beamish museum — modelling visitor flows

beauty of Cornwall. and the variety of

rural and coxtxl Isisurr activities.

Yet. there ;lre also inherent wz:~li-

nesscs in this position. Tourists com-

ment unfavourably on cleanliness

problems, on traffic nnd congestion

difficulties and on the lack of all-

weather attractions in uII three surveys

and. on balance. the wlume of com-

plaints has increased over time. This

may. or may not, be connected with a

significant decline in the percentnsr of

first-time visitors to Cornwall. A suh-

stantial number of non-econornicall4 motivated entrepreneurs meant that

the industry ;~s a whole is not alloys as

sensitive to such trends as it could be.

Therefore. one of the major contribu-

tions of the project has been to hiph-

light the difference hetsvern the short-

term ;md the long-term interests of

tourism in Cornwall. It is precisely

because of this that it is inip~~rt~~nt to

establish accurate long-term monitor-

ing of tourism trends in Cornwll anif,

indeed, in :lIi major tourist re$xxi.

Gareth Shaw and Allan Williams Department of Geography

University of Exeter Exeter, Devon EX4 4RJ, UK

and Justin Greenwood Department of Administrative

and Social Studies Teesside Polytechnic

Middlesbrough C/eve/and, TSl 3BA, UK

Notes

‘British Tourist Authority, The British Tour- ism Survey, London 1987: see also En- glish Tourist Board and Wales Tourist Board, The British Tourism Market 1988, London, 1989. These surveys are also discussed in J. Latham, ‘The statistical measurement of tourism’, in C.P. Cooper. ed. Progress in Tourism. Recreation and Hospitality Management, Belhaven Press, London, 1989, pp 55-76. ‘British Tourist Authority, ibid. 3British Tourist Authority, ibid. 4J. Greenwood, G. Shaw and A. Williams, Cornwali Visitor Surveys 1987, 1988 and 1989, Tourism Researdh Group, University of Exeter. UK. 1988. 1989. 1990. ‘J.C. Holloway, The Business of Tourism, Pitman 2nd ed. London, 1985. ‘British Tourist Authority, British Holiday lntenfions f 988, London, 1988. ‘A. Woodside, ‘Measuring the conversion of advertising coupon inquirers into visitors’, Journal Travel Research, Vol 19, No 2, 1981, pp 3&41. ‘R.P. Perdue and MR. Botkin, ‘Visitor survey versus conversion study’, Anna/s of

Tourrsm Research, Vol 15, 1988, pp 76 87. ‘P.L. Pearce, The Ulysses Factor: Evaluar- ing Visitors !n Tourist Settings. Springer- Verlag, New York, 1988. “‘C.P. Cooper, ‘Spatial and temporal patterns of tourist behaviour’, Regional Stu- dies, Vol 15. No 1, 1981, pp 359-371. “0. Pearce, ‘Tourist time-budgets‘, Anna/s of Tourism Research, Vol 15, 1988, pp 106-121. ‘*J. Hunt and G. Cadez, Utah Tourism - Spring 1978, Institute of Outdoor Recrea- tion and Tourism, Utah State University, USA, 1980. 13R.R. Perdue, ‘The 1983 Nebraska visitor survey: achieving a high response rate with a diary questionnaire’, Journal of Travel Research, Vol 24, No 2, 1985, pp 23-26. ‘“0~ tit, Ref 9. p 48. 15G, Dann. 0. Nash and P.L. Pearce. ‘Methodology of tourism research’, Annals of Tourism Research, Vol 15, 1988, pp l-28. ‘6Pearce. op cit. Ref 9, p 58; and SE. lso-Ahola, The Social Psychoiugy of Lei- sure and Recreatjon, Dubuque, IA, USA, 1980. “Pearce, ibid. “Op cif, Ref 4. “Ibid. “Part of the project is described in G. Shaw and A. Williams, ‘Firm formation and operating charactenstics in the Cornish tourist industry - the case of Looe’. Tour- ism Management, Vol 8, No 4. 1987. pp 344-348.

Beamish Museum - modelling visitor flows An econometric model of visitor flows to a single tourist aftfaction - Beamish Museum - has been developed by Adrian Darnell, Peter Johnson and Barry Thomas of the University of Durham, UK. The study complements the work on aggregate studies of tourism demand. The single equation model is subject to various limitations, which are discussed, but it nevertheless provides some robust results which are of interest both as a test of economic theory and as a potentially useful management tool.

The formal econometric modelling of It is against this background thnt the tourism demand between countries results of an analysis of visitor flows to has received considerable research a major individual attraction, the attention in recent years.’ This study North of England Open Air Museum complements these ‘macro’ studies by at Beamish, are presented.’ formally modelling demand at the Attention is focused on n sinple level of the individual tourist nttrac- equation demand model based on

tion. Such modelling may provide a elementary economic theory. It is better and more rigorous understand- shown that such a model, despite its ing of the underlying nature and deter- limitations, can provide some interest- minants of demand for the attraction ing insights and may be of value as a and hence a sounder basis for management tool. Decisions on pric-

forecasting.’ ing. investment. staffing. marketing It is against this background, that and product development are. for es-

ample. likely to be affected by their

implications for demand. ,Iforeover.

some of these decisions tviil be ;l cw-

~~‘~~~~~~?~~ of past or forecast trends in

demand. While the form:11 modelling

of demand cannot be ;I substitute for

the intimate intuitive knwledge of

their visitor flows that munl\gers ma!

have built up over many years - fre-

quently, an econometric annlysis can-

not easily capture some of the more

.qualitntive’ factors which managers

mny think are important - it can

nevertheless provide an appropriate

txw from which to work. It is thus a

useful complement to managerial in-

tuition and an aid to judpment.

Background to Beamish

The idea of an open-air museum in the Xorth of England was first formalized in 1958 tvhen a proposal ~vns put to

Durham County Council’s Bowes

1luseum Sub Committee by Frank

Atkinson, the then ne\cIy appointed Curator of the Boues Lfuseum.’

TOURISM MANAGEMENT September 1990 257

Atkinson‘s ideas had originated from

a visit to an open-air museum in Scan-

dinavia in the early 1950~.~ The pro-

posal \vas eventually taken up by a

consortium of local authorities in the

Northeast and an initial exhibition was

opened in May 1971. The opening of

the museum occurred a year later. The

purpose of the museum was ‘to study.

collect. preserve and eshibit buildings,

machinery. objects and information,

illustrating the historical development

of industry and the way of life of the

North of England’.’ It was to be a

‘living’ museum. The museum was enthusiastically

received in the region with the open-

ing exhibition - which ran for only 20

summer weekends in 1971 - attracting

SO 000 visitors. As Figure 1 shows.

visitor numbers rvse substantially dur-

ing the 1970s - attendance in 1979 was

over sis times that of 1971. During

that period, a number of major ex-

hibits (including the tram, track. sta-

tion, pit cottages, signal box and drift

mine) were opened. These develop-

ments were financed by the local au-

thorities. grant-giving bodies and a

trust fund set up to promote the de-

velopment of the museum. The local

authorities also provided a substantial

contrib~lt~on to revenue funding.

In the summer of 1980, the museum

experienced its first ever downturn in

visitor numbers. This fall created sub-

stantial financial pressures on the

museum and led to some retrench-

ment. It also led, however, to a new

commitment to the marketing of the

museum and to the introduction of

much better budgetary and planning

procedures, The decline eventually re-

versed in the summer of 1985, since

when the trend has been upward. The

severity of the earlier downturn is

shown by the fact that only in 1987 did

the summer figures finally exceed

those of 1979. In the mid 19SOs.

Beamish consolidated its position as a

major museum. In 1985 a key new

development, the Town Street. was

opened at the museum. Then in 1986,

the year a new visitor centre was

opened, the museum received the

Museum of the Year Award. In the

following year it received the Euro-

pean Museum of the Year Award.

The locaf authorities have continued

252

” I ” ” ” I ’ * ’ i t ” 1975 1980 1985

! Year

Figure 1. Total visitor numbers to Beamish Museum 1971-l 988.

to c~~ntribute to the revenue account,

although their c~~ntr~butivn has de-

clined in real terms since 1Y7-L75 and

is now less than a fifth of total income.

Although the museum was initially

envisaged as meeting regional needs,

over half of its visitors now come from

outside the Northeast.

Visitor flows are highly seasonal.

This of course is largely attributable to

the weather which probably has a

greater effect on open-air than co-

vered museums.

Modelling the demand for Beamish

In modelling the visitor flows at

Beamish the technique of single equa-

tion estimation was adopted.

Although it could be argued that there

is an identification issue and that the

quantities are influenced by price and

vice versa, this is not relevant in this

context since we are treating the

‘supply’ as infinitely elastic at the pre-

vailing price which is chosen by the

museum. Thus a single equation

approach is likely to be appropriate.

The quarterly flows exhibit a clear

seasonal pattern, which on a simple

ratio-to-moving average analysis -

which involves computing a 12 month

moving average and then expressing a

particular observation as a proportion

of the trend - appears to be stable.

This pattern is not in the least surpris-

ing and mav be wholly explained by

correlating the monthly observations

of visitor flows (espressed as a percen-

tage of a 12 month moving average)

with the n~onthly figures for average

maximum temperature. avernpe i-ain-

fall, and average sun hours. Given the

great stability in the clistribution of

visitors over the year the tlo~vs were

modelled in a log-linear form. using

simply shift dummy variables to cap-

ture the seasonality. The log-iinear

form has been widely used in studies

of tourism demancl.x There is also a

need to model ‘quality’ changes as the

nature of the museum’s -product’ has

changed si~nifi~~lntiy over the recent

past with the opening of the Town

Street and the new visitor centre.

Again, dummies were introduced to

capture this effect, though they were

introduced in a manner which allows

there to be a ‘decay’ in the effect.

Both dummies take the value one in

the quarter of introduction, but then

the dummies each decline so that in

the next period they take the values

0.9. 0.8 and so on to a value of 0.1

which is then maintained. This is a

rather crude attempt to capture the

likely decline of the influence of such

TOURISM MANAGEMENT September 1990

quality changes. The timing of Easter is also likely to have an impact. and Easter may fall in either the first or second quarter. Two dummies were introduced to capture the effect. one taking the value one in quarter one if Easter Sunday falls in that quarter and zero otherwise. and a second dummy which takes the value one in quarter two if Easter Sunday falls in that quarter and zero otherwise. This allows there to be a differential impact upon visitor flows. depending upon the quarter in which Easter falls.

The equation which was first examined therefore includes the above dummies, and includes. as ‘economic variables’ the entry price to Beamish, disposable personal income and the retail price index. as an index of the price of other goods.” These variables are included in accordance with standard economic theory. The variables ‘own price’, ‘income’. and prices of other goods and services’ appear (in one form or another) in all the ‘macro’ studies of tourism referred to earlier. although the precise specification of each variable varies. I” U’hen estimated in this fashion, the equation showed marked autocorrelation in the residuals which was interpreted as an indicator of mis-specification. Any regression equation is necessarily char- acterized by errors. omissions and approximations. However. a well specified equation will have residuals which are consistent with a non- systematic error structure. and the presence of autocorrelation indicates that the error contains some systematic components. This clearly indicates that the specification is deficient in some way, and further analysis is re- quired. The deficiencies may arise, inter ah, from the use of an incorrect functional form, a mis-specified set of regressors or data which are inadequ- ate proxies for their theoretical coun- terparts.

In a simple equation which seeks to explain visitor flows by a set of dummies (thought N priori to be important and which have theoretical justifica- tion) and a set of contemporaneous economic variables, it is recognized that a number of salient variables may have been omitted or may have been mis-specified. For example, the role of

advertising and marketing is not included because of the absence of suit- able data. nor is the important effect of information ‘trickling down‘ through the potential population of visitors - visitors tell others of Beum- ish and this leads to increased demand as avvareness of the museum becomes more widespread (see below hovvever).” Furthermore, there is no attempt to model the composition of demand in terms of first-time and repeat visits. (The frequency of visits will depend. inter dia. on the rate of decay of the initial experience.) Again, there is no explicit recognition of the fact that continued growth in demand entails drawing visitors from more and more distant locations. Travel costs, which it should he noted are incorporated as an explanatory variable in studies modelling tourist movement between countries and visitor demand for particular attractions, increase as a result. and the price of the ‘day-out’ (rather than simply the admission price) increases prtri passer.” There may be several com- plex interactions, eg repeat visits are more likely for visitors who live near-

er, and the attraction’s marketing strategies may influence and be influenced by the geographical source of visitors. Again transport costs are ex- cluded because of a lack of appropriate data. Finally. possible supply constraints and the role of competitors have not been examined. These issues may be of importance but need not he considered here.

However, account has been taken of the possibility that in making con- sumption decisions. individuals may react to previous values of the admission price, of their own disposable income and of the general price level. Specifically, the rate of change of the admission price may be salient, as may the rate of growth of their income and the rate of growth of the retail price index (RPI) may also be important. In order to examine these possibilities, the original specification was expanded to include the lagged values of the entry price, disposable income. RPI and visitor flows as additional explanatory variables. The inclusion of the lagged dependent variable allows for the ‘trickle down‘ effect referred to earlier


and for habit persistence.” The latter effect implies that individuals uill make repeat visits - crtrris prrrihs. an individual who has made a visit in period t. is more likely to do so in period (+I. These additions resulted in a well-specified regression equation which successfully passes the key diagnostic tests of serial correlation. functional form. normality and heter- oscedasticity (see below).

Modrl reprrset~tatiott

The estimated equation may be written in a somewhat simplified form. The coefficients on the current and lagged entry price are not significantly different in size, but are of opposite sign, and this allows us to combine the two independent variables of current and lagged price in difference form. Also, it is possible to combine the disposable income variables with the general price level and write the equation in terms of current deflated disposable income, and its rate of growth. These changes are data-based simplifications of a general equation whose specification is determined by theoretical considerations. This equation. estimated over the period 1975Q7 to 19SSQ3. may then be written in the following terms:lJ

In(V) = - 13.53 + 0.61&t + 3.20QZ + (4.65) (0.2s) (0.29)

2.71Q3 + 0.91E, + 0.69E2 (0.09) (0.14) (0.16)

+0.08X, + 0.22X, - 0.91s (0.11) (0.13) . (0.18)

-0S3ln(P/P_,) + 3.lOln(rp&) (0.17) (0.90)

+1.2lln(rpciiirpdi_t) (1.27)

- 0.55ln(RPI) + 0.45lnV_ L [l] (0.17) (0.11)

(Standard errors are in pa- rentheses.) R-squared = 0.9880; F- statistic [F(l3? JO)] = 253.0602. R-bar-squared = 0.9831; Stan- dard error of regression = 0.1641.

253

I. = the sisitor flt-r\v:

Q, = 1 in quarter i. 0 othrr-

\\lx?;

6 = 1 tf Easter Strn&~~~ falls

in quarter i. 0 otherwise:

X, = product quality dum-

my: Town Street. see

text:

,U, = product quality dum-

mb; Visitor Crntre. see

text;

s = exceptional kveather

dummy. see test. 1 in

lY79Q 1. 0 otherwise:

P = the full admi.ssion price

(average for the quarter);

rptli = real personal dispos-

able income: and

KPI = retail price index.

The following diagnostic tests are re-

ported:

0 serial correlation - CHJ-SQ(A) =

7.1690: F(1, 36) = I .JOOO * fLincti~~n~l form - CHI-SQ( 1) =

1.66JO: F(1. 39) = 1.2-W

l normality - CHJ-SQ(7) = I).9?87:

F statistic not applicable

e hrteroscrdasticity - CFJI-SQ( 1) = 2.55%; F( 1. 52) = 2.X%1

The 5% critical values are 3s follows:

0 CHI-SQ( 1): 3.54; CHI-SQ(7):

5.99, CHI-SQ(j): Y.-19

0 F(-l, 36): 2.S6; F( I, 39): 4.09; F(1.

57): -I.03

The four tats examined are, respec-

tively. the Lagrange multiplier test of

residual serial correlation, Ramsey’s

RESET test using the square of the

fitted values . a test of the skewness

and kurtosis of residuals and a test

hnsed on the regression of squared

residuals on squared fitted values.” This equation was also subjected to

a test of stability, estimating it over

the period I97501 to 198701 and

examining the predictions over the

next six quarters with respect to the

known outcomes. Not only are the estimated coefficients little different

from those from the full sample, but

using Cho\v’s second test for predic- tive failure. the hypothesis of stability

254

l CHI-SQi6) = S.OIss:

l F(h), 34) = l.3Xi

which are to be compared with critical values (using ii 3"L significance level)

of 12.5’) and 7.35 re>prcti\,elc.

It is important to notr that the lap-

ged variable:1;, ~~lth~~u~h included in ;I

general way. may be xvrittrn in the

specific form as above - the estimated

equation allows the current md lagged

admission price to hc written ;IS the

logarithm of the ratio of currt’nt to last

period’s price. This is (~lppr~~~i~i~~ltci~) the percentage increase in the xdmis-

sion price and. as predicted by theory.

has ;I significant nspative sign. The

estimated equation also indicates that

the role of the senrral price level is

felt through the cariahlc rpli which is

nominai persitmti disposable income

deflated bv the RPI, through the

logarithm oi the ratio of current to last

period’s ‘real’ personal disp~~sahle in-

come (tvhich i\ roughly rqu~~l to the

percentage r:itc of growth of -real

personal disposable income), and

throuph the term in the RPf itself.

Also. the last period’s visitor flows

have a siynificant positive effect on the

current flo\vs. This latter variable may

be explained by reference to the role

of potenti~~ll~ important, though im-

measurable. variables - as inf~~rrn~lti~~n

on the museum percolates through the

potentia! visitor population this in-

creases visitor flows further. many

visitors repeat their visits, and direct

advertising (such as that throuph car

stickers displayed by previous visitors)

also acts to increase the number of visitors. This lagged flow variable may

be interpreted as catching the aggregn-

tion of such effects.

As a test of economic theory, this

equation performs ns predicted by theory - the role of admission prices is

significant and negative. an d the current demand for admission would

appear to be price inelastic (:I 1% rise

in the current admission prices

appears to reduce current demand by about 0.5% crtrrisprrrihrcs). The influ-

ence of current ‘real‘ personal clispos-

able income is significant and positive. and indicates a relatively large short-

run elasticity of -!..?I. However, not

onI\ doe\ the Ie\cl clt Inc‘omr’ matter,

but-so doe\ the JirecticJn of sro\bth -

srtxvth in income Increat‘\ demand

(Thiz cctctfficlent on the growth of r&i

i> not l+ell defined. hut it> ikirtwn produces illltOc~)rrel;lti(~[1 in the rr‘-

siduals, indicating that excluding thi3

variable results in some mis- 3prcification . and on thi\ critr‘ritxl its inclusion is justified.) The ~rnttral

price level has ;I further role to play. in

addition to dctl~itinp nominal incomes

- even if incomes and price5 were to

rise in the same proporrton this rqu;~-

tion indicates that demand for muscum admission ax~uld fall. This

suggests that, even if real it~co~l~cs

xvere maintained. general inflation re-

sults in consumers si4itching demand

aw;iv from such Iei3urc activities as

museums. The rote of ht period’s

visitor numbers is, as predicted. signi-

ficant and positive. ;mt this muht he

interpreted as catching ;I large number

of omitted, non-mea~iirahls. influ-

ences. The signs and significance of

the coefficients on otvn price. inconic

mti the tagged tiepcntfat vari:~hle ;~re in line with results from the agprcgztc

srudies of tourism flokvs.‘”

The &mated equation also indi-

cates that the quarterly effects are all

significant, as is to be c\;pected. and

the quality changes both have positive

impacts. though the coefficient on the

Town Street dummy i% not well de-

fined. The effr’ct of Easter is positive,

and significant. bvith the six of the

impact depending upon rhc quarter in

which Easter falls. The dummy vari-

able S takes account of the escep-

tionally bad weather of qxrrter one,

lY7Y, during which the Xorthrast suf- ferrcl badly from snow conditions.‘i

FOW(XStv . .

The equation can be used for forrcxt-

ing demand on the basis of different

assumptions about the yrowth in admission prices and in real personal

disposable income. As an example.

visitor numbers for 1YS9 and the sub-

sequent five years were forecast. This

exercise was undertaken at the end of 19% and used then a\-ailable UK

treasury estimates. adjusted where

appropriate. of future likely trends in prices and incomes. The forecasts also

incorporated the price increases


already agreed for IYSY.‘” Specifically. it was assumed that:

l

0

0

prices would rise by 5% per annum after lYS9; the RPI would grow at 7.5% in quarters 1 and 1 of 19SY. would rise to 8.0% in quarter 3 and would then fall back to 7.0% in quarter J; during 1990, the assumption was that inflation would be 6.0% and would be 4.0% in all future years (all the percentage figures are annualized rates);‘” the growth in personal disposable income, deflated by the price level. would grow at 2.5%. 3.0% or 3.5% per annum.“’

Each of these scenarios was considered, and the results are shown in Figure 2. The lowest growth path was that associated with real grov.C ot income at 2.5% per annum, the mid- dle growth path was that associated with real growth of income at 3.0% per annum and the highest growth path was that associated with real growth of income at 3.S% per annum. Whichever scenario is considered, the general path was upwards from 19S9. The forecast dip between 1988 and 19S9 was largely a consequence of the known increases in admission prices and the acceleration of the general price index. The forecasts suggest that the number of visitors may significantly exceed SO0 000 by 1991.

The act& visitor numbers in the first three quarters of 1989 were nearly 11% higher than those forecast on the basis of data available at the end of 19%. This difference was almost cer- tainly largely accounted for by the exceptionally good weather in the spring and summer of 1989. Longer term forecasts of weather patterns are of course notoriously difficult to make and hence the need to retain some inbuilt flexibility that can enable management to respond to such fluctua- tions. Forecasts should of course be made on a rolling basis with subse- quent forecasts incorporating new information as it becomes available.

It is not realistic to use the model for longer term forecasts but the forecasts for the years up to 1995 have been presented in Figure 2 simply to

IIOO-

1000 -

“$ goo-

r 2 6 800- c’ i5

: 700-

600 -

Figure 2. Annual forecasts up to 1995.

indicate the growth paths if there were no changes in environment nor any constraints operating. It cannot be emphasized too strongly that such long-term forecasts cannot be taken at their face value. However, while they may be seriously inaccurate they may nevertheless be of some use for planning by providing a benchmark which can be modified in the light of managers’ views of specific factors influenc- ing the demand for the museum, its competitive position, and its capacity. Various limitations of this forecasting exercise are considered below.

Discussion and review

This modelling and forecasting exercise provides some useful results, summarized in the final section of the paper, but it is proper to recognize that it has a number of limitations.

The forecasts are, as shown above, subject to error.” There are three sources of potential error. The first is the unexplained component of the estimated equation. The equation fits the data extremely well but it is. of course, not an exact fit and the conse- quent forecasting error will become larger as the period of the forecasts increases because any error or forecast in one period feeds into the forecasts of future periods.


A second source of error is the uncertainty of the future path of disposable income, the general price level and admission prices. The paths drawn in Figure 2 were based on ‘in- telligent guesses’ about the movement of these variables.

A third source of error is that the forecasts are made on the assumption that the future will be an extrapolation of the past. Simple extrapolation takes no account, for example, of ‘shocks’ which may occur. An obvious instance in the case of Beamish Museum is the potential effects of the UK National Garden Festival to be held nearby in Gateshead in 1990. This is likely to be a major tourist attraction and the net impact on Beamish is uncertain. On the one hand, it may attract more visitors into the region who may combine a visit to Beamish with a visit to the festival, or on the other hand, the festival may draw demand away from the museum. This example raises the more general question of the significance of factors such as the competitive interaction of different tourist attractions and the role played by marketing, which are not explicitly modelled. The effect of changes in competitors’ products and prices may influence the business strategies adopted by Beamish and the flow of visitors. The marketing strategies

adopted by the museum m;iy ;~lso b*

affected. as noted e;trlier. hq’ the need

to entice Csitors from mare dist:int locations, \chich mav raise the

museum‘s costs. Escep~ionally go5d

or bad weathrtr represents another

type of ‘shock’. The possible dang&s

of extrapolation from the demand

model presented abovr are also rvi-

dent from the fact that supply wits;

assumed to be infinitely elastic so

there are no supply constraints on the

fiow of visitors. At some point.

however, in thr ,oro\vth of visitors it is

likely that the capacity of the museum

would he rexhrd. The measurement

OF capacity might not be straightfor- ward because the daily physical capac-

ity varies across different p~fs of the

museum and rhr issue of whether or

not the product - The Eknmish Es-

perience - comprises the option of

visiting cdi parts of the nl~l~e~Irn be-

comes relevant. In an? event the esist-

ence of capacity constraints could im-

pose ;t ceiling on the growth of visitors

from the supply side uhich would

operate separately from any demand-

side ceiling attributable to such f;lctors

ns saturati5n. frequencies of repent

visits and eventually prohihiti\,e travel

costs as the market is extended geop-

raphicaiiy.

This paper has deseloprd an eco-

nometric model of visitor tk3vs to 3

single tourist attraction. ft cumple-

ments the work on apgregnte studies

of tourism demand. The single equa-

tion model used is subject to a number

of limitations 3s considered in the discussion, but nevertheless provides

some clear results which are of interest

both as a test of economic theory and as a potentially useful management tool tvhich may be applicable n~arir

t~ztf~~i~l~j~ to other individual attrac-

tions,

The modef show5 the rekvance nf

admission pricer and of real personal

disposable income as determinants of

demand. In the short run. price elasticity over the range experienced is

low (about -0.5) and income elastic-

ity is high (about i-4.3). These results are robust and suggest that a simple model of tkis kind can he of consider-

256

able v;~lue. This i\ not to deny rh;lt

more sophisticated moclelling, talking account of some of the issues raised in

this paper. Nould not he drsirablr.

The po>sihilitc of there being ~)mr

ceiling to the forecasts might he conG-

derrd but in fact. in this cxx study.

the fit of a iop-linear model to the

sample data is extremely good and

experiments with varktbk elasticities

did not perform well.

The strength of the estimated equ;+

tion prrmits a modest measure of con-

fidence that the model m;~y br of some

vuiue in aiding the formntion of man-

agerial judgments, for esampk ;tbout

the size of the elasticities and the trends in visitor flows. Other findings

are also potentially significant. ?‘~Iz

remarkable stahifitq in the ~~istr~bLIt~(~~~

of demand across the four quarters

suggests. for instance, that it might be

difficult to alter this pattern. Thus

r~~iistrib~itin~ the s~li~ir~~er peak might

be possible but is fikcly to require

substantiat effort. The rolr ~>f certain

product developments is XISLI high-

lighted as art‘ the czrry-over effects

from one period to the next.

As a short-run forecasting tool the

model appears to have some prcdic-

tive ability though for the longer term

it could only he used as a basis for

modifying projections in the light of

j~id~~lents about qll~~~it~~tive aspects of

the operating envir~~rln~ent.~~ The

appropriate way to use the model for

forecasting would thus be in the form of a rolling review with cnntinual up- dating as estimates of frrturc ximission

prices and real personA disposable

income are revised.

Adrian DamelI, Peter Johnson and Barry Thomas

~e~a~rnent of Economics, ~~~~ers~t~ of Durham, UK

Notes

‘ML. ~liman, ‘A quantitative analysis of Canadian overseas tourism’, Transporta- tion Researcti, W 1%. No 6, 9981, pp 487-497; J.S. Little, ‘international travel in the US balance of payments’, New Er?g iand Economic Review, May-June t980, pp 45-55; P. Loeb, ‘International travel to the United States: an econometric evalua- tion’, Anna/s of Tourism Research, Vol 9, No 1, 1982, pp 7-20: CA. Martin and S. Witt, ‘Substitute prices in demand models of tourism demand’, .&~rnal of Travel Re- .S&WGh, Vol 25, No 3, 1388, pp 23-30; E.

Smeral, ‘Tourism demand, economic theory and econometrics: an integrated approach’, Journal of Trave) Research. Vol 26, No 4, 1988, pp 38-43: SF. Witt, and CA. Martin, ‘Forecasting future trends in European tourist demand’, Tourist Review, VoJ 4. 1985, pp 1 Z-10: SF. Witt and C.A. Martin, ‘Econometric models for forecasting international tourism demand’, Journal of Travel Research. Voi 25, No 3, f 987(a), pp 23-30; and SF. Witt and C.A. Martin, ‘International tourism demand models - inclusion of marketing variables’, Touris# management, Vol 8, March 1987(b), pp 33-40. For a brief review of some of these studies, see: P.S. Johnson and J. Ashworth, ‘Modelling tourism demand: a summary review’, University of Durham, Department of Economics, Tourism Work- ing Paper, No 1, 1988; and J. Ashworth and P.S. Johnson, ‘Holiday tourism expenditure: some preliminary econometric results’, University of Durham, Department of Economics, Tourism ~ork;~g Paper, Na 2, 1989. qhis case study is concerned with one method of forecastjng only (regression). For a detailed review of a number of forecasting techniques used in tourism, inctud- ing regression, and an assessment of their relative merits see: R.J. Calantone, CA. di Benedetto and D. Bojani, ‘A comprehen- sive review of the Lou&m forecasting liter- ature’. Journal of Travel Research, Vol26. No 2, 1987. pp 28-39. % might be argued that Beamish is a museum first and a tourist attraction second. It is not however necessary to enter this debate. Whatever the status assigned to Beamish, the ~eterminanis of its visitor ffows remain of considerable management interest. ‘For a history of the museum see: P.S. Johnson and R.B. Thomas. ‘The development oi Beamisk: an assessment’, Inter- natioffai Jixjrnaf of Museum Management and ~ura~ursbj~, Vol9, NO I, 1990, pp 5-24. SMinutes of Durham County Council’s Education Committee on Further Educa- tion, 10 December 1958. ‘The Times, 18 June 1986. ‘first Development Plan, presented to the Joint Committee for the North of England Open Air Museum, 11 December 1970. *See, eg Witt and Martin t987(a), op tit, Ref 1, and the studies quoted therein. ‘it can be argued that the relevant price is the cost of the whole outing. and should therefore include travel costs and possibly the cost of meals out (bought either inside or outside the museum) and other shop ping. This raises questions about the de- finition of the product demanded, ie whether it is admission to the museum or some wider experience, which might in- elude visits to &her tourist attractiot?s. ‘OSee. ea Martin and Witt. 1988, OD cif, Ref 1, for a &scussion of alternative ‘methods of including substitute prices. “Most ‘macro’ studies of tourism do not include an advertising or marketing variable. For an exception see: S.I. Papado-


poulos and SF. Witt ‘A markettng analysts of foreign tounsm in Greece’, in S. Shaw, L. Sparks and E. Kaynak, eds, Proceed- ings of the Second World Marketing Con- gress. Stirling, Scotland, 1985. It should be noted that the data requirements for an advertising/marketing variable are quite severe since the advertising/marketing efforts of competing countries should also be included if the model is to be correctly specified. “Johnson and Ashworth, op cit. Ref 1; J.N. Morgan, ‘The impact of travel costs on visits to US National Parks: intermodal shifting among Grand Canyon visitors’. Journal of Travel Research, Vol 24, No 3. 1986, pp 23-28; and S.F. Witt. ‘An abstract mode-abstract (destination) node -ode1 of foreign holiday demand’, Applied r’conomics, Vol 12, 1980, pp 163-180. Witt (1980) also includes a travel time variable in his analysis of overseas tourism by UK residents. As far as Beamish is concerned transport costs will of course be of relatively limited importance for visitors coming from the Northeast. 13Witt, 1980, ibid; and Witt and Martin 1987(b), op tit, Ref 1. “The entry price (P), real personal disposable income (rpdi) and general price index terms (f?P/) in the estimated equation were derived as follows. Denoting Y as nominal personal disposable income the contnbution of P. Y. and RPI may be specified by: - /fin(P)+ji ,ln(P ,)+dln(Y)-i, ,ln(Y. ,) - xln(RPI ,) + .-r.,ln(RPI 1)

this may be wntten as:

- @ln(P/P ,) - (/; - /j ,)ln(P ,) T Oln(YIRPI) - 0 ,In(Y ,IRP/ ,) - (II - 0) In(RPI) + (I , - b ,)ln(RP/ ,)

The hypothesis that/j = /j , could not be rejected and so the separate term in P , is redundant. Equally, the hypothesis that .1 1 - b , = 0 could not be rejected and so the separate term in RPI , is also redundant. Thus the equation may be written as:

- jjln(PiP~ ,) + l~ln(rpdi) - 2, ,ln(rpdi ,) - (IT - ~~)ln(~P~

This may now be written as:

- [3ln(PIP ,) + (6 - &,)ln(rpdi)+ S_,In(rpdilr@L,) - (a - O)ln(RPI)

and this is the form of the equation re- ported in the text. “For a full discussion of these tests see M.H. Pesaran and B. Pesaran, DATA-At An interactive Econometric Software Package, Oxford University Press, Oxford. UK, 1987, pp 136-139. “Johnson and Ashworth, op cif, Ref 1. “In the first quarter of 1979 there were 22 days in January with one or more inches of snow on the ground at 9.00 a.m., 12 such days in February, and 13 such days in March. This was far greater than for any other year since the early 1960s. “The admission price increases in 1989 were substantial. They were well over 20%. lgThe UK treasury’s forecast in The Finan-

ciai Statement and Budget Report, March 1989, of the annual rise in the RPI was 5.5% for 1989 and 4.5% for 1990. At the time the forecasts were made, these were widely viewed as being too low. ‘This range of figures was chosen on the basis of the UK treasury’s forecasts of the growth of GDP (1989 - 2.5%, 1990 - 2.5%) and consumer spending (1989 - 3.5%; 1990 - 2.5%). “It IS unl~keiy that the error will exceed j, 15% for the earliest forecasts. The standard error of the log linear regression is esttmated as 0. f 6 so that in natural levels one standard error represents f6%. For a normal distribution, rather more than two thirds of all observations lie within one standard deviation of the mean. It is in this sense that the word ‘unlikely’ is used. “It was noted in the section on modelling the demand that ‘wlthin sample’ forecasts were convincing. Forecasts of rpdi are not easily available but there are many good proxies such as gross domestic product (GDP) and consumers’ expenditure. Wad forecasts of GDP, which were available in 1978 and 1979, been used the model would at that time have correctly forecast the downturn in the number of vtsitors in the early 1980s. UK treasury forecasts of GDP growth a year ahead had been non- negative since 1959, but in 1978 the forecast for 1980 was for a substantial fall in GDP (which did occur). By 1979 all the principal economic forecasting models of the economy were publishing forecasts of a fall in GDP.

Reports To~ri~rn planning in Nigeria The Lagos State government of Nigeria has instigated several tourism initia-

tives during the 1980s to do with planning and pa/icy making and devising development strategies. The lack of available data on Nigerian tourism largely invalidates the planning assumptions which may therefore have resulted in unrealistic goals. J.B. Falade, Senior Lecturer in the Department of Urban and Regional Planning at Obafemi Awolowo University, provides a critical review of the Lagos State regional plan which aims to increase Nigeria’s supply of foreign exchange.

Generally speaking, there is a low During the past decade. ho\vcver, priority accordrd to~lrjsrn planning the Lagos State governnler~t of Nigeria and development in Nigeria.’ This has takkn an active lead in evolving

point was well made by Akhiehc, a tourism plans. policies and drselop-

one-time governor of the Lagos State, ment strategies. This radical effort has who. in 19S7, described tourism as an Qivrn rise to some intriguing lessons important contemporary industry for tourism planning. From a critical which has not been given due atten- review of the tourism components of

tion in Nigeria.’ To circumvent the the Lagos State Regional Plan and economic crisis facing the nation man> associated tourism policies and action have advocated the need to develop plans it has been possible to discuss the nation’s tourism resources to earn the viability of the Lagos State much needed foreign exchange.” approach as a model for tourism plan-

ning and development in Nigeria at

large.

Background to Lagos State

Lagos State, one of the 21 states in the federation. is situated to the south- lyestern corner of Nigeria and borders on the Atlantic Ocean to the south. While Lagos State is amnny the smal- lest Nigerian states in land area, para- doxically, it is also among the most populous and urbanized states in the country. With an area of 3577 km’, Lagos State. has a current population of Sk336 x 10’ of which 7898 X IOh

(94.4l%) reside in metropolitan Lagos.’

Everything in Lagos State revolves around metropolitan Lagos. the feder- al capital, which is among the most populous capital cities in Srfrica. Both the tourist attraction and population growth of metropolitan Lagos are connected with the city’s role as the feder-


beamish museum — modelling visitor flows

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