, local tourist offices, and statetravel guides. In retrospect, these findings made sense giventhe retiree status of much of the sample. Thus, for this sam-ple, the lower income ranks included those with more travelexperience. Those with higher incomes tend to be stillemployed and might require greater amounts of informationto get the most from their limited vacation time.

Search Outcomes and Information Search

In general, the model hypothesized that the nature ofinformation search would influence both qualitative (attitu-dinal) and quantitative (behavioral) outcomes. Unfortu-nately, no attitudinal data were available from the secondarysource on which this study was based. Certain behavioraloutcomes were measured, however, and although noassumptions of causality could be made, four associationhypotheses were tested using one-way analysis of variance(ANOVA). These hypotheses predicted relationshipsbetween length of stay and information search (H7), betweennumber of destinations visited and information search (H8),between number of attractions visited and information search(H9), and between entertainment expenditures and informa-tion search (H10). Results of the four ANOVAs are found inTable 6.

One-way ANOVA results on length of stay were signifi-cant,F = 2.44,p < .018. Evidence of significant associationwas found as well for number of destinations visited,F =2.36,p < .001, for number of attractions visited,F = 2.36,p <.022, and for entertainment expenditures,F = 3.17,p < .003.In general, as predicted, the level of search effort increasedalong with increases in rates of consumption. For example,those travelers who used the greatest number of sources,Cluster 4, also stayed the longest. Those who made the few-est overnight stops also consulted the fewest sources. Thus,the model’s predicted relationships between search andsearch outcomes was confirmed by these analyses.

DISCUSSION

From the consumer and tourist information search litera-ture, we constructed a model of tourist information searchstrategies with their interrelationships, determinants, andoutcomes. The model was field-tested in a field study of

228 FEBRUARY 1999

TABLE 5

INDIVIDUAL DIFFERENCES HYPOTHESIZED TO AFFECT CHOICE OF SEARCH STRATEGY (PERCENTAGES)

Family Life Cycle Income(χ2 = 18.70, p < .096) (χ2 = 15.04, p < .020)

Households Households Lower HigherSearch Strategy with Children without Children Retirees (≤ $40,000) (> $40,000)

Prepurchase mix 13.4 8.4 10.3 10.0 11.3Tourist bureau 5.5 9.5 7.9 4.5 11.3Personal experience 14.6 12.9 14.5 14.0 14.0Ongoing mix 3.7 5.0 5.0 3.7 5.9Friends or relatives 22.0 27.4 29.3 31.0 21.1Auto club 24.4 22.4 25.6 24.3 24.2Travel agent 16.5 14.5 7.4 12.1 12.1

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leisure travelers using chi-square analysis and one-wayANOVA. Results converged to support the model and itsunderlying proposition that tourist information search strate-gies are the result of a dynamic process in which travelers usevarious types and amounts of information sources to respondto internal and external contingencies in vacation planning.

The findings of this research make several contributionsto the literature. These include (a) an expanded discussion ofa broad range of tourist information search behaviors, (b) asynthesis and delineation of contingency factors affectingtourist choice of search strategy and information sources,(c) the consideration of potential interrelationships amongalternative tourist search strategies, (d) an emphasis onincreased awareness of potential differences in touristresponses to diverse environmental conditions, (e) a descrip-tion of testable hypotheses regarding the conditions underwhich various search strategies or combinations of strategiesare employed, (f) a synthesis and discussion of the interrela-tionships between information search and other touristbehaviors, (g) the consideration of a broader range of infor-mation search outcomes, and (h) suggestions for makingfuture information search research more relevant to tourismscholars and practitioners.

Major caveats of this study must be observed in fourareas: empirical setting, sample, data collection, and analy-sis. First, we examined a fairly homogeneous group of con-sumers in a single product category. Although the respon-dents were “real-world consumers,” information search maybe monomorphic, that is, specific to product category. Thesample also limited generalizability of the results. Given thenonrandom nature of the sample and the focus on a singlemode of travel, there is no way of judging how representativethese real-world consumers are of the real world. This con-cern extends to issues of data collection. Whereas issuesabout the appropriate sampling unit in traveling partiesalways are problematic in tourism research, this study alsosuffers from the unknown respondent problem inherent inmail surveys. We have no way of knowing who in the travel-ing party filled out the questionnaire. Finally, the data werecollected retrospectively, with all measures taken at onceusing a common method.

Managerial Implications

There has long been an interest in how travelers select,acquire, evaluate, and use the information on which theybase their trip planning. The belief that systematic patterns oftourist behavior are attributable to the information available

to them compels its study. Marketing managers have usedvarious types of analyses to identify customers’ searchbehavior for purposes of segmentation, product positioning,and development of targeted promotion strategies for differ-ent market segments (Boone and Kurtz 1995; Evans and Ber-man 1994; Kotler and Armstrong 1995). These activitieshave been critical to the marketer who seeks to better under-stand the differential needs driving consumer decision-making processes and associated information searches tocommunicate product benefits most effectively and effi-ciently. This is especially important within an overall contextof rapidly increasing competition in the travel/tourism/hospi-tality industry, where even marginal improvements in under-standing and matching customers’ needs can increase com-petitive advantage.

Managerially, our model provides a theoretical andempirical basis for segmentation, product positioning, andpromotional strategy development related to tourist informa-tion search behaviors. A close examination of the specificfindings of the hypothesis tests provides rich insights forunderstanding, predicting, and possibly influencing a criticalcomponent of tourist behavior.

Implications for Future Research

Consumer researchers interested in the purchase decisionprocess frequently have focused on information searchbehavior either to identify and classify information sourcesused or to examine the relationships between informationsearch and other factors affecting and affected by the con-sumers (Berning and Jacoby 1974; Bettman 1979; Furse,Punj, and Stewart 1984; Jacoby, Chestnut, and Fisher 1978;Leigh and Rethans 1984; Lynch and Srull 1982; Moore andLehmann 1980; van Raaij 1977; Winter 1975). Additionalresearch on tourist information search is needed in manyareas. The focus here is on research that would be most use-ful in testing, revising, and elaborating the model of touristinformation search presented. Both descriptive and prescrip-tive research are needed.

A fertile area for future descriptive research would be tomore carefully explicate the strategies, constructs, and pro-posed interrelationships outlined in our model. Outcomes arean area of particular importance given their multidimension-ality and the complexity of their relationships to both infor-mation search activities and the tourist decision-making pro-cess. Research is needed that examines how consumersperceive, evaluate, and weigh various potential outcomes ofinformation search.

JOURNAL OF TRAVEL RESEARCH 229

TABLE 6

OUTCOMES HYPOTHESIZED TO BE INFLUENCED BY CHOICE OF INFORMATION SOURCE

Length of Stay Number of Number of Entertainment Expenditures(F = 2.44, p < .018) Overnight Stops Attractions Visited (F = 3.17, p < .003)

Search Strategy (nights) (F = 3.62, p < .001) (F = 2.36, p < .022) (dollars)

Prepurchase mix 18.4 2.4 1.8 167Tourist bureau 19.7 2.4 2.1 185Personal experience 23.7 1.8 1.3 139Ongoing mix 30.5 2.8 2.2 173Friends or relatives 17.7 2.0 1.4 105Auto club 18.2 2.3 1.6 74Travel agent 9.5 1.8 1.4 109

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From a theoretical perspective, it also would be useful toexplore the link between the concept of information searchbehavior as manifest by search strategy and the concept ofinformation processing behavior. The issue here is whetherthe information gathered via one search strategy is processedsimilarly to or differently from information gathered byanother search strategy and, ultimately, whether or not thisaffects the nature of the decision processes and the decisionmade.

Prescriptive research is needed as well to provide practi-tioners with direction for achieving desired outcomes. Giventhe complexity underlying seemingly straightforward con-sumer use of information sources, practitioners need to besensitized to the various factors involved and their relation-ships. In other words, prescriptive research should beginwith a more solid foundation of descriptive findings.

Our research represents a much-needed contribution tothe literature in terms of the “who, what, when, where, andhow” of tourist information search. It is an incompletemodel, however, as it is missing what is perhaps its most use-ful and interesting element, “why.” We close by emphasizingthe need for more theoretical and empirical research on thismost important issue in understanding tourist informationsearch.

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