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Impulse purchasing in tourism –

learnings from a study in a matured

marketChristian Laesser a & Sara Dolnicar b

a Institute for Systemic Management and Public Governance,

Research Center for Tourism and Transport, University of St.

Gallen , Dufourstrasse 40a, CH-9000 , St. Gallen , Switzerlandb Institute for innovation in Business and Social Research,

University of Wollongong , Northfields Avenue, Wollongong ,

Australia

Published online: 15 May 2012.

To cite this article: Christian Laesser & Sara Dolnicar (2012) Impulse purchasing in tourism –

learnings from a study in a matured market, Anatolia: An International Journal of Tourism and

Hospitality Research, 23:2, 268-286, DOI: 10.1080/13032917.2012.688409

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Impulse purchasing in tourism – learnings from a study in a matured

market

Christian Laessera* and Sara Dolnicarb

a Institute for Systemic Management and Public Governance, Research Center for Tourism and Transport, University of St. Gallen, Dufourstrasse 40a, CH-9000 St. Gallen, Switzerland; b Institute

for innovation in Business and Social Research, University of Wollongong, Northfields Avenue,Wollongong, Australia

( Received 7 December 2011; final version received 23 April 2012)

Existing literature suggests that information search and planning always precede travel

activity. This contrasts with our understanding of purchasing behaviour in othercontexts where a significant amount of non-planned, impulse purchasing occurs. Wepropose that impulse purchasing also occurs in tourism. Results from an empiricalstudy show that impulse purchasing does occur in tourism and is specifically associatedwith shorter trips, a small number of travel companions, specific travel motivations,and familiarity with the destination.

Keywords: impulse purchase; planned purchase; travel planning tourism services

Introduction

It is widely accepted that the purchasing of core tourism services is associated with

planning (for an extensive discussion of the process view of travel planning and execution,see Correia, 2002; Crompton, 1992; Hsieh & O’Leary, 1993; Um & Crompton, 1990;

Vogt & Fesenmaier, 1998; Woodside & Lysonski, 1989), mainly because travel is

assumed to be a high involvement activity (Kuss & Tomczak, 2007). Many studies thus

aim to understand the relationship between planned and executed behaviour in order to

predict the latter (for an overview, see March & Woodside, 2005; note that Ajzen and

Driver (1992) in originally used leisure activities as the research setting for testing the

theory of planned behaviour).

However, the increased availability of last-minute offers and low-cost airline

connections, as well as increased interest in short trips suggest that in many cases travel

planning is reduced substantially. For example, in 13% of all trips taken by the Swisspopulation the time between making an irreversible travel decision and departure is less

than 7 days (Bieger & Laesser, 2008). Hence, very short-term travel planning or even

impulse-type purchasing behaviour appears to exist also in the tourism context. Yet,

nothing is known about the situations in which such behaviour is most likely to occur.

The aim of the present study is to develop knowledge about impulse purchasing in

tourism. Specifically, we aim to (1) provide a definition of impulse purchasing in tourism,

and (2) empirically determine trip characteristics associated with impulse purchasing

in tourism.

ISSN 1303-2917 print/ISSN 2156-6909 online

q 2012 Institute for Systemic Management And Public Governance at the University of St. Gallen

http://dx.doi.org/10.1080/13032917.2012.688409

http://www.tandfonline.com

*Corresponding author. Email: [email protected]

Anatolia – An International Journal of Tourism and Hospitality Research

Vol. 23, No. 2, August 2012, 268–286

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Literature review

Marketing, and especially retail research, identifies impulse behaviour as having a

powerful and real influence in the consumer buying behaviour process (Bayley &

Nancarrow, 1998; Hausman, 2000). According to Lee and Kacen (2008; derived from

Kollat & Willett, 1967; and also Prasad, 1975), “impulse buying can be defined as anunplanned purchase that was not anticipated or planned before the shopper entered the

store” (p. 266). Although an extreme form of the normal buying behaviour process, it has

been long recognized and capitalized on by major fast-moving consumer goods companies

(Crawford & Melewar, 2003; Lee & Kacen, 2008; Mogelonsky, 1998). Impulse purchases

can range from small-scale supermarket items such as candy to “big-ticket” items such as

larger home appliances and even automobiles (Beatty & Ferrell, 1998; Rook & Fisher,

1995; Rook & Gardner, 1993; Weun, Jones, & Beatty, 1998). The key characteristics of

such purchases across those product categories include emotionality, lack of intention, a

low level of reflection, and instantaneousness purchase and consumption planning

horizons (Dowling & Staelin, 1994; Hoch & Loewenstein, 1991; Lee & Kacen, 2008;Rook, 1987; Rook & Fisher, 1995).

Impulse buying behaviour in general

In classical mechanics, an impulse is defined as the integral of a force with respect to an

amount of time. An impulse may also be regarded as the change in momentum of an object

to which a force of some kind is applied. In psychology, an impulse is a wish or urge

(force), particularly a sudden one (time) to act in a certain manner (Hofmann, Strack, &

Deutsch, 2008), that is, for example, to make a purchase. In his 1962 seminal paper, Stern

proposes four potential categories of unplanned purchases, ranging from pure impulse

buying (total lack of preplanning) to planned impulse buying. The latter implies that aconsumer has a product or product category in mind for purchase, but has not decided yet

which brand to buy (cf. Figure 1). Drawing on these concepts, researchers agree (Rook,

1987; Rook & Fisher, 1995) that impulse buying generally occurs when an individual

makes a more or less unintended, unreflective, and immediate purchase. The object of the

purchase can range from a product category to a very specific product within a given

product category.

Lack of intention arises from a sudden urge to buy a specific item, mostly in a shopping

context, when the desire and decision to buy occurs after an external stimulus – for

example, the person sees or is aware of an article (Hoch & Loewenstein, 1991).

Planned buying Impulse buying

Pure impulse buying

-> total lack of planning

Planned impulse buying

-> product or category in mind

-> no decision yet which brand to buy

Figure 1. Conceptualization of impulse purchasing. Source: Own conceptualization adapted fromStern (1962), Rook (1987), Rook and Fisher (1995).

Anatolia – An International Journal of Tourism and Hospitality Research 269

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Lack of reflexion means that a purchase is made without engaging in a systematic

evaluation. In an extreme case, the only available information, aside from internal

information (such as previous consumption experience), is the external information

available at the time of purchase, for example, product display incentives, or people in the

store (Lee & Kacen, 2008). This differs from a fully planned purchase, with unconstrained planning time, in which all sources of information are available and potentially consulted,

for example, internal and external sources, including media, interpersonal and expert

advice (Dowling & Staelin, 1994). Individuals are thus less likely to consider the

consequences or to think carefully before making the purchase, especially in terms of

income allocation for a specific item (Rook, 1987).

Finally, regarding the immediate character of a purchase, the time interval between

being aware of a purchase object and buying it is minimal in an impulse purchasing

situation (Barratt, 1985; Rook, 1987).

In line with research on impulsiveness in the psychology literature, studies in

marketing observe, similar to Jones, Reynolds, Weun, and Beatty (2003), that “impulse

buying tendency is a consumer personality trait indicating that individuals can be

distinguished from one another based on this trait” (p. 503). Previous research treats the

impulse buying tendency as a generalized trait (that is, trait impulsiveness) as consistent

across product categories (Beatty & Ferrell, 1998; Rook & Fisher, 1995; Rook & Gardner,

1993; Weun et al., 1998). However, as far back as 1971, Kassarijan noted that an important

task for personality research in consumer behaviour is to determine whether such a trait

can be generalized across product categories, and also whether it should be measured on a

product-specific level. These concerns prompted our investigation of the full extent and

quality of impulse buying behaviour, as well as its potential variety across product

categories (Jones et al., 2003).

More recent research reveals that different factors influence impulsive buyingbehaviour, ranging from simple socio-demographics (such as age and gender) to more

complex constructs (such as trait impulsiveness described above, for example, Jones et al.,

2003; Rook & Fisher, 1995; Weun et al., 1998), as well as the presence of others (Luo,

2005), the consumer’s mood (e.g. Beatty & Ferrell, 1998; Rook & Gardner, 1993),

evaluation of the appropriateness of engaging in impulse buying (e.g. Rook & Fisher,

1995), individual and environmental situation (Peck & Childers, 2006), self-identity (e.g.

Dittmar, Beattie, & Friese, 1996; Lee & Kacen, 1999), and cultural orientation (Kacen &

Lee, 2002; Lee & Kacen, 1999).

Most studies focus on retailing, partially because of the prevalence of impulse buying

in today’s retail marketplace (Jones et al., 2003), which can make up more than one-thirdof department store purchases (Bellenger, Robertson, & Hirschman, 1978). However,

because impulse purchases can also occur with big-ticket items (Beatty & Ferrell, 1998;

Rook & Fisher, 1995; Rook & Gardner, 1993; Weun et al., 1998), the transferability of

the concept of impulse purchases to other product categories, including travel, remains

untested. The likelihood of someone buying a car or a larger home appliance after only

minimal evaluation is rather slim. Hence, the degree of how immediate a purchase needs

to be to qualify as an impulse purchase probably varies according to the size of the ticket.

Therefore, we hypothesize that the duration of the process associated with the purchase

(and sometimes consumption), including the planning horizon for its evaluation, varies

accordingly. The degree of this time compression can be posited along a continuum,

ranging from extensively planned to impulse buying, where the planning is associated

at minimum with a product category and, in certain cases, even with a brand (Cobb &

Hoyer, 1986).

270 C. Laesser and S. Dolnicar

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Conceptualizing impulse purchasing in tourism

Travel-related decisions are considered to be contingent and coherent portfolio decisions,

incorporating a multiplicity of partial decisions. They include travel dates and duration of

travel, choice of members of the travel party, a budget for expenditure (absolute, and in

terms of income allocation), a core leisure pursuit, including travel motivation, choice of destination, transport and route to the destination, and choice/category of accommodation

(Becken & Gnoth, 2004; Hyde & Laesser, 2009; Laesser, 2003; Tay, McCarthy, &

Fletcher, 1996). Consequently, there is not one, sole decision related to a given trip, but

rather a multiplicity of decisions about each single component of the portfolio – which is

why the concept of impulse purchase (and thus time related to that type of buying) should

be adapted accordingly.

As discussed in the previous section, an impulse consists of two elements: (1) a wish or

urge to act in a certain manner, and (2) a time-related issue meaning that this urge is

sudden, indicating a very short time frame between attention (becoming aware of

something) and action (its purchase).As derived from motivation theories, the source of the impulse is either endogenously

activated (“push”, from within the person) or exogenously activated (“pull”, from outside

the person – for example, via a purchase incentive) (Bieger & Laesser, 2002b; Cha,

McCleary, & Uysal, 1995; Gitelson & Kerstetter, 1990; Yuan & McDonald, 1990). We

thus propose, in line with Curtin (1982) and Wood (2005), to extend impulse purchasing to

discretionary spending – regardless of where the impulse or need to purchase comes from.

Curtin and Wood base their rationales on Katona’s argument, in which the Second World

War economy provided the Western world with “substantial increase in the average

family’s income together with a great change in the distribution of income . . . Millions of

consumers have latitude in deciding whether to spend or to save, on what to spend and how

to save” (1975, pp. 19–20). Katona’s concept of consumer discretion includes consumercontrol and consumer allocation of time and income – that is, serious control of when,

where, and how much to spend. According to Katona, discretionary spending goes beyond

compelled purchases, or those that are strictly necessary. He refers mainly to the purchase

of consumer items, but also includes purchases of travel and items “often connected with

recreation and luxury” (1975, p. 29), as well as with emotions and less rationality (Bayley

& Nancarrow, 1998; Hausman, 2000).

Because travel is a portfolio-based decision, the time component of impulse purchases

in travel also needs to be analysed in detail. Travel decisions contain at least three

components relating to time:

. the time allocation decision in terms of when and how much time to be absent from

home (i.e. the trip duration);

. the portfolio decision regarding what to consume during a trip (trip structure; see

Bieger & Laesser, 2004; Hyde & Laesser, 2009); and

. the decision regarding when to commit to a service once selected.

Associated with the above components are three core time frames, which can be variably

compressed:

. decision–booking time frame, describing the time between the first decision of at

least one or more portfolio elements of a trip;

. booking–departure time frame, describing the time between the first legally binding

action (booking) towards a trip and the departure; and

. departure–return time frame, describing the duration of a trip.


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We define impulse purchases in tourism as planned impulse purchasing (this

acknowledges that impulse buyers in tourism at least consider taking a vacation before

booking), with a maximum of one week between the decision to take a trip and the

departure. In so doing we align our proposed definition with Stern (1962), Rook (1987),

and Rook and Fisher (1995), who assume that a consumer who engages in an impulsepurchase has a product or product category in mind for immediate purchase but has not

decided yet which brand to buy.

Development of research hypotheses relating to the nature of impulse purchasing in

tourism

Duration of trip and travel composition

From the structural theory of a trip (Hyde & Laesser, 2009; Tay et al., 1996), we can

deduct that an association exists between the duration of a trip and its planning horizon,

basically due to the different lengths of trips associated with different types of trips. Forexample, touring holidays (self-drive) are more complex to organize and normally last

longer than “stay-put” holidays at a beach. Thrane (2012) also stresses that “the longer the

planning or booking time, the longer the trips tend to be”. Thus, we propose the first of a

number of hypotheses:

Hypothesis 1: The longer the departure– return time frame (trip duration), the longer the

travel planning time frame.

Eymann and Ronning (1997) and Walsh, John, McKean, and Hof (1992) propose that

family size plays an important role in recreational decisions: the number of members of a

household also influences various aspects of vacation decisions (Hsieh, O’Leary, Morrison,

& Chang, 1993; Sheldon & Mak, 1987). In addition, different individual time allocations

must coincide when more than one person takes a trip. Hence, we propose the following:

Hypothesis 2: The higher the number of participating household members, the longer

the travel planning time frame for a trip.

Income and travel expenditure

In a study by Abratt and Goodey (1990), the authors suggest that higher income is one of

several factors that can account for a higher level of impulse purchasing. Mogelonsky

(1994) goes further to suggest that impulse buying is reserved for consumers who canafford it. We expect consumers with higher incomes to have fewer constraints on acting on

their opportunities; they could have a more “open” buying list, which allows them to

pursue sudden and unexpected purchasing ideas with less difficulty paying for them. Thus,

they may be able to buy on impulse more frequently than can others. For people with lower

incomes, short-term buying decisions may be more likely to be interrupted by the so-called

“income block”, which may lead to lower buying frequency and expenditures

(Mogelonsky, 1994). Because income is often related to education as well as professional

position (Becker & Tomes, 1986; Waelde, 2000), these characteristics might equally

influence the share of impulse buying.

From these ideas, we form the following hypotheses:

Hypothesis 3: The higher the household income, the shorter the travel planning time

frame.


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Hypothesis 4: The higher the type of terminal education, the shorter the travel planning

time frame.

Hypothesis 5: The higher the type of professional position, the shorter the travel

planning time frame.

As is found for travel, several studies demonstrate that overall travel expenditure per tripas well as daily travel expenditure is significantly associated with the duration of a trip

(Cannon & Ford, 2002; Fredmann, 2008). There is a logarithmic association between

overall travel expenditure and duration of trip, and an exponential association between

yearly expenditure and duration of trip (Beritelli, Bieger, & Laesser, 2006; Laesser &

Crouch, 2006). However, the literature gives no indication of how travel expenditures are

associated with travel planning, necessitating a deductive approach to this topic.

Hausman (2000) suggests that impulse-type buying is a hedonic need predominantly

motivated by achievement of higher-order motives, which, in turn, leads to different types

of impulse buying behaviour, including non-economic and immediate reasons, such

as fun, fantasy, and social or emotional gratification. Extending the original impulsepurchase concept, the transactional dimension of an impulse purchase should be

considered, as well as the post-acquisition in-use/functional and (often experiential)

dimension. This suggestion is also offered by Bayley and Nancarrow (1998), who provide

evidence for the fact that the post-acquisition and in-use/functional dimensions of any

purchase deflate the “dark side” of potential impulse buying behaviour at the time of

acquisition. Dittmar et al. (1996) report that in developed countries purchase and

consumption of products are increasingly associated with expressing a sense of self-

identity. Shopping and travelling (as surrogates for the purchase of services) have become

major lifestyle activities, which might explain the increase in non-planned or very quickly

planned purchases.

Drawing on Hausman’s (2000) notions, we might conclude that short time frames

regarding travel planning might be associated with higher travel expenditures and higher

shares of income allocation for a given trip – either overall or per diem. Hence, we propose:

Hypothesis 6: The shorter the travel planning time frames, the higher the overall and per

diem travel expenditure.

Hypothesis 7: The shorter the travel planning time frames, the higher the overall and per

diem income allocation for a given trip.

Core leisure pursuit

Consensus exists among scholars that travel motivation is an excellent differentiator and

segmentation criterion in travel behaviour (Bieger & Laesser, 2002b; Cha et al., 1995;

Dolnicar, 2004; Dolnicar & Leisch, 2003; Gitelson & Kerstetter, 1990; Yuan &

McDonald, 1990). From the literature we also know that short-term purchase planning is

associated more with emotion than rationality (Bayley & Nancarrow, 1998; Hausman,

2000). On the basis of that, we propose:

Hypothesis 8: Travel motivations differ in dependence of the length of the travel

planning time frame.

Information sourcing

“Travel business is an information business” (Schertler, 1994, p. 23). Travel products are

mostly intangible personal service products, involving personal interactions between


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customers and service providers (Lovelock & Wright, 1999; Normann, 1996; Teare, 1992;

Zeithaml, Parasuraman, & Berry, 1990). They are delivered away from home, often in

unknown places, inducing functional, financial, physical, psychological, and social risks

(Dolnicar, 2005, 2007; Lovelock & Wright, 1999; Teare, 1992). In addition, the

consumption and production of tourism products always coincide, creating high personalinvolvement (the uno actu principle; see Bieger, 2006). According to the economics of

information, these characteristics often lead to high personal investments of time, effort,

and financial resources for customer decision-making (Lamberton, 1998; Wohler, 1997;

Schertler, 1994). Traditional perspectives of information search focus on functional needs,

defined as motivated efforts directed at or contributing to a purpose (Vogt & Fesenmaier,

1998). According to this approach, the search for information enables tourists to reduce the

level of uncertainty and enhance the quality of a trip (Fodness & Murray, 1997; Schertler,

1994; Schiffmann, 1972; Teare, 1992). From this, we might conclude that travel most of

the time includes planning and information processing, mostly related to purchase

situations (Assael, 1984).

However, contrasting to this approach is the inclusion of experience in the purchase

deliberation process. Experience, which can be considered as the accumulation and

habitual buyer behaviour, ultimately allows for well-informed purchase behaviour without

time-consuming deliberation (Katona, 1975). Consequently, tourists visiting a place they

are familiar with are unlikely to engage in a great deal of deliberation, instead relying on

their accumulated knowledge (Fodness & Murray, 1999). Therefore, no source of

information, except perhaps the one triggering a purchase, would be important with longer

planning periods (Dowling & Staelin, 1994; Lee & Kacen, 2008).

Thus, we propose:

Hypothesis 9: The shorter the travel planning time frame, the less important are sources

of information for travel planning.

Because internal information, based on previous trips, is another potential source of

information, especially when it comes to quick decisions (Lehto, Kim, & Morrison, 2006),

we also propose the following:

Hypothesis 10: The higher the number of previous trips to a destination, the shorter the

travel planning time frame.

Choice of transportation to and accommodation at the destinationAirlines, hotel chains, and single hotels have become successful price discriminators

(Hunkel, 2001; Jaggi, 2000). Aimed at maximizing their yield per customer transaction

(short term) and customer relation (long term), they set prices according to demand and

willingness to pay (Belobaba & Botimer, 1999; Desiraju & Shugan, 1999). As intended by

the suppliers, customers react to the incentives from this pricing scheme by behaving as

opportunistically as possible, especially when it comes to leisure travel, which can be

planned (Bruhn & Meffert, 2003; Kimes, 1989). Hence, we would expect a certain effect

on the consumer’s behaviour: that they would follow price-driven planning horizons

(Fassler, 2006). From this, we offer the following:

Hypothesis 11: Means of transportation that require advance booking are associated with

longer travel planning time frames compared with means of

transportation that do not need a booking.


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Hypothesis 12: Means of accommodation that require advance booking are associated

with longer travel planning time frames compared with means of

accommodation that do not need a booking.

AgeTo complement previous hypotheses regarding the socio-demographic factors in travel

planning, we finalize this section with an age-related hypothesis. The literature suggests

that younger people have more impulsivity compared with older people (e.g. Rawlings,

Boldero, & Wiseman, 1995). Regarding buying behaviour, it is expected that younger

consumers are more likely to experience an urge to buy things spontaneously when exposed

to the relevant objects and to act on the urge, whereas older consumers may demonstrate

better ability to control their buying. Therefore, we present the following hypothesis:

Hypothesis 13: The travel planning time frames of young people are shorter than those of

older people.

Methodology

The study was conducted in Switzerland, which represents a prototypical mature travel

market. Swiss travel shoppers are experienced as well as sophisticated (Hopkins, Rodi, &

Vincent, 2002), and their domestic buying environments are highly evolved. For example,

in Switzerland, the net travel propensity is well above 80% (see Bieger & Laesser, 2008).

The share of frequent tourists from this country (68%) is well above the accepted threshold

for a mature market (50%; see also Bieger & Laesser, 2008). Consequently, as in most

mature markets, product utilities are typically driven by price and quality issues as well

as brands. Growth in such markets is only small (D’Souza & Rao, 1995; Ehrenberg,

Barnard, & Scriven, 1997; and regarding Switzerland, Bieger & Laesser, 2008).Our study is based on the analysis of parts of Travel Market Switzerland 2007 , a survey

conducted with the Swiss resident population in 2007. Data collection took place via self-

administrated and structured written diary-like interviews with a representative sample of

households and all their members, surveying all their private trips during 2007 (for the

specifics of the survey, see www.alexandria.unisg.ch/Publikationen/46512).

Survey participants could either complete a self-administrated and structured paper-

and-pencil questionnaire or complete an identical questionnaire online. It was entirely up

to them to decide which means of completion they chose.

The questionnaire included a range of questions (available from the technical report

online). The key measurements for this study are questions about people’s travelmotivations and information search. Regarding travel motivation, items included were

taken from Bieger and Laesser (2002a), Gursoy and Gavcar (2003), Gustafson (2002),

Hirtenlehner, Morth, and Steckenbauer (2002), Jang and Cai (2002), Kiefl (1997),

Kim and Jogaratnam (2002), Kim and Lee (2000), Shoemaker (2000), Sirakaya, Uysal,

and Yoshioka (2003), and Wickens (2002). Regarding information sources, the items were

taken from Bieger and Laesser (2004), Fodness and Murray (1999), Lehto et al. (2006),

Luo, Feng, and Cai (2004), Tideswell and Faulkner (1999), and Pearce and Schott (2005).

A full list of measurements can be found at Bieger and Laesser (2008), to download at

http://www.alexandria.unisg.ch/publications/46512.

Data collection and sampling were administrated by IHA-GfK Switzerland (a leading

market research institute) on behalf of the Institute for Public Services and Tourism (which

provided the survey instrument, methods, and financial sources). For the whole of 2007,

participants completed one questionnaire for each private trip with one or more overnight


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stays. Repetitive trips (for example, to second homes) were not to be recorded because

they are considered part of test persons’ usual environments. To secure the constant inflow

of responses during the entire duration of the survey, the participants were contacted four

times during the survey period (which lasted all 2007), reminding them to turn in their

completed questionnaires or indicate that they had not travelled within a given quarter.The overall sample recruited for this study consisted of 2712 households. The sample

was recruited in two ways:

. 1187 households were recruited by phone. The contacts were (within quotas of

region, size of household, and type of household) randomly drawn from the national

database “CH-plus Consumer” by AZjDirect AG. This database is representative of

98% of all households in Switzerland.

. 1525 households were recruited from an online panel of 45,000 active members,

representative of the Swiss resident population. Seventy per cent of this panel was

originally recruited via CATI; the other 30% through personal contacts (for

example, from face-to-face interviews), Internet providers, communities, and other.Self-selection and registration through banner ads or similar was explicitly not

possible.

Overall, 1898 households (70% of the overall sample drawn) participated across all four

quarters in the study year (either by completing questionnaires or by indicating that they

had not travelled), and could thus be included in the final sample. The non-weighted sample

thus consisted of 1898 households, including 4387 persons (that is, 2.3 persons per

household, where the mean size of a Swiss household is 2.2), of which a large proportion

undertook an overall 10,903 trips (trip cases). The database is representative of 90% of

Swiss, and approximately 50% of foreign (assimilated) citizens in the German- and French-

speaking areas of Switzerland (the Swiss population in Switzerland is 6 million, while theoverall foreign population in Switzerland is 1.5 million), that is, 6125 million people.

From the information gathered, we derived an understanding of when at least one

element of the travel-related portfolio decision was definitely made, when the first

bookings were made for the trip, and when the test persons departed for the trip.

The latter constitutes a newly created variable, “planning behaviour”, with the

following delimitations and codes: (1) “a decision–booking AND booking–departure

time frame of less than one week” (test group), (0) “all other planning time frames”

(control group). A preliminary descriptive analysis of this variable revealed that 13.5% of

the cases (that is, trips) belonged to Group 1, and 86.5% to Group 0, which means that

13.5% of all trips taken by the Swiss population had a travel planning time frame of lessthan one week.

Analysis

For the analysis, we applied a binary logistic regression of variables denominating our

hypotheses into two groups of planning behaviour: (code: 1) “a decision–booking AND

booking– departure time frame of less than one week” (test group) compared with (code: 0)

“all other travel planning horizons” (control group). The reason for conducting a binary

regression as opposed to an OLS model is constituted in the desire to analyse/compare two

segments (test and control groups) rather than predicting behavioural differences due to

incremental changes in the decision–departure time frame.

The variables (listed according to the order of the hypotheses) regressed against the

above-planning variable included (parentheses indicate scale: duration of trip (metric),


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number of participating members from the household, household income (metric) and trip

expenditure per person (overall; per day; absolute and related to income; metric), 25 types

of travel motivations (on a five-point importance scale), 28 types of information sources

(on a five-point importance scale), number of previous trips to destination (metric;

representing a key internal source of information), means of transportation (out of 10categories), age groups (out of nine categories), terminal education (out of 10 categories),

professional position (out of 15 categories).

Because of the exploratory character of our study, and with the aim of finding a

minimal model to explain short-term planning in tourism, we chose a backward stepwise

procedure. This analysis begins with a full or saturated model, and variables are eliminated

from the model in an iterative process. The fit of the model is tested after the elimination

of each variable to ensure that the model still fits the data adequately. When no more

variables can be eliminated from the model, the analysis is complete. Hence, this

procedure allowed us to maximize the number of explanatory variables. Because of the

distribution of the cases, and in order to facilitate the interpretation of the results, we set

the classification cut-off at 0.135. (We reiterate here that the previous descriptive analysis

showed that 13.5% of all trips taken by the Swiss population have travel planning time

frames of less than one week.) To test if our data adequately fitted the model, we

performed the Hosmer and Lemeshow test, which is considered more robust than the

traditional Chi-square test, particularly if continuous covariates are in the model, as are

found in our study (see Menard, 1995).

Propositions were tested based on the resulting model coefficients. If rejected, 1000

cases we randomly selected and performed Chi-square tests on item levels across the

groups of planning behaviour to assess whether potential differences were significant or

merely due to chance variations.

Results

The data fitted the model at an acceptable level, with an R 2 of 0.473 and a Hosmer–

Lemeshow test statistic of 0.36. From the latter we can conclude that we failed to reject the null

hypothesis, according to which there is no difference between observed and model-predicted

values. This implies that the model’s estimates fitted the data at an acceptable level (well-

fitting models show non-significance on the H-L goodness-of-fit test, indicating model

prediction is not significantly different from observed values). The classification table further

revealed that 80% of all cases were correctly classified; regarding group membership (code:

1), short-term planning, 74% of all cases were correctly classified.A large number of model predictors were revealed as significantly different from zero.

For an overview, see Table 1, where (for readability reasons) only significant coefficients

are presented. However, none of the socio-demographic predictors (age, gender, terminal

education, professional position) produced significant coefficients, as were a large

majority of transportation means as well as accommodation.

Regarding our hypothesis, we can draw the following conclusions:

We discuss the results hereafter in more detail, following the original structure of the

hypotheses.

Duration of trip and travel composition

As proposed, both duration of trip and travel composition are significantly associated with

planning behaviour. Doubling of either the duration or the number of travel companions


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Table 1. Results of the regression analysis.

B SE Wald Df Sig. Exp( B)Change

in odds (%)

Duration of trip 2

0.093 0.008 129.495 1 0.000 0.911 2

8.9Number of members fromhousehold

20.180 0.085 4.488 1 0 .034 0.835 216.5

Income and consumptionHousehold income 0.000 0.000 11.385 1 0.001 1.000 0.0Total travel expenditure per person 20.001 0.000 28.350 1 0.000 0.999 20.1Total travel expenditure per personper day

0.001 0.001 4.830 1 0.028 1.001 0.1

Total travel expenditure per personper day in relation to householdincome

219.537 8 .069 5.862 1 0.015 0.000 2100.0

Importance of travel motivations

Diversion; see and experiencesomething new 0.126 0.046 7.377 1 0.007 1.134 13.4

Liberation from obligations(and relations)

0.134 0.045 8.764 1 0.003 1.143 14.3

Termination/conclusion of phasein one’s life

20.186 0.063 8.650 1 0 .003 0.830 217.0

Rest and relaxation 0.149 0.050 9.002 1 0.003 1.161 16.1Ability to make spontaneousdecisions

0.104 0.045 5.274 1 0.022 1.110 11.0

Enjoy nightlife 20.352 0.062 32.178 1 0.000 0.703 229.7Make contact with new people 20.224 0.056 16.026 1 0.000 0.799 220.1Prestigious character of trip 0.126 0.060 4.442 1 0.035 1.134 13.4Challenge and stimulate oneself 20.179 0.057 9.786 1 0 .002 0.836 216.4

Sports (active) 0.195 0.046 17.991 1 0.000 1.216 21.6Search for self-esteem 0.241 0.056 18.717 1 0.000 1.272 27.2Experience of adventure and evenrisk

0.128 0.052 5.958 1 0.015 1.136 13.6

Time for the family 20.174 0.044 16.054 1 0.000 0.840 216.0Time for oneself 20.141 0.044 10.478 1 0.001 0.868 213.2

Importance of sources of informationBrochures of destination(communal level)

20.125 0.063 3.906 1 0 .048 0.883 211.7

Accommodation guide of chain 0.177 0.088 4.104 1 0.043 1.194 19.4Advice from travel agency/railservice

0.228 0.057 15.973 1 0.000 1.257 25.7

URL from a hotel chain 2

0.140 0.067 4.375 1 0 .036 0.869 2

13.1URL from an airline 20.248 0.092 7.350 1 0 .007 0.780 222.0URL from a tour operator or travelagency

0.277 0.103 7.232 1 0.007 1.319 31.9

Travel guides/books/travelmagazines

0.292 0.054 29.534 1 0.000 1.339 33.9

Fairs and exhibitions 0.166 0.076 4.807 1 0.028 1.181 18.1Advice from friends and relatives 20.150 0.036 17.024 1 0.000 0.860 214.0Number of previous trips todestination

0.019 0.003 48.079 1 0.000 1.019 1.9

Means of transportation(reference ¼ car) 43.512 10 0.000

Train 2

0.329 0.141 5.455 1 0 .020 0.719 2

28.1Scheduled flight 20.900 0.361 6.207 1 0 .013 0.407 259.3Motorbike (or similar) 1.791 0.662 7.320 1 0.007 5.996 499.6


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extends the travel planning time frame ceteris paribus by 9% and 17% respectively. This

effect is quite modest when compared to others within the model, but nevertheless

important from an information economics perspective. In larger groups of tourists, a larger

amount of information must be processed, which, in turn, takes more time. This

information processing includes the registration and handling of different needs, as well as

dealing with perceived risks associated with a travel decision.

Income and travel expenditure

The level of income does not have any measurable effect on the travel planning

horizon. The same result is seen for travel expenses. The one exception is that

each doubling the income share allocated per travel day is also associated with a

doubling of the travel planning horizon. This result conflicts with previous research: it

Table 1 – continued

B SE Wald Df Sig. Exp( B)Change

in odds (%)

Bicycle (or similar) 1.528 0.555 7.576 1 0.006 4.611 361.1 Means of accommodation(reference ¼ not determined

54.241 17 0.000

Holiday home of friends andrelatives

1.230 0.594 4.285 1 0.038 3.420 242.1

Camping (tent, trailer, motor home,caravan)

21.828 0.855 4.573 1 0 .032 0.161 283.9

Constant 21.193 0.725 2.706 1 0 .010 0.303 269.68

Note: Positive signs denote a converse relationship with a short-term travel planning time frame (and vice versa).

Hypothesis 1. The longer the departure–return timeframe (trip duration), the longer the travel planningtime frame.

Supported.

Hypothesis 2. The higher the number of participatinghousehold members, the longer the travel planningtime frame for a trip.

Supported.

Hypothesis 3. The higher the household income, theshorter the travel planning time frame.

Not supported.

There is no measurable effect of income on theplanning time frame.

Hypothesis 4. The higher the type of terminaleducation, the shorter the travel planning time frame.

Not supported.

No type of terminal education tested in the modelpredicts the extent of the planning time frame. Thenon-significance of the additional Chi-square testsupports this hypothesis result.

Hypothesis 5. The higher the type of professionalposition, the shorter the travel planning time frame.

Not supported.

No type of professional position tested in the modelpredicts the extent of the planning time frame. Thenon-significance of the additional Chi-square testsupports this hypothesis result.

Hypothesis 6 . The shorter the travel planning time

frames, the higher the overall and per diem travelexpenditure.

Not supported with respect to overall travel

expenditure: the longer the planning timeframe, the smaller the overall travelexpenditure.


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signifies prudent economic behaviour, where spending higher shares of income is

associated with commensurate longer planning time frames. This result is associated

with the cultural peculiarities of the sample: the Swiss population in general is con-sidered quite conservative when it comes to spending, which, in turn, produces high

saving rates.

Core leisure pursuit

Of the 25 types of motivations tested, several are associated with short travel planning time

frames. These are (in decreasing order of coefficient): search for self-esteem, sports

(active), rest and relaxation, liberation from obligations (and relations), experience of

adventure and even risk , diversion/see and experience something new, prestigious

character of trip, and ability to make spontaneous decisions. In contrast, the following

motivations signify longer planning horizons (in ascending order of coefficient): enjoy

nightlife, make contact with new people, termination/conclusion of phase in one’s life,

challenge and stimulate oneself , time for the family, time for oneself .

Hypothesis (continued).

Supported regarding yearly travel expenditure: botheffects are only minimal.

Hypothesis 7 . The shorter the travel planning time

frames, the higher the overall and per diem incomeallocation for a given trip.

Not supported; actually the shorter the travel

planning time frame the smaller the yearlyincome allocation for a given trip.

Hypothesis 8. Travel motivations differ in depen-dence of the length of the travel planning time frame.

Supported.

Results discussed below. Hypothesis 9. The shorter the travel planning timeframe, the less important are sources of informationfor travel planning.

Not supported.

Some information sources become important withshort-term travel planning time frames. Detailsdiscussed below.

Hypothesis 10. The higher the number of previoustrips to a destination, the shorter the travel planningtime frame.

Supported.

Hypothesis 11. Means of transportation that requireadvance booking are associated with longer travelplanning time frames compared with means of transportation that do not need a booking.

Partially supported (for scheduled flights andtrains).

Hypothesis 12. Means of accommodation thatrequire advance booking are associated with longertravel planning time frames compared with means of accommodation that do not need a booking.

Not supported.

Also, the results do not reveal a clear pattern.However, and as the cross-tab and Chi-square testsreveal, hotels tend to generate long-term planning

time frames; whereas second homes and staying withfriends and relatives tend to be associated to short-term planning.

Hypothesis 13. The travel planning time frames of young people are shorter than those of older people.

Not supported.

There was no measurable effect of age on theplanning time frame. The non-significance of theadditional Chi-square test supports this result.


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In line with previous results relating to the size of the travel party, travel motives

linking a tourist to other people are less relevant to impulse travel. Conversely, we might

propose that motivations either associated with short-term/intensive experiences in

general, or representing a need that can be met with highly industrialized products (for

example, rest and relaxation) should lead to short-term decision-making.

Information sourcing

Of the 28 sources of information tested, several are associated with short travel planning

time frames: travel guides/books/magazines, URL from a tour operator or travel agency,

advice from travel agency/rail service, accommodation guide of chain, and fairs and

exhibitions. In addition, a high number of previous trips to a destination also signify a short

travel planning time frame. The following sources of information are associated with

longer planning horizons (in ascending order of coefficient): URL from an airline, advice

from friends and relatives, URL from a hotel chain, and printed brochures of the

destination (communal level).The composition of the above information sources somewhat mirror the short-term

booking behaviour of commercially organized travel and the information need related to

it. A person’s own travel experience may substitute commercial support, explaining why

this internal source is also associated to short travel planning time frames. In contrast, a

person’s own information sourcing (and possibly booking activities) requires more

planning time, explaining why the use of URLs and more static sources of information

(such as friends and relatives) as well as printed brochures can be associated with a more

extensive travel planning time frame. In addition, printed and more generic and static

information can serve as a kind of database, on which to base specific travel needs and

subsequent travel decisions (and similarities exist with the concept of the latent comparedto the activated decision set).

From the above discussion, we can conclude that even very short-term travelling

is associated with a minimum of planning and information sourcing. It has to be

concluded, therefore, that pure impulse purchasing as defined by Stern (1962) does not

occur in tourism because the case of total lack of preplanning of any kind is extremely rare.

Choice of transportation to and accommodation at the destination

As proposed in our hypotheses, the use of means of transport that require bookings is

associated with extended travel planning time frames. This does not only include flights

and trains for international traffic, but also motor homes (see “types of accommodation”).In contrast, means of transportation that do not require reservations, and that normally

would be used in favourable climatic/weather conditions (such as motorbikes and

bicycles), are associated with short travel planning time frames. Interestingly, the latter

two means of transport have the highest model coefficients, which also indicate the

potential overriding effect of weather on travel decisions.

The choice of means of accommodation does not contribute to the explanation of

travel planning time frames.

Age

Results reported in previous studies are not confirmed. This is probably because of the

trade-off between available time and income, which is more crucial for the product

category “travel” than for other product categories.


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Conclusion and implications

The key question of this study was how impulse purchasing in tourism can be defined, it at

all it exists.

We define impulse purchase in tourism as planned impulse purchasing with a

maximum of one week between the decision (on at least one core travel portfolio element)to take a trip and the departure. Analysis of a data-set representative of the Swiss

population indicates that, in a mature travel market, impulse-type purchasing in tourism

appears to exist, with approximately 14% of trips complying with the above definition.

Such impulse purchases can be characterized as follows: they are typically short trips

to familiar destinations, which are the likely reason that only commercial or internal

sources of information are of importance (and this aligns with the literature). In terms of

the core leisure pursuit, impulse purchases in tourism are associated with rather

individualistic travel motivations. However, contrary to impulse purchasing in retail,

impulse purchasing in tourism does not necessarily lead to non-economic behaviour:

travel expenses (in absolute terms as well as in terms of how much income is allocated fora trip) tend to be quite prudent, and only increase when the planning horizon is expanded

too. Furthermore, and also contrary to our understanding of impulse purchasing in the

retail context, it is not the young, very well educated people in top positions who can

“afford” to engage in impulse purchasing. Rather, it is a person’s degree of freedom to

make autonomous time decisions in the first place, which, in turn, is influenced by the

quantity (time) of compulsory interaction (either professionally or privately) associated

with impulse purchasing in tourism. The need for coordinating time allocation between

members of social groups thus seems to be one of the key factors determining the degree of

impulsiveness of a travel decision. This can also be proposed from the fact that with an

increasing number of participating travel companions, the travel planning time frame alsoincreases. Therefore, future research could focus on the external environment/setting of

travel planning and the social context in which travel decisions are made.

The present study has some major implications for the tourism industry. The character

of some of the impulse trips offers several business opportunities for the travel industry.

These mainly comprise short trips to unfamiliar destinations, which require an effective

and efficient sourcing of information, and often a commercial type of travel planning and

production. However, one has to be aware of the expense prudence of such tourists,

because they are unlikely to be big spenders, although they might be in the position to

“splash out” (considering their age and professional position). Consequently, the travel

industry should provide travel offers that give tourists a short-term first glimpse of either a

destination, a travel type, a set of activities, or combinations hereof. Travel providers

could put up such offers as a series of different weekend promotions for more or less

independent people (such as singles). Thus, they could attract interest in the first place and

meet the increased demand of fragmented holiday bits and pieces.

Three obvious directions for extending this work emerge: (1) extending the scope of

decision-making towards not only looking at pre-departure decisions, but also at decisions

made during the trip; (2) extending the scope of the factors potentially influencing the time

frame of any decision-making before departure or during the trip (including gender effects,

impact of independent singles, and shopping related travel motives); and (3) testing for the

sensitivity of our arbitrary threshold (one week) to test potential impulse behaviour versus

non-impulse behaviour.The study has several limitations. For survey technical reasons, persons in collective

households were not registered. Small children and persons older than 80 were


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under-represented. Most foreign citizens in the survey came from countries neighbouring

Switzerland. In addition, trips with a regular and homogeneous repetition rate (for

example, to their own holiday homes) were under-represented. However, because of the

large sample used in this study, those limitations are not serious.

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