Purchase expectations and the demand for consumer durables

PURCHASE

EXPECTATIONS

CONSUMER

Rewved

Sll

following

1.

tional

and lhc lime xric’s

nic’;Isurc

and

of consunicf

intentions

ing mod& appcnrs

may

dat;~

lhal of the

rtxently

of inlcntions

data

kvcls.

have

author

d~matid

though

In gcncd. in

for consumer btxn

much

nut&al at both

it was often

cross-sectional

3s an input

r;ithtx into

durd-dcs.

(e.g.

rationale (I’ichcring

the cross-scchclcl that kvhilc

work. than tinic

it

IV;IS ;I

specific

to collection Ievel

buy-

scrims forecast-

In consqucncc‘.

kss attention

31 fhc crosksectional

Katona

of

hchavioural

in wrlicr

or attitudes

was importanr

to have

FOR

work

has proceeded

value

confitknce

pioneering the underlying

by fhc prcscnt

ch.

ing

anti

1981). Such work

1977:

intentions

the

of this work

has been ccxisidcrctl

DEhlAND

September 30. lYR3

particularly

1075). l‘hc nature

THE

*

JJnuary 25. 1983. axeptrd

rvcys,

AND

DURABLES

the recent

there and

use

study

by

de Jonge and Oppedijk

\‘an Vren

(19P7)

decline

intentions

data

in

durablcs

the use of contrasts

grnsralixd

models

decision

and

explaining

of consumer

research

(e.g..

the reality.

The durables

of

Parlicular

present

author

the

is

;I

of

m~thoclologic~lt

the scrics

asling (ion3

raponx

others

or

consumer

~vays in Lvhich such

to aspects

of

of

kvith

the Lvork

cspcctation5

ho\t, many. and

availahlc xopc

the

in

through

buv.

the

niarhct

for iniprovcd

the

data i5 to

Mill

indcccl

of the information bctwwn

of

l‘hc

to

Thih

grc)\\ing

and

social

tcchniquc5

collcctcd.

need

to

I lo~~vcr.

maintain

dirwt

and the need to cncour;Igc

time

methods

of

categoric>

data collection

form

cxcrcisa

of wwding

SoniL:

surveys

have

have used ordinal that

the

has ranged

intcrmcdiatc

has v;Iricd, asking

is

3 (yes.

dur;ihk

no. don’t

have been used).

cac5

cardinal

ncwmallv l‘hc

numba

hnoiv) The

on

the: cspccta-

to ux

(thoiigh

metric).

onlv

in wmc

;Ibout

attcmptcd

scaling

scale

from

vnlucs

on

have been wlthin

other.\ have focu5wl

to buy and in other5

assumption

not all

time horizon

intentions for

perfor-

of ;I Lvidcl rangin g hurvcy.

purchasing.

while

use of

its predictive

has been uacd. Some

expwt;ltions.

implicit

(though

variety

about inlcntions of

scaling

and the

to be so close.

the

Ciil;l”tifiC;\ti(~ll

conflict

different

or

Unfor-

the 1970~

mcthodologics

cxpwtations

purchase

is quite

the demand

of \vho. or

and rcliahility

predicting 19X0).

improvcmcnt~!

the framwwk

the

the

considcrablc:

purchase

made

in

to improve

and Lvorhing

sonic

with

as to further

allo\v5 consitlcrablc:

potcnti;ll

c~~mparability A

for

of

gcncr;Illy

add to the quality there

is

for

\wiablcth

Warshaw

to review

topic during

the dtlmand

to the actual purchase

be assumed

forecasting

of prediction

need

sophistication rcsarch

reference

sort

is

in

This

it is clear that stated

concerned

durables.

in an effort

of collecting

some

irnplich

paper

of

There

19SO:

some suggestions

on this

purpox

allow

with

cannot

datu

be developed

mance.

The

this

and to offer

kvork might

is more

exception.

intentions

to be tantamount

especially

expectationx

studies

use of

Reibstein

relation

purpose

in

the

hehaviour.

interest

intentions

intentions-purchase purchase

with

to buy are assumed

intentions

tunately

rwrhedly

is an important

with 01

to 101

purCha5ing

has varied over 3. 6. 12. 24 man ths ahcad. I’roccdurcs

for

summarising

the data have varied.

some

using

the arithmetic

mean.

some the median. some a test balance of the difference betkveen the proportions giving favourable and unfavourable answers. while others have used the proportions

checking

the most

favourable

response

categories only. If the basic technique is valid. it seems likely that many of these variations may only make a marginal difference to the information available. though this mav be important. However. it does seem that tuo methodological dcvelipments have been especially important. The first of these is the shift from a dichotomous yes/no response category to the use of scaling, alloiving the recognition that the expectation of purchasing will be stronger for some consumers than others. The other development is the shift from asking about intentions to buy to an assessment of the likelihood that a purchase will be made. It may be suggested that an intention to buv indicates a very firm commitment and one that it is probably realistic to ask about for only 3 or perhaps 6 months ahcad. Howcvcr. a recognition that there is some possibility of purchasing in the medium term may hc much more realistic. There ma? wdl not bc an intention to buy but there may hc a recognition of a likelihood of buying. Thus lve might expsct fcwcr pcoplc to indicate an intention to buy than a poAhility of buying. Thcrc is also a choice to bc nixic hct~vccn using ;I numerical scale and ;I verbal rating scale. Juatcr (I%(,) pionccrcd the introductk~n of ;I purchase probability scale, 311 itlca ivhich was later uhccl by olhcrs including Gabor awl Grangcr (1972/73). Pickering (lY77). and I’ickcr111::

and lshcrunod

( 1974). While

a 0

100 kcalc has sonwtinics

hcai

iisd, a11 1 I-point scale ranging from 0 -10 has gcncrally been prcfcrrcd. Others have, howcvcr, continuccl to use a verbal scale of 4 or 5 points. I Iowcvcr. the handling of this in a prcclictivc model crcatcs diffcrcnt problems since thcrc may be a wish to establish ;I quantitative summary of lhc data and the choice of wording may bc important. The prcscnt author has also used 7- and Y-point semantic cliffcrcntial scales in a self-completion battcry of scales relating to a particular product. I’ickcring (1977). I’ickerin g and Grcatorcx (1980). The semantic diffcrenlials Lvcrc simply: “will probably buy within the next 12 month.\/~vould not consider buyin, 0 Lvithin the next 12 months”. Effcctivc use has also been made. on a postal questionnaire, of a seven-point verbal rcsponsc scale relating to 12 month purchase expectations. Tlx rcsponsc catcgorics w92rc: “would certainly not buy/unlikely to

buq/possibly won’t buy/50 : 50 chance/possibly will bu>/quitr likelq to buy/will certainly buy”. Fig. 1 compares the distributions obtained (from two separate sampies) of purchase probabilities on an ll-point numerical scale and purchase expectations on ;1 7-point verbal scale. It will be observed that there W;LS;1 loHer proportion on the verbal scale who said they would certainly not buy. This may be helpful in reducing the incidence of non-intenders who subsequently buy. It seems what has happended is th3t more tended to use the nest verbal point ‘unlikely to buy’ than the 1 clnd 2 probability statements. The proportion indicating certainty of “b respondents 12 month 11 point

purchase expectations, 12 month 7 point scale (verbal)

_---

<

purchase probabilities, scale (numerical)

\ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \

/

I

0

1

2

certainly not

3 possibly won’t

unlikely

I

I

4

5

I 50 : 50 chance

6

7

8

9

10

I

possibly will

certainly quite likely

purchase

was lower

on the verbal

than at the previous

scale points

proportion

at the end point

ties. Thus.

on the assumption

comparable different found

in studies

tended

sense. it appears

probabili-

were appropriately

that a verbal

distribution

using a probability

scale the

for the previous

that the two samples

more realistic

to be lower

on the probability

was above that

in a statistical

and perhaps

scale. and this whereas

scale had a

of responses

than that

scale.

The predictive performance of purchase expectations This

leads naturally

on to the assessment

of such information.

Generally,

relate to a forecast

it is likely

this would

period of time - time-series

also the question

Icss emphasis also

for

general

the time-scrics

of

the

time-scrics

the rcvicw in Pi&ring cxpcctations wcrc included

not

have prcdictivc

in fhc model.

information

though

there is this

behaviour.

cross-sectional is mixed

In

rclation-

This

and. in the

has

long

concluded

attitudes

on the product

specific

that this may bc

is devclopin g in a way distinct is initial

J~lTlillld

(see

that pl~rchasc when

to suggestions

and where

hccn

on this in lhc 1W..k

significance

emphasis

has krl

when demand in demand

the

it is arguable

consumer

poor.

worh

ch. 1) gcncrally

nature of purchase cxpcctations lhc gtXlt.!lXltrend

is

cxtcnsivc

1977:

data did

is.

of

do so? While

expectations

pcrformitncc,

to he the cast. The

rccogni5cd

There

model.

actual cvidcncc on purchase

case of

useful

study

it may hc suggcstcd that a convincing

ship iindcrpins The

the

to

of change, of

performance

on this aspect, at Ieast by practitioners,

KlWil1lt

additic,n.

be understood

prediction.

of the cross-sectional

data - do the people who expect to buy actually is

performance

of the level. or at least the direction

sales over some future however.

of the predictive

from

rather

than

XplilC~IllCIl~. The

poor performance

of such data was rcflcotcd

the I3urcau of the Census survey F.T.

its Col~s~Itiicr

which had used the purchase probability

Juster.

predictively favour

to drop

of

IIitcnti[~ns purchase

Having

started

more useful attitudes.

It

a position

than atliludcs, was also

data (i.e. using prohabilitics

from

intentions

approach that

that

developecl by would

swung strongly

the Quarterly

to buy) performed

of the Consumer

of

Expectations

intentions

the pendulum

found

in the decision

Buying

Survey

better

Buyin g Expectations

bc in of

than tht sursey

in

predicting neither

car expenditures.

found

to be dominant

portant.

(XlcNeil

Juster

on

recrni

model.

Since have

hlcNeil’s

purchase Survey

The

expectations

data

included

neither

any measure

on purchase

purcha.\e combined explain

with

an

LV;ISdominated sign when

ttic gcncral

Car purch;w

t2upcclalions

they

income

again

variabk

Thub

that

sion analysts

In cross-wcticw, kvorh,

(we

1075;

Pickering

following

in

and

1977;

to

A principal condi-

Xv;13 included. \vith the overall

confidcncc

mcasurc

in thk

work

N’;I> IIIL‘

to hc insignificanl.) cxpwlations

tlominatccl

mc;imrcs

Istier~~~oc~tl 1974: and

of

had the ‘Lvrong’

akwciatctl

of ;I purchahc

Pickering

each

index

cxpcctations

component

variable

in multiple

of consumer

the results arc more encouraging.

Pickering

informa-

economic

(Incitlcnt;rlly.

being

by Ward

tquations

purchainp

and indeed

gcncrally

EEC

(19S7)

An

on all durables.

rcflccft‘d

insignificant.

gcntzraliscd

by mm

confidcnw

conditions

such J;ILI

disappointing.

sur\ey,

wncr;iI rcflcctin, 0 a

the time scrich pcrformancc

remains

tests of the

and Gianotten

had the Lvrong sign \\ hen

sib~~nificantly

was ;1150 found

their

for all three surveys

and

to of

some countries

disappointingly.

circumstances wwc

appears

In the review

but Lvhcn ;1 consumer

bcc;Imc

in a

the collection

in the EEC

cxpcnditurc

economic

Icvcl of car cxpcnditurc.\ added

results

consumer

data

financial

In

expectations.

by other componwts

tic>ns and pcrwnal

imand

purchase

information required

was available

of

of the survey

house

nor \‘an Raaij

was insignificant index

was

also

b> Adams

basis. though

performed

the le~ei of consumer

component

only

frequrn1ly.

of the British

expectations

of

purchase5 income

liere

Commentaries

expectations

(197X)

expectations

where

purchases

influence

surveys

more

this variable

However.

durable

( 1981).

of purchase

(1981)

house

on an annual

Nerb

non-car

regressions

the

the

EEC

the information

and Pickering tion

On

the use of purchase

rtaults

year.

see also

paper.

limited.

collected

expected

see also Pickering

then.

been

in multiple

and

1974).

for

Ho\ve~er.

series n;ls sipnlficant

The author’s

I~hcrwood

Grcatcmx

regra-

confidence. 2nd

19X0)

OLVII

I’ickcring

Icuds

10 the

conclusions.

(I )

Mean cx ante

(\r.ith

the: exception

purchase

expectation.\

of furniture)

for

different

significantly

higher

frcqucntly

significant

produc1>

for buyer5

arc

than for

non-buyers.

(2)

Purctiasc

analyses

expt’ctations

that successfully

arc

distinguish

buyers

from

in di3criminant

non-buyers.

(_?)

The

items

total

appears

that

important the ratio

the

ratio

interest The

of

the Irvrl

rather

of

purchase

than

in this

a range of HoueLer

probabilities

it

is an

are indicating

an intention

of buying

case may over-predict

planning

horizon.

If

a medium it as actual

reflected

in ;1

ma> give rise to an under-predict-

ratio

purchases.

across

predicted.

of over- or under-prediction.

hand. ;I short

probability

the nature

that

that consumers

expectations

On the other

12 : 3 month

to

12: 3 month

in the product

purchase

purchases.

influence

of

made summed

close

on the likelihood

is high this suggests

term

lwer

of purchase5

encouragingly

influence

such.

ion

number

UZIS quite

Thus

of the information

the

nature

obtained

of

the product

from

purchase

may expec-

tations. Higher

(4)

TV ante probabilities

actual purchases.

ilrt: ilssoci;itd

Lvith

It is illso clear th:tt the consistency

higher

le\ds

of the relationship

%actually purchasing 100

1

/

purchase

over

9 months

purchase

over

6 months

purchase

over

3 months

60 -

of

continues tions

after

related.

the actual indeed.

as

time

period

fig.

2

to u hich the purchase

shw\,s.

strengthen.

kvith the slope of the regression

is allowed

to elrrpse

serves

to emphasize

months

ahead

continuum

(5)

muy

o\w

which

that

to postulate

sound

actual

precise

Given

the high

probability

concentration

v~llue. the majority

of responses

a zero purchase

from

intentions

asking

categories still (6)

buying

to purchase

has not overcome The

apptxred

predictive

expectations this particular

performance

tn \‘ary bct\vtxn

diffcrcnt

with

This

3. 6 or

12

is on

at the zero were still

a

Thus

purchase made by

the shift

dichotomous

on ;I multi-point

aivay answw

numerical

scale

problem.

of purchase

eupectntions

types of consumer.

information

The

vnung

8 actually purchasing

80

to

hold.

(55%)

probability.

questions

of

behaviour

really

of purchases

seems

as more time

are observed.

horizon

consumer

cannot

those \vho had stated

relationship

purchases a time

but

and precise time horizons

the

line increasing.

expecta-

3 months probabilltles .13+.66x Y 6 months Y

probabilities 10+.55x

60 12 months probabilities y .05+.47x

and

more confident were more likely not to achieve their predicted purchases H bile older and higher income consumers ivere more likely to make unanticipated purchases. (7) Although its predictive performance could only be tested over 9 months. a 7-point verbal purchase expectations scale seems to offer an encouraging way of overcoming some of the difficulties with the use of a purchase probability scale. We have already noted that the distribution of expectations on such a scale is different from a probability scale. It also appears to be the case that the proportion of purchases made by those stating that they would certainly not buy \vas lower (25% of total purchases over a 9 month period) and. as fig. 3 shows. the relation between expectations and behaviour was even stronger. There is. however. a non-linearitv in this case which emphasizes the predictive power of the stronger purchase expectations.

Rcficctians

on the use of purchase

cspcctations

~lethodologici~lly there is no doubt that SONIC useful developments have been made over the past 20 years in the collection of purchase especta[ions data. This applies both to the form in Lvhich the question is asked and also to the bays in which the answers are scaled. While the use of a numerical, probability, scale has many attractions it has regretfully to be ildMittCd thilt it hilS not really ilClliCVCCi What W;lS hOpCd of it eSpCciillly in terms of its ability to move 0bjccGvcly likely purchasers a\vay from the zero probability category. A considcrabk number of verbal scales of one sort or anc>ther have been dcvclopcd. Among them. the -I-point verbal scale referred to above may be worth further cspcrimentalion as it does seem to overcome Ihe problem of the distribution of responses and the high proportion of purchases made by zero probability respondents. The cross-sectional predictive performance of purchase expectations remains very good, but it may be asked “of ivhat USC is this if it Jocs11’1 predict the level of purchases effectively‘?“. To this there are t\vo possible responses. First. allhough the time-series : cross-section paradox remains a paradox. at least there is re;1ssur;lnce that the microfoundations of the approach are upheld. Secondly, the identification of prospective purchasers and their particular characteristics nwy i~ll~>\\ more effective target marketing to thilt PilrtiClllilr scgiliCn1. Homwcr.

the

emphasis

forecasting

is

clearly

trends

attention

consumer deface

sentiment. that

Lvhich

purchase

they

is

added.

the standard

than that on buying

well.

basis

HoLvever.

(1974)

some

It should

be

Juster

probabilities offering

to

used on their

a consumer

and

of

been sho\vn

When

when

data. thereby

in

measures

be in order.

purchases.

McNeil

intentions

On this

have normally

on purchase

help

may not seem strong.

to work

are dominated

As

error

will

durahies.

data may still

consumer

but

that

on more generalised

do appear

with

;1 series

information

expectations

are significant

dence measure shown,

for

for consumer

be focussed

expectations

have some association own

need

expectations

should

of purchase

recognised

the

in the demand

the case for collecting Rather.

on

confi-

(1974)

have

data was

In\ver

some grounds

for

hope. Possible

reasons

data should \vording should

for the relatively

be sought

of

the

field

fort

point

to

moving,

house

survey

IIIGIII

of

I’hc

the

the

nic‘;in,

the

distribution

to

l:xpcctationx

cstini;ite

pointccl

to the

ol’tcn

in three

that the

u&

size

probabilitv while

wry

il

sample

of 17,000.

then

it

sample

g et

in the

correct,

silt

Iargc

to bc conGdchanges

ill.

i5 not

in the

VillllC!

01 0T

Buying

Consunic’r

Rc:acarch to cstini;ltc questions

in many ~3~3.

1978).

Consequently insufficient

Illildc of

the

distribution

these shift5

surprising

if

the

ItlL’;lIl

wkrcas

of the change in ilttitlldL’.\

111~11 up

ChilIlgC

The:

in

indeed.

bvith ;I rcasonabk

expectations

adopted have to pick

is

of the

purchase

shifts

this

il

to bc very small

large sampIc.

used sample bizes too small

If

~1mplc

it is not difficult

the direction

(Pickerin

hitherto

meaningful

thaw

to the need for

distribution,

;lrc likely

for a five-figure

figures

This

;I high dcgrec of accuracy the true

;I

to c5tini;itc

:lpprCXlChCS

achieving

of the rcquirctl

for the EEC

11csd

s:imple

points

the true direction

survey

wmpk

rcquircd

with

requires

required

This

over time

size to cstiniatc

of the ot.crall

decision.

:idcquatc1y.

of this is tlliit

COIISC~~ICIICC:

sample

context

durablcs.

to

products.

skcwcd

distribution

consider

that it is d&w

and the state of the stock of existing

to particular

it heavily

it seem

purchase

the

that both the

to be aduptcd

iittitudeh,

to cover the ground With

proccdurtx

in the wider

wl

of expectation5

It stxms

gcncral ccononiic

11ccd

‘I’hcrc is also the question crcd.

scaling

cxpcctation

to the

ovt’rconw.

Furthermore.

of influences

ownership

attitudes

ilIlJ

the

considered.

blc to put the purchase psychological sct‘111s

and

question

bc cnrcfully

poor performance

and. if pasihlc,

the

AIM) the LVil.4

it i5 lihcly prc)grc35 in and

have

with

any rc:liability.

pllKhilSC

expectations

effectively

predict

dence measures

the general

predict

Ieel

much

of purchases

more rffectivel!

but consumer

the mwrment

confi-

about the

mean of sctlrs. The key could therefore be to trv other \vays of shifting the mean of the distribution and/or to find other ~3~s of summarising the distribution There

of the survey

is perhaps

figures

problem,

mand rather

choice betwwn the first purchase

attention

meaningful into

account.

10 have their

is also required

must

actually

the

sales

predictive

be taken

measure

over

the

consumer

de-

to recopnise

the

durabks.

e.g.. the

3 video cassette recorder

tn the time

art‘ asked. A finite

Whcrtxis

variabks

consumc‘r

prcdictivc

should

attitudes.

pcrformnnw

or sudden cvcnts

also

for

hrcnhdo\vns

fin4y

Lvhich

of the responses.

be taken

more

a’cllts

bcc;1usc purchase

spccificd

Ggnificant

full>

art‘ unlikcl)

llllexpcctccl

by

c>fcquipmcnt.

\vill have ;i mow

about

may not bc verb

l-wing gcwral.

afl-cctcci

arc in a hcnsc much mow

uncspcctcd

horizons

time pwod

and may affect the quality

of intervening

3s kvindfalls

cxpcctation5

it i5 likely

impacl

that

011 overall

twhaviour.

Finaily

it appcar5 that diffcrcnt

tc‘ncl 10 over- or under-c5tirii;itc informaticw may

test

It is also important

3 car and buving

to respondents

impact

purchwc

series

supply?

Care

to

and choice bet\vern different

replacing

expectations

The

such

do sales

the USC of individual

attempts

time.

Closer

sucli

in

expectations.

than producer

of competition

about

variable

of purchase

identification

responses.

a problem

as ;1 dependent

performance

nature

also

thcrcforc

content

of

;iIsc~ vary.

purchase If this

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