marketing management and tourism

MARKETING MANAGEMENT AND TOURISM

Roger J. Calantone Michigan State University, USA

Josef A. Mazanec Wirtschaftsuniversitat. Austria

Abstract: Tourism services are generally provided by various business and government organizations. To the greatest extent, they provide services to the traveling public. The marketing and management of these services exchanges are the thrust of this paper. This paper focuses on the management and information analysis tasks of these organizations within a marketing context. An overview of the fit with management literature philosophies is provided at rhe macro-level, while at the micro-level the paper pursues marketing science and marketing research contexts for tourism research. The service encounter, its conduct, direction. and information needs are emphasized. Keywords: tourism, marketing. management, marketing research, marketing science, services, exchanges.

RCsum6: La gestion du marketing et le tourisme. Les services du tourisme sent fournis en g&&al par differentes organisations commerciales ou gouvernementales. Dans la plus grande mesure. elles fournissent ces services au public qui voyage. cidbe rnairresse du prGsent article est la com- mercialisation et la gestion de ces &hang-es de services. L’article Porte surtout sur les tlches de I’analyse de l’information et de la gestion de ces organisations dans le contexte du marketing. Une vue d’ensemble de la faGon dont la gestion du rourisme s’accorde avec les philosophies de la 1ittPrature de la gestion est prtsentee sur le plan macro, tandis que sur le plan micro l’article traite des contestes de la science du marketing et de la recherche en markering. On souligne le rencontre du service, son exCcu- tion, sa direction et ses besoins d’information. Mots-cl&: tourisme, marketing, gestion, recherche en marketing. science du marketing, services, &changes.

INTRODUCTION

Virtually every time people participate in an organized effort or receive the benefits of an organized effort, a manager of some sort is involved in achieving that result. “Managers are ultimately responsible for the achievement of results through the specialized efforts of other

Roger Calantone is Professor of Marketing at Michigan State University (East Lansing ?rlI 48824). His research interests are primarily in market segmentation, technological product innovation. and quantitative analysis applied to tourism and new product decision making. Josef Mazanec is at Wirtschaftsuniversitit Wien and is Director of the Institute fur Fremdenverkehr. His research spans marketing science, marketing strategies, as well as involvement in many national longitudinal tourism studies and the development of expert systems in tourism.

101

IO? MARKETING MANAGEMENT AND TOURIShI

people, whether individually, in groups, or in organizations” (Ivan- cevich, Donnelly and Gibson, 1989). The president of an airline is a manager, as are a college dean, the director of a tour group, the bell captain at a hotel and a football coach. Management is the process undertaken by individuals to coordinate the actions of others to achieve that which they could not achieve alone. It is the process and tools of marketing management and its relation to tourism that is presented here.

The study of management has evolved quite rapidly and dramatical- ly over the last several decades. This has been accomplished by a heightened interest and awareness of management as an area worthy of scholarly treatment. Two very pragmatic reasons stand out. First, the society requires the outputs of specialized organizations and institutions to provide various goods and services, products, and processes. Organizations and institutions, whether privately-owned or state-run, are directed by managers and guided by their pohcy decisions. Manag- ers determine which services are offered to tourists, which attractions are built, how goods and services are priced, and who will do the work and how. Managers decide the who, what, where, when, how much, and many other aspects of the supply-side of the tourism exchange. It is their calibration of the service delivery system with the wants and needs of tourists that provide satisfaction and efficiency in that exchange relationship. If these reasons alone are insufficient justification for the study of management in tourism, one needs only notice that many who manage were never trained as managers. Chefs manage restaurants or at least kitchen staffs, physicians manage hospitals, teachers manager schools, ticket agents manage large airline ground service staffs, and so on. Tourism organizations need managers.

There are three well-established approaches to the study of management: the classical approach, the behavioral approach, and the management science approach. These have evolved historically, but later approaches were built on earlier approaches without replacing them. Furthermore, each approach has continued to evolve to some degree. Some merging has occurred in academe through the systems and con- tingency approaches. However, these latter distinctions are more for understanding and macro-synthesis, rather than for real effect within managerial practice, and little has crept over to tourism.

The classical approach aims principally at the management of work, production, and work methods. Furthermore, studies of the management of organizations showed differences from the management of work. The classical approach involved a study of the critical management processes of Planning (deciding what to do), organizing (turning plans into action), and controlling (do the actions, match the plans and

’ objectives of organizations). The behavioral approach focuses on helping managers in managing

people. In the marketing function, this creates a parallel interest in analyzing the consumer or buyer. The behavioral approach uses concepts, constructs, and methodologies from anthropology, sociology, psychology, and other behavioral science areas to help managers understand human behavior in work and consumption.

The management science approach uses numerous mathematical

CALANTONE AND MAZANEC 10.1

and statistical tools to solve problems abstractly in an efficient manner and to translate the solutions developed through these tools to good practical management solutions. The concentration has been more on computer assistance to managers through Decision Support Systems (DSS) and Expert Systems (ES), where mathematical abstractions give way to decision support or even artificial intelligence assistance to managers in real time decision situations.

As sophistication of applications evolves, one finds the literature is becoming more heavily weighted toward behavioral science and management science approaches in tourism. This parallels the evolution of the literature in the applied general management, marketing, and policy studies. The primary thrust of the authors’ own work has been in the management science area and, thus, they present some tools in sufficient detail to permit speculation on applications in real management/ marketing situations. Various functional subdivisions of management occur in real tourism situations-consumer behavior, advertising, market planning, and the like. They have organized subsections which represent those areas and research work in tourism which appears in sufficient degree to permit reasonable discussion of these topics.

Tourism is an exchange process, an experience which has value to the tourist. Where other people contribute to this experience, the exchange usually occurs between the tourist and a business. This business may be a huge state-owned airline, like Aeroflot, or a simple one-person seasonal wurstel stand. The management of the business can enhance or destroy the value of the tourism experience. The two important management tasks are managing people and managing information. This paper briefly discusses the philosophy of managing people in the tourism service exchange and then presents the tools of the information trade on the demand-side of the tourism experience; knowing who the tourist is, what she or he wants, and the management of expectations (usually known as advertising). The paper begins by discussing the philosophy of managing the tourism service delivery system.

Peak Performance Delivery in Services

Tourism is a service, thus delivery of peak performance is critical to its success. “Although the performance of most services is supported by tangibles, the essence of which is bought is performance rendered by one party for another” (Berry 1984:29). The importance of the human impact in service marketing is emphasized by Czepiel, Solomon and Surprenant (1985:3) h w o stated that “to study the service encounter is to study the behavior of human beings interacting.” Thus, tourism marketers, like other service marketers, must strive to bring high service levels to their customers. A good way to begin searching for ways to improve delivery of a service is to understand how services differ from goods.

Zeithaml, Parasuraman and Berry (1985) described four ways in which services are different from goods: intangibility, inseparability of production and consumption, variability in performance, and perish- ability. Services are intangible in that they are not measurable or objec- tively definable. The output of a service (such as operating a tour

104 LIARKETING MANAGEMENT AND TOL’RIS.LI

destination) is more abstract. With services, production and consumption are inseparable. This can be taken to mean that a service, unlike a product, usually requires a certain degree of closeness between produc- er and consumer-the provider is not unknown to the customer. A rude tour bus operator or hotel receptionist is directly confronted by the tourist, sometimes with unfortunate results. Since the human element is so important in the delivery of services, differences in personality. training, or situational circumstances may lead to vrariability in the performance of the service. A major challenge in designing services is standardization and quality control (Bitner, Nyquist and Booms 1985; Uttal 1987). Finally, services are perishable in that they cannot be stored or inventoried (Mills 1986). This implies that consumption is immediate, and that services not used (such as unsold airline seats or unbooked hotel rooms) are lost forever.

The service encounter is the “fundamental framework through which resources are exchanged between the service organization and its envi- ronment” (Mills 1986:6). The firm, the employee, and the customer have mutual expectations for “performance criteria on which parties are evaluated and [for] the kinds of payoffs they can expect” (Mills 1986; see also Czepiel, Solomon, Surprenant and Gutman 1985; and the discussion of transactional analysis by Cohen and Dann in this issue). Tourism is a good example of a high-contact service in which the provider acts somewhat like a consumer advocate (Surprenant and Solomon 1987). This implies that real differences exist in the treatment of different customers and, furthermore, that role expectations are probably well understood by all participants.

High service quality, is an important element of peak performance, and it must be recognized that service quality evaluation is multifac- eted. Both the process and the outcome of the services are evaluated (Parasuraman, Zeithal and Berry 1985). Gronroos (1982) provides the most useful distinction between components of quality evaluation. He maintains that it is composed of technical quality (what the customer observes in the actual delivery of the service) and functional quality (how the service is deli\rered). These both contribute to a global quality evaluation. This has obvious use in a tourism setting. A hotel manager or tour organizer may have a product which has high technical quality in that it delivrers the benefits sought by the customer; yet the global quality evaluation may be compromised if employee attitudes and behaviors, appearances. and service-mindedness (components of functional quality) are poor. Such bad experiences may engender such negative word-of-mouth that the high technical quality of the service provided is overshadowed.

ANALYSIS FOR STRATEGIC MARKET PLANNING

Strategic market planning (Abel1 and Hammond 1979; Day 1977, 1984) and, particularly, the analytical steps preceding the formulation of strategies and actions represent a typical domain of marketing thought not yet fully utilized in tourism management. The purpose of this section, therefore, is to demonstrate that the most widely used methods of strategic evaluation techniques (known as portfolio models)

CALANTONE AND MAZANEC 10.5

are adaptable to management conditions even in a tourist non-profit organization. A company is viewed as a portfolio of individual businesses or products and brands (Hedley 1977:9). The simplest portfolio model (the growth-share matrix) employs market growth rate, relative market share (compared to the toughest competitor), and importance value (contribution to overall sales) as three assessment criteria for products (Day 1986: 168ff; McNamee 1985: 13Off).

Portfolio Analysis Applied to Tourist Destinations

Strategic market planning in a national tourist office entails one crucial decision to be taken annually. A destination’s portfolio consists of a mixture of guest segments from various generating countries and management has to decide on how much effort should be directed towards these markets. An assessment of a destination’s competitive position vis-ci-vis its competitors assists in designing strategies in a sys- tematic manner. In the subsequent example, a national tourist office (NTO) evaluates the strategic market positions of two receiving countries: Austria and Italy. Evaluation criteria are market growth rate (percent variation of the relevant market volume comprising the total number of bednights sold by the 9 leading European receiving countries to the 19 leading generating countries in the world during one calendar year), relative market share (share of bednights sold by one particular receiving country in the bednight total bought by a generating country divided by the share of bednights reached by the largest competitor), and importance value (proportion of bednights sold to a particular generating country in the bednight total of guests recorded in a receiving country).

Table 1 exhibits the data for the major selected tourism generators in 1988 and Figures 1 and 2 portray the evaluation criteria along the vertical axis (growth rate), the horizontal axis (relative share), and through the diameter of the country circles (importance value). The NT0 management may easily exploit the information diagrammed by answering questions such as: Which country was more successful in tackling the growth markets? Is the portfolio rather one-sided or rea- sonably. diversified? (A single dominant circle like Germany in the Australian portfolio indicates an unbalanced mixture of guest nations). Which receiving country has a dominant position in generating market? Market dominance is diagnosed from country circles situated in the first or fourth quadrant (right of the origin). It may reveal a competitive advantage by achieving economies of scale in market opera- tion.

One of the major criticisms brought forward against the growth- share matrix refers to the limited number of evaluation criteria utilized. Additional information of a more qualitative nature is excluded from the evaluation process or must be introduced separately. Another family of portfolio techniques to overcome the restriction in the number of assessment criteria is widely known as Industry Attractiveness Analysis (IAA). Each of these “multifactor portfolio models” (Day 1986:194ff) constructs two evaluative aspects named market attractiveness (or business sector prospects) and competitive position (Day 1986: 198; McNamee 1985:145ff) by integrating a discretionary number of factors into a

Tab

le

1.

Por

tfol

ios

of A

ust

ria

and

It

aly

in

1988

BE

L

+

Gcn

crat

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Cou

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FR

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U

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R

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me,

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mn.

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dnig

hts

232.

0 50

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108.

3 45

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26.9

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.7

19.9

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%

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ustr

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rn

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t sh

are

in

%

24.2

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2.9

6.6

9.3

4.7

10.0

7.

0 -

=:

Aus

tria

’s

rela

tive

shar

et~

1.17

0.

98

0.08

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19

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0.

16

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13

0.46

0.

30

- z

(Tou

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Impo

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%

65

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1

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2.7

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%

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6 9.

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10.8

3i

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0.86

0.

42

0.12

0.

53

0.21

0.

21

1.35

-

0.55

0.

47

1 .44

(T

ough

est

com

petit

or)

(AU

S)

(FR

A)

(ES

P)

(GH

R)

(GH

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(FR

A)

(FR

A)

(GR

R)

(FR

A)

(YU

C;)

Impo

rtan

ce

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e in

%

r 45

.1

3.7

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5.0

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6.7

_ 1

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6. ‘1

Com

pris

es

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ight

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th

e 9

maj

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, FR

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, G

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, IT

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’ (d

omes

tic-

tour

ism

cx

clud

ctl)

.

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pare

d to

st

rong

est

com

petit

or

(nam

ed

in

pare

nthe

ses)

.

‘Prr

cent

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ntri

butio

n to

to

tal

hedn

ighr

s re

cord

ed

in

Aus

tria

/Ita

ly

(cor

resp

onds

to

dia

mct

cr

oft

it-cl

cs

in

Figu

re

1).

CALANTONE AND MAZANEC 107

3 5

11 Austr’c

relative market share

Figure 1. Portfolio of Italy 1988 (Area of Circle = Importance Value)

summary judgment. A simple scoring model or more advanced processing methods of multiattribute decision-making (e.g., Mazanec 1986a: 10-17) may serve this purpose. A very illustrative sample study for the tourist destination of New Zealand has already appeared (Hen- shall and Roberts 1985). The authors merged factors such as market size and growth rate, domestic/international expenditure ratio, dispos- able income per capita, and so forth, to depict market attractiveness of tourism generators, and selected cost of transport, exchange rate, quality of tourism services provided, among others, to establish New Zealand’s competitive position.

One should not forget to emphasize that there are several other portfolio models offered in the management and marketing science literature. It may puzzle the naive user that different models sometimes

growth rate

10

5

0

(5)

1 F R Germany

2 Netherlands

3. UnIted Kingdom

4. France

5. USA

6. Benelux

7 Switzerland

8 Italy

9 Sweden

10 Denmark

5 4

(‘O&,05 0.1 0.2 0.5 1 2 5 10

relative market share

Figure 2. Portfolio of Austria (Area of Circle = Importance Value)

108 MARKETING MANAGEMENT AND TOCRIShl

arrive at different recommendations if the “textbook” recipes are ob- served (Wind, Mahajan and Swire 1983). It is imperative, however, that the manager in tourism, like his or her colleagues in other industries, learns to look at tourist services as part of a portfolio in order to pinpoint his strategic position.

Portjoolio Analysis Applied to Restaurant Management

At first glance, the variety of menu items offered by a restaurant seems to be a prototype task for portfolio considerations. Hospitalit!. management, however, has its idiosyncrasies pertaining to the products it deals with. Since market volume figures (namely, the number of portions of a menu item sold in a market area during the planning period) are practically inaccessible, both axes suspending the “portfolio space” have to be redefined. Smith (1983) discussed an appropriate adaptation: Market growth is replaced by the menu mix percentage. which relates each menu item’s sales to the sales total of the restaurant. Rela- tive market share also gets transformed into the “internal” evaluation criterion of item contribution. In spite of being substantially altered, the diagnosis still preserves a remainder of market response: The menu mix percentage at least covers the aspect of populari<p of a menu item among the customers patronizing the restaurant.

The populariy/contribution approach was extended by Pavesic (1983) who introduced the third evaluative factor of food cost. In order to adhere to a two-dimensional portfolio matrix, the authors of this paper compounded item sales and item contribution into the single variable of weighted contribution (item contribution multiplied by number of items sold). It may not be too surprising that strategic implications suggested by the Smith and Pavesic approaches can deviate from each other (keep vs. delete an item, etc.).

Marketing Planning

Tourism is one of the last industries to experience the change from seller’s to a buyer’s market, Marketing techniques, therefore, are still less advanced than those in the branded goods industries, where managers have been accustomed to a fastidious and discriminating customer for many years. Marketing action aims at influencing customers. Such action is bound to be inefficient, unless management takes pre- paratory steps in choosing a suitable explanatory model of the travel decision process, and developing a strategic plan prior to action planning.

An excellent state-of-the-art overview of behavioral models applicable to tourism is presented by Moutinho (1987). It deals with the micro-approach modeling tourist behavior on the individual level (Pearce and Stringer, this issue, for several interesting concepts to mea- sure the cognitive level of the tourism act). The manager monitoring tourist market response on a disaggregate level observes variables such as attitu&. image, perceiued risk, cognitive dissonance, etc. Normally, one of‘ these \.ariables accounts for most of the explanatory power in a particular behavioral model. Managers, therefore, must be provided guidance on how to opt for one of several rivalling models (Mazanec 1989). As

CALANTONE AND MAZANEC 1 O!)

Nash and Smith (in this issue) point out, anthropologists dealing with the tourist-host encounter can generate useful recommendations on how to adapt from the managerial perspective. Although the anthropo- logical concern is mostly “macro-level” from a manager’s point of view-such a perspective is necessary to map possible adaptations in the long run. Once a micro-model is identified, it greatly assists in streamlining the entire planning process.

Product Positioning

Strategic marketing planning involves decision-making in two major areas: product positioning and market segmentation. Positioning refers to detecting or developing product attributes which are expected to establish a competitive advantage and, therefore, may be transformed into valu- able arguments and appeals in advertising and personal selling. Sup- pose a tourism manager is in charge of strategic marketing planning for a destination. He has already decided to model tourist product evaluation in terms of image formation. Under the image paradigm, the connotative and emotional criteria associated with tourist destinations are assumed to prevail due to the lack of factual knowledge. (This may be typical for inexperienced travelers or in the early stages of a travel decision process.) Since image measurement demands a multidimensional representation, data techniques, such as Multidimensional Scal- ing, Principal Components or Factor Analysis, and Correspondence Analysis, may be used (for examples refer to Fenton and Pearce 1988; Morucci 1980; Perry 1975; Lewis 1985 presents a sample study in hospitality management).

There are numerous variations of positioning models, behavioral ones (other explanatory constructs), representational ones (adding “ide- al points” to make preference explicit), and algorithmic ones (metric vs. nonmetric procedures). The reader interested in more detailed information is referred to Myers and Tauber (1977).

Martkt Segmentation

The second domain of strategic marketing planning is market segmentation. Management may face either of two situations. The first one is “a pTio?i segmentation” (Smith 1989:46; “criterion segmentation” according to Bagozzi 1986:229). This is when a criterion variable for splitting up a global market is known in advance (imagine a large tour operator entering a new travel market where it is feasible to differenti- ate travelers from non-travelers and package tourists from individual travelers). The second is “a postmori segmentation” (or “factor-cluster segmentation” Smith 1989:46; or “similarity segmentation” Bagozzi 1986:229). This is when the management has no prior knowledge about partitions in the market. It is likely, however, that traveler segments due to differences in motives, attitudes, activities, etc., exist, but they are still unknown.

A priori segmentation compels management to search for additional characteristics typical for travelers vs. non-travelers, package vs. individual tourists, etc., in order to pave the way for selective market action. A posteriori segmentation requires detecting the “psychological”

110 M,IRKETING MANAGERfENT AND TOURISM

or behavioral subgroups at first and seeking further concomitant variables afterwards. The marketing science toolkit again offers various methods to tackle both problems. The Automatic Zntmzction Detector (AID). a convenient exploratory method for a priori segmentation, and a clustering procedure for a posteriori segmentation are presented in Vavrik and Mazanec (1990) with extensive use of tourism case material.

A posteriori segmentation very often employs attitudinal or benefit segmentation; that is, aggregation of the individuals of the market into groups (“segments”) that have similar attitudes or seek similar benefits when choosing a travel destination or tourism service. This kind of analysis is useful, as the tourism manager is likely to be interested in determining which groups or segments would support a given product category; how the segments differ in their responsiveness to a range of offerings (brands, destinations, etc.) within that category:; and how they differ in their expectations. The manager can use this information in developing advertising and promotion programs which will be most effective; choosing appropriate media vehicles; and deciding on required marketing expenditures and allocations (Fitzgibbon 1987).

Psychographics (Plog 1987) are an intuitively appealing way to segment a market. Schewe and Calantone (1978) provide an example of a psychographic segmentation of out-of-state visitors to Massachusetts. They elicited attitudes, interests, and opinions (AIO) information from their sample and showed that visitors to Cape Cod had a different psychographic profile than visitors elsewhere in the state. Similarly, business travelers differed psychographically from pleasure travelers. These observations, coupled with demographic information, can be very useful in developing advertising and promotion copy.

Benefit segmentation is also a useful method. Calantone, Schewe and Allen (1980) d escribed the steps of this kind of segmentation. Using pre\ious studies, expert judgment, and input from respondents, a set of relevant attributes is derived. Respondents’ assessments of the relative importance of each attribute are obtained through questionnaires, and cluster analysis is used to group together individuals with similar importance ratmgs. Thus, the resulting clusters represent groups of individuals that all look for about the same “bundle” of benefits when choosing a destination or tourism service. Calantone et al (1980) then performed a benefit segmentation of tourists in Massa- chusetts and showed that five segments existed: frequent visitors, sight- seers, sports/relaxation seekers, nature buffs, and others (mostly one- day visitors or “drive-through?). In an extension of this study, Calantone and Johar (1984) h s owed that the benefits sought varied by season-summer travelers look for different attributes in their vacation destinations than did winter travelers.

Benefit segmentation has proven to be one of the most often used methods in tourism. Goodrich (1980) segmented American international travelers; Mazanec (1984), and Young, Ott and Feigin (1978) studied American tourists in Canada. This latter study revealed six different benefit/activities. A similar method is segmentation by activity packages (Graham and Wall 1978). These authors provided an example of Americans traveling in Canada. They identified which visi-

CALANTONE .4ND MAZANEC 111

tors took part in each activity package, and determined socioeconomic attributes of participants in each segment.

CONSUMER BEHAVIOR

How should a tourism manager begin to improve his or her decision making? A logical way to begin is by investigating consumer needs, attitudes, and decision processes. Marketing researchers have developed models of consumer behavior which provide insights as to why consumers do what they do. Such insights can be translated into ac- tionable marketing strategies and programs by management. Before moving to a discussion of the strategic implications in tourism management, a brief overview of consumer behavior models is required.

Mazanec (1989:63) defined models as “systems of hypotheses relating one or more dependent variables . . to several independent variables.” In a tourism context, dependent variables might be choice of a tourist destination or hotel, while independent variables could include such factors as behavioral intentions, comprehension or perceptions of alternatives, consumer motives, and so on. He differentiated between stochastic, econometric, structural, and simulation models of consumer behavior. Stochastic models depict loyalty and switching among alternatives. A tourism director might want to know the probability that a first-time visitor will choose another destination next time. Econ- ometric models show how aggregate response variables (such as sales volume or attendance levels) are related to one or several stimuli (such as oil prices, advertising, or the opening of new attractions). Structural models usually aim at understanding the processes and relationships at the individual (micro) level. Simulation models are specifically designed to help managers answer “what-if” type questions; usually, these are computer aided for fast execution. One interesting behavior model in the tourism literature is that of Woodside and Carr (1988) who postulated, and tested empirically, the model that awareness of destinations and high preference levels tend to lead to higher probability of choice. Their study is a clear example of the need to understand the process by which consumers make tourism-related decisions. (For an especially good discussion of models and simulations in tourism research, see Rovelstad 1987.) Sociologists have similar models relating to the resort-cycle (see Cohen and Dann in this issue), as well as geographers (Mitchell and Murphy in this issue).

Many consumer behavior models in tourism use psychographics to explain underlying motivation for travel (Plog 1987). Psychographic or personality-based research is designed to look under the surface characteristics (demographics like age, sex, income, home state, or country) to investigate the personality underneath, usually by means of a questionnaire instrument eliciting AI0 information. Again, anthropologists can lend support to inquiries of host-guest encounters and provide insight into the adaptation behaviors on both sides (Nash and Smith in this issue). Psychographic research can be used to support such tourism decisions as how to develop destinations and support services, how to position a tourism service to target segments of the population, how to advertise, promote and package the product, and so on (Plog 1987).

112 LIARKETING hIAN.L\GEhlEST AND TOURISXI

Similarly, psychologists and sociologists do basic research into the use of social-psychological attitudes at this level (articles by Pearce and Stringer, and Cohen and Dann in this issue). Plog (1987) provides an excellent historical perspective on psychographics and pursues a practical discussion of how to do psychographic tourism research. In a related vein, Pizam and Calantone (1987) suggested that the ,410s of questionnaire respondents are all related to their values. They use value scales in place of psychographic scales and had reasonable success in predicting travel behavior. Thus, value analysis can complement psy;- chographic analysis in tourism research. The psychology article in this issue provides an interesting critique of the uses of motivational studies. For example, the “escapism” motivation can manifest itself in man\. ways other than touristic pursuit.

In addition to psychographic and other descriptors. a questionnaire can be used to elicit perceptions on salient attributes for a set of alternatives (brands, destinations, hotel chains. etc.). These perceptions can be represented as a perceptual map which is useful in managerial planning. Goodrich (1978) used MDSCAL (a program for multidimensional scaling) to obtain a two-dimensional positioning map representing consumer perceptions of nine warm-climate tourist destinations on ten attributes (scenic beauty, shopping facilities. entertain- ment, etc.). He found that images of Caribbean destinations were \rer)r similar to each other, while different from California, Mexico, Hawaii. and Florida. Calantone, di Benedetto, Hakam and Bqjanic (1989) used correspondence analysis (another applicable data handling technique) to compare perceptions of various Pacific Rim destinations, as perceived by tourists from different origins (Britain, America, Japan. etc.). They discovered that people from different origins differed mark- edly in both their perceptions of individual destinations. and also in what they looked for when choosing tour destinations.

Forecasting Beharior

Another key ingredient to tourism planning and decision-making is obtaining accurate demand forecasts. Conscientious forecasting can reduce chances of over- or underestimation of demand. Overly-opti- mistic demand forecasts may result in unrecoverable losses and undul! high promotional costs, while underestimation of demand results in undersized tourist attractions, preventing the area from reaching the full economic benefit it could have attained (Calantonc. di Benedetto and Bqjanic 1987, 1988).

Several overviews of tourism forecasting have appeared recently (Archer 1987; Calantone, di Benedetto and Bojanic 1987; Sheldon and Var 1985; Uysal and Crompton 1985), while a useful classification of’ methods is provided by Van Doorn (1984). Exploratory forecasting, the most common kind in tourism forecasting, extrapolates trends and identifies relationships between variables to predict future levels of some dependent variables to predict future levels of some dependent \.ariables like monthly attendance. Usually, time-series, regression, or gra\rity models, are used in exploratory forecasting,.

A time-series model of tourism attendance will identify factors such

CALANTONE .4ND MAZANEC 113

as seasonality, cyclical effects, and underlying trends that appear to cause changes in levels of visitors (Ansari 1971), while advanced time- series models are available for complex problems (Baron 1973: Geurts and Ibrahim 1975). A regression model may relate tourism attendance to several explanatory variables and determine the extent of the relationship. More advanced techniques are available for use with more complex tourism problems and are exhaustively listed in the above referenced review articles. Gravitv models are based on the physical law that the closer and more massive two objects are, the more attraction they have for each other. In a tourism framework, a gravity model depicts tourism demand or flow as a function of distance traveled, cost, income levels, and perhaps other variables. For examples of the classic gravity model, extensions, and criticism see Durden and Silberman (1975), Wolfe (1972) Smith and Brown (1981), Mayo, Jarvis and Xan- der 1988; for more information on all techniques, see Archer (1987).

Exploratory approaches to forecasting are generally useful for the short-term only (two years or less) (Makridakis and Wheelwright 1979). For longer-term forecasts, speculative approaches are more appropriate. As a rule, these rely on the expertise and knowledge of tourism professionals and can be used to complement the shorter-term forecasts based on historical precedent. In tourism, speculative approaches include Delphi modeling, GSV modeling, scenario writing, and the nominal group technique.

In the Delphi technique, tourism experts are identified and sent questionnaires eliciting their opinions (over several rounds) on the like- lihood of certain events or situations taking place in the future. The Delphi has been used to determine the likely impact of such trends as increased leisure time or changing women’s roles on tourism demand (\-a, 1984). The GSV ( named for Gearing, Swart and Var 1976) technique relies on experts to provide evaluations of alternative attractions on a set of predetermined criteria. Scenario writing requires experts to identify possible future tourism “images” (baseline, better than expected, worse than expected) and paths that might lead to each future image (political and economic climate, extent of advertising, frequency of au- flights, etc.). Baron applies GSV to long-term forecasting of tourism to Thailand (1979) and Israel (1983). Alternatively, the nominal group technique (NGT) may be used (Herbert and Yost 1979; Ritchie 1987). NGT is a controlled group discussion in which members reflect individually on certain discussion topics, share their views, then consolidate and (eventually) compile aggregate results.

PRODUCT DEVELOPMENT

Understanding customer wants, needs, and perceptions is useful in making other managerial decisions as well-for example, what to build into a tourist attraction, what services to include, and what prices to charge. Clearly, an understanding of benefits sought can be useful to the tourism planner deciding how to develop a new tourist attraction; so could an understanding of how target consumers perceive competing tourism offerings. To avoid being repetitious, these methodologies will

114 MAKKETING LIANAGEMENT .4ND TOLRIShl

not be further commented on here. Rather, this section will discuss another methodology with particular application to the product development decision: conjoint analysis.

Conjoint analysis is starting to gain popularity in tourism-related applications. It is designed to evaluate the relative importance individuals place on various components of a product or service (Bojanic and Calantone 1990; Claxton 1987). S ome individuals may place more importance on speed for travel, for example, and others on low cost. When faced with the choice between traveling by local bus. express bus, or helicopter, then, the individual must make a tradeoff between these various modes, depending upon the relative importances of the attributes (indeed, conjoint analysis is often called “tradeoff analysis”) (Claxton 1987). In a typical conjoint analysis, an individual may be required to rank-order alternatives on several attributes: cards describ- ing the alternatives may be used to facilitate the task (usually about twenty or thirty representative alternatives are provided). A computer program, MONANOVA, is used to translate the rank orders into “part-worth utilities,” which indicate which attributes were preferred by the individual. Thus, the manager can determine what combination of features are preferred by the target market, and can design the product offering accordingly. Claxton (1987) summarizes the results of a number of applications of conjoint analysis. One studv of air services by Air Canada showed the relative importance of particular services to air travelers. Baggage handling was seen as more important than in-flight snacks or newspapers, so it ought to have received more attention.

This is an appropriate place to mention that the decision-maker need not reinvent the wheel every time a product, advertising, or other decision is made. Much excellent secondarv data are available to the tourism professional. An Information Serv’ices catalog, published by the University of Colorado and Travel and Tourism Research Associa- tion, is available (Goeldner and Dicke 1980), and is a good starting point.

Advertising

It is clear from the above that knowledge of benefit segments can be of great help in developing advertising or promotional plans for tourist attractions and services. In the Calantone, Schewe and Allen (1980) study. five benefit segments were identified. A tour operator, for example, could decide which segment was the most appropriate to pursue (i.e., there was a good match between benefit sought by segment and benefit offered by tour; the segment was large enough to be worthwhile pursuing). Then, the operator could develop an advertising campaign around these benefits. Benefit or psychographic segmentation (Schewe and Calantone 1978) are especially powerful when combined with demographic information, which can help the manager choose specific media vehicles that reach the desired benefit segments.

Benefit segments are not stable and may change through time (Ca- lantone and Sawyer 1978). This implies that advertising copy and/or vehicles may have to be reviewed occasionally to check if they are still

CALANTONE AND MAZANEC 115

appropriate. The fact that benefits can change from season to season (Calantone and Johar 1984) may also imply that advertising copy

ought to be varied by season. Advertising funding and allocation decisions are among the most

difficult problems faced by national departments of tourism. Mazanec (1986b, 1986c) has proposed decision support systems based on managerial judgment to help solve these problems. These systems require, as input, judgments on the relative importance of factors determining country market shares. Advertising policies can then be optimized by considering each target country’s ability to generate tourism. A related problem is deciding on how many different international ad campaigns to develop. The Calantone, di Benedetto, Hakam and Bojanic (1989) positioning study of tourism in Pacific Rim countries, using correspondence analysis, showed that people from different origins perceived particular destinations (such as Singapore) differently. Information like this could help the Singapore Department of Tourism decide whether it was worth the cost of developing different ad campaigns targeted at different origin countries.

Another issue of importance is measuring the effectiveness of advertising, to determine what (if any) changes ought to be made in the campaign or choice of vehicles. Advertising professionals speak of conversion rates, that is, the ability of an ad campaign to “convert” inquir- ers into users. Ronkainen and Woodside (1987) provide a useful, “how- to” guide for advertising conversion studies in tourism. They compare and contrast different data collection modes (telephone versus mail), discuss estimates of revenues and costs associated with carrying out the study, and discussed some recent applications.

Several recent articles have shown how tourism practitioners have segmented their markets and developed promotion specific to their targets. Grand Circle Travel serves the over-50 market exclusively, and reaches them through direct mail (Savini 1986). Reno has sought to target affluent “baby boomers” (Edmondson 1988). Nationwide Lei- sure. Inc. targets vacationers preferring a special kind of travel experience- self-catering villa vacations (Upton 1985), while Club Med. Inc. has been trying to expand its reach to more than its typical “swinging single” market by advertising a new, more cultured image (Heller 1985).

CONCLUSIONS

This article has presented an overview of the uses of marketing management in tourism and a few selections from the literature of marketing research tools which have been applied to that task. Man> other substantial articles exist and the interested reader is encouraged to pursue these by referring to the recommended articles and sources. There should be little doubt that tourism has entered an age where scientific tools of management and the arts of managers contribute to the design and fulfillment of the tourism act in many forms. To the degree that scientific tools are integrated into the tourism marketing management process, these tools can contribute to greater efficiency in both production and the delivery of tourism goods and services. q 0

116 1lARKETING ;2lANAGE%IENT AND TOURIS

ArX_nou,/~d~rne7l/-The authors are Krateful to C..1. diBrnedctto for comments and asb1.v tance on this paper. Rogel- Calantonr tvorkcd on thi, article \vhile hv was still at tht University of Kentucky. US.4

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Submitted 37 October 1989 Re\.isrd version submitted 22 Aueust 1990 Accepted 24 August 1990 Refereed anon!.mousl!

marketing management and tourism

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