European Journal of Social Psychology, Vol. 21.261-271 (1991)

Expectancy-value models of attitudes: a note on the relationship between

theory and methodology

PAUL SPARKS, DUNCAN HEDDERLEY and

AFRC Institute of Food Research, Reading Laboratory, Shin field, Reading RG2 9A T U. K.

RICHARD SHEPHERD

Abstract

Concern has been expressed in the literature regarding the method of scoring ‘beliefs ’ within expectancy-value models of attitudes. This paper reviews the major issues and focuses upon some hitherto largely neglectedproblems with scoring methods. Empirical findings from a series of studies concerned with ‘the theory of reasoned action‘ are examined: with a multiplicative Combination of beliefs and evaluations, it is found that bipolar scoring of ‘belief items leads to higher correlations of the summedproducts of beliefs and evaluations with attitudes than are achieved with unipolar scoring. These findings contrast markedly with recently reported research and indicate the important role played by contextual factors (such as belief content and the response scales pre- sented to subjects). It is concluded that more attention needs to be paid to the relationship between conceptual and methodological issues.

INTRODUCTION

Expectancy-value* models appear in various guises (Mitchell, 1974; Feather, 1982) and a sizeable accumulation of research literature relating to such models testifies to their widespread infiuence. Some of this body of literature has focused on theoreti- cal concerns while a major proportion of it has concentrated on the empirical issue of the predictive capabilities of such models (Beach and Beach, 1982). The present paper se‘eks to provide both a theoretical and empirical contribution to some issues that have received considerable attention in the context of expectancy-value models of attitudes.

The central impetus for the present paper is a concern with the way in which theoretical proposals are operationalized in terms of methodological procedures. Specifically, attention will be focused upon Fishbein and Ajzen’s ‘theory of reasoned

+Addressee for correspondence: Dr Paul Sparks, AFRC Institute of Food Research, Reading Laboratory, Shinfield, Reading RG2 9AT, U.K.

OO46-2772/9 1/030261-11%05.50 0 1991 by John Wiley & Sons, Ltd.

Received30 May I990 Accepted 19 October I990

262 P. Sparks, D. Hedderley and R. Shepherd

action’ (Fishbein and Ajzen, 1975; Ajzen and Fishbein, 1980). It is proposed that the methodology employed to assess this theory often creates problems for the scoring of the belief (or subjective probability) component of that model. This, in turn, affects correlational relationships between belief-evaluation and attitude measures. Treating response scales as unproblematic is likely to exacerbate these difficulties. Some research which has employed the ‘theory of reasoned action’ expectancy-value framework will be used to illustrate the problem of selecting scaling methods without due attention to the nature of the data gathered. Ways in which the nature of these data might affect the relative performance of different scoring methods are discussed.

CONCEPTUAL ISSUES

Very generally stated, expectancy-value models are characterized by the guiding notion that a person’s orientation towards a particular course of action is influenced by, (i) the person’s belief that the action will lead to a particular outcome and (ii), the person’s evaluation of that outcome (see Mitchell, 1974, 1982; Feather, 1982, for extensive discussions).

In Fishbein and Ajzen’s ‘theory of reasoned action’ (Fishbein and Ajzen, 1975; Ajzen and Fishbein, 1980; Fishbein, 1980), it is proposed that an estimateofa person’s attitude towards performing a behaviour ( A d can be derived from the summed products of beliefs (bi) about the outcomes of performing that behaviour and the evaluations (ei) of those outcomes. Thus,

n

i l l A, = biei,

where n represents the total number of beliefdnumber of evaluations. The multiplicative relationship here is deemed to correspond to a fundamental

tenet of expectancy-value positions (Mitchell, 1974) which indicates that the value of the criterion measure (here: the attitude measure) is derived from the summed products of expectancies and values. This multiplicative procedure is a sine qua non of the process of ordering ‘utilities’ as a preparation for optimal choice decisions in subjective expected utility theories. Two problems associated with this multiplica- tive relationship warrant mention here.

First, Fishbein and Ajzen interpret belief as synonymous with subjective proba- bility (e.g. Fishbein and Ajzen, 1972, p. 495, 1981, p. 262; Ajzen and Fishbein, 1980, p. 66; Ajzen, 1988, p. 120) and recommend a variety of response scales to measure this construct, For example, in their 1980 publication they recommend a bipolar scale which ranges from -3 (extremely unlikely) to +3 (extremely likely) when ‘modal behavioural beliefs’ are measured. They recommend this method under these circumstances because, ‘Clearly, it would be inappropriate not to give . . . the opportunity to say that the statement is false’ @. 71). However, in the w e where an individual’s own salient beliefs are being measured, they advocate unipolar scoring in suggesting that subjects might be asked to estimate the probability of a particular action leading to a particular outcome (e.g. ‘The chances are - in 100 that my using birth control pills will cause me to gain weight’ (p. 66)) or to indicate how certain they are of a particular action leading to a particular outcome (on a scale with points, ‘not at all certain’ (0), ‘slightly certain’ ( + I ) , ‘quite certain’

Expectancy-value models 263

( + 2), ‘extremely certain’ (+ 3)(p. 67)). Thus, for Fishbein and Ajzen, the recommenda- tion of either unipolar or bipolar scoring of belief items depends upon the ‘individual’ or ‘modal’ origin of those items.

Fishbein and Ajzen (1981; Ajzen and Fishbein (1980)) suggest the necessity of a bipolar method when scoring modal beliefs in order for disbeliefs about negative attributes to contribute positively to attitudes:

This scoring system is essential for an expectancy-value model since it permits a disbelief that an object has a negative attribute to contribute positively to the overall attitude i.e. (-2) x (-2) = +4 (1981, p. 310), (see also Ajzen and Fishbein, 1980, p. 71).

Table 1 sets out the belief X evaluation scores for all possible combinations of belief and evaluation ratings with unipolar and bipolar belief scales. The reader is able to see from this table, for example, how a unipolar scoring of beliefs in the example provided above by Fishbein and Ajzen would lead to a negative contribu- tion to attitude, i.e. (+2) x (-2) = (-4). At a theoretical level, then, Fishbein and Ajzen’s proposal about bipolar scoring appears to be eminently sensible (as does the complementary suggestion that disbeliefs that an object has a positive attribute may contribute negatively to an attitude). From consumer research, Ryan and Bon- field (1975) make the same point with an illustrative example in which a person ‘believes that universal unit pricing will not lead to higher prices for supermarket products’ (p. 124). Ryan and Bonfield point out that if the person negatively evaluates the outcome ‘higher prices for supermarket products’, then a bipolar scoring of beliefs leads to a strong contribution towards a positive attitude towards universal pricing [cf. Table 11. On the other hand, a unipolar scoring of beliefs leads to a product score which indicates a reduction in the favourability of the overall attitude. Furthermore, there exists evidence to suggest that people do, in fact, interpret like- lihood ratings in bipolar fashion (e.g. Bettman, Capon and Lutz, 1975).

Table 1. Scores for different multiplicative scaling methods (belief and evaluation on seven-mint scales)

.tings

(1) Unipolar belief scale (2) Bipolar belief scale Belief

7 -21 6 -18 5 -15 4 -12 3 -9 2 -6 1 -3

’3

-14 - 7 0 -12 -6 0 -10 -5 0 -8 -4 0 -6 -3 0 -4 -2 0 -2 - 1 0 -2 -1 0

7 14 21 6 12 18 5 10 I5 4 8 12 3 6 9 2 4 6 1 2 3 I 2 3 Evaluation

~~ ~

Belief 3 -9 -6 -3 0 2 -6 -4 -2 0 1 -3 -2 - 1 0 0 0 0 0 0

-1 3 2 1 0 -2 6 4 2 0 -3 9 6 3 0

-3 -2 - 1 0

3 6 9 2 4 6 1 2 3 0 0 0

-1 -2 -3 -2 -4 -6 -3 -6 -9

I 2 3 Evaluation

Afternativeiy, since the assessment of belief has been widely held to be synonymous with the assessment of subjective probability (e.g. Mitchell, 1974; Axelson and Brin- berg, 1989), it has been suggested that belief should be treated as a unipolar construct (since probabilities range from 0 to 1) and that scales should correspondingly be scored in unipolar fashion (e.g. Page1 and Davidson, 1984). At a conceptual level,

264 P. Sparks, D. Hedderley and R. Shepherd

this proposal has some immediate intuitive appeal although it remains an open ques- tion as to whether subjects are likely to interpret response scales on belief items as probability scales.

Fishbein and Ajzen (1975) propose a number of different scales to assess beliefs, ‘such as probable-improbable, true-false, yes-no, agree-disagree, or likelpunlikely ’ (Fishbein and Ajzen, 1975, p. 58). Whether subjects interpret these scales as synony- mous has yet to be assessed. Certainly, there is growing evidence that subjects’ responses are sensitive to the options offered to them (e.g. Schwarz and Hippler, 1987). It has to be noted however, in advance of empirical work addressing this issue, that under a unipolar method of scoring beliefs one is faced with the awkward consequence that disbeliefs in negative outcomes contribute negatively towards attitude (e.g. + 1 X - 3 = - 3) and disbeliefs in positive outcomes to contribute posi- tively towards attitudes (e.g. + 1 x +3 = +3).

Second, Schmidt (1973) has pointed out that in order for the procedure of multiply- ing numerical measures of expectancies and values to be valid, both the relevant response scales need to possess a rational zero point (that is, both scales require the presence of points where none of the attribute in question is present). Schmidt suggests that the scales used in expectancy-value models are unlikely to possess such rational zero points and that ‘The nature of the scales used in studies of the expectancy valence model appears to be interval at best’ (op. cit., p. 245) (however, it is not clear that such an interval criterion is normally met (cf Mitchell, 1982): the presence of unequal scale intervals further exacerbates the problems alluded to here). The implications of this are that different assigned values on interval scales will al€ect the overall correlation between expectancy-value and a criterion measure (e.g. attitude). This will not occur with ratio scales that possess absolute zero points. Schmidt presents details of scale transformations and correlation changes to illustrate this point, showing that linear transformations of expectancy (E) and valence (V) scores (of the fonn X + b, ‘where X = the scale score and b = some positive or negative constant’ (p. 244) have substantial effects on the correlation of ZE.V with a measure of effort. He concludes that,

. . . perfectly legitimate changes in the location of the arbitrary zero point on the V and E scales can drastically alter the apparent performance of the multipli- cative model (p. 247) ... a meaningful test of the multiplicative expectancy- valence models is not possible using the measures and operations employed by researchers in this area to date (p. 249).

On Schmidt’s argument, then, ratio scales are seen as a prerequisite for any assessment of the multiplicative relationship proposed by expectancy-value theories.

EMPIRICAL ISSUES

A recent paper by Hewstone and Young (1988) has rekindled attention to the scoring procedures used in experimental work concerned with expectancy-value models of attitudes. Focusing specitically on the work of Fishbein and Ajzen, Hewstone and Young review some of the literature relating to the issue of how ratings on belief measures within that work ought to be scored: that is, whether a bipolar or a unipolar scoring system should be adopted. They emphasize that the predictive validity of

Expectancy-value models 265

the multiplicake method which is employed in this research does not address the problem of the descriptive validity of the theory. Rather, in their paper, they are ‘concerned only with the methodological issues arising from the use of an expectancy- value model of attitudes’ (p. 961).

Hewstone and Young address the issue of whether unipolar or bipolar scoring of beliefs within the framework of the theory of reasoned action leads to superior correlations of Zb,ei with attitude measures. They also assess whether a multiplicative or an additive combination of beliefs and evaluations results in better correlations with attitude measures. They report two studies which demonstrate support for the view that a unipolar scoring of beliefs reveals greater correlations between Cbiei and attitudes than does a bipolar scoring of beliefs.

From the examination of these two pieces of empirical work, Hewstone and Young draw the conclusion that, ‘in both studies, the multiplicative/unipolar belief model was a significantly more powerful predictor of overall attitude than was the multiplica- tivehipolar belief model’ (p. 969).

METHODOLOGICAL AND THEORETICAL CONGRUITY

At this juncture, a number of points need to be made which bear on the issues raised above.

First, it does appear to be the case that unipolar scoring method contravenes the position of the theory of reasoned action since, as Fishbein and Ajzen, infer a h , point out, the scoring method should allow for disbeliefs in negative outcomes to lend a substantial contribution to positive attitudes (see Table 1). Thus, the unipolar belief scale should not be considered as a preferable scoring method in the absence of strong-theoretical arguments in favour of the procedure. Not only does it not meet the theoretical requirements referred to by Fishbein and Ajzen and Ryan and Bonfield but its predictive efIicacy is likely to be highly dependent on contextual considerations (see below).

Second, while Fishbein and Ajzen’s and Ryan and Bonfield’s point (that a combi- nation of negative belief and negative evaluation should permit a positive contribution to overall attitude) is essentially a sensible one, it is not immune from problems. of its own. By way of illustration, the example offered by Ryan and Bonfield (above) has been called into question by Bagozzi (1984) who suggests that the belief that ‘universal unit pricing will nor lead to higher prices’ is more likely to reflect a ‘neutral’ belief than a ‘negative’ belief (e.g. 0 rather than - 3 on a bipolar scale). Furthermore, and allied to Bagoui’s objection, there is the supposed symmetrical contribution to overall attitude produced by believed and disbelieved items. This is a problem for the following reason. Suppose expensive foodstuffs are negatively evaluated (-3) and cheap foodstuffs are positively evaluated (+3). If a person believes (+3) that a foodstuff is expensive (- 3) this will lead to a contribution to overall attitude of -9. If a person does not believe (-3) that a foodstuff is expensive (-3), this will lead to a contribution to overall attitude of 9, a score similar to that produced by the belief (+ 3) that a foodstuff is cheap (+ 3) (see Table 1). In terms of contribution to overall attitude, a disbelief that a foodstuff is expensive is thus deemed to be equivalent to a belief that a foodstuff is cheap. This is logically incorrect (since the person might believe the foodstuff to be neither expensive nor cheap). Moreover,

266 P. Sparks, D. Hedderley and R. Shepherd

it is also likely to be often incorrect in practice that a person who disbelieves that a foodstuff is expensive will believe that foodstuff to be cheap. The essence of the problem is that a disbelief rating does not indicate what is believed (and what is believed is a crucial component of ‘the theory of reasoned action’). The unipolar scoring method does not, of course, produce this symmetry between belief x evalu- ation scores for believed and disbelieved items. However, even here, the relationship between belief X evaluation scores for believed and disbelieved items is erroneously considered to be fixed rather than variable. Under neither of the scoring schemes is the inherent problem of inferring beliefs from disbeliefs adequately addressed.

Third, it should be emphasized that we concur wholeheartedly with the view that the predictive capabilities of the product of beliefs and evaluations has little sigmfi- cance for the ‘theoretical meaningfulness’ of the multiplicative procedure (Schmidt, 1973, p. 246; see also Fischhoff, Goitein and Shapira, 1982; Mitchell, 1982; Eiser and van der Pligt, 1988). For predictive purposes, however, it is likely that the utility of the multiplicative method will be partly dependent upon the congruence of the scoring methods with the response options offered to subjects. For example, it is not at all obvious that ‘belief ratings, ‘agreement’ ratings, ‘probability’ ratings and ‘likelihood’ ratings are interpreted by subjects as synonymous (studies which have addressed ‘the theory of reasoned action’ have employed a variety of such measures). There may well be situations where different response options are best accompanied by different scoring methods. Thus, assessments of the problems concerning the lack of a rational zero point and unequal scale intervals are likely to be intensified by any lack of congruence between different scales. The improved predictions pro- vided by the unipolar method in the work reported by Hewstone and Young (1988) should therefore not be treated as representative of a general empirical trend which is independent of the type of data gathered. Rather, the predictive performance of unipolar and bipolar scoring methods is likely to be influenced, for example, by attitudes to ‘X’ in relation to attitudes to ‘not-X’, the number of alternatives to ‘X’ which possess similar attributes to ‘X’, and also, perhaps, by the options provided on the response scales. As an initial line of enquiry to examine some of the above issues, analysis of

existing data sets was carried out using both bipolar and unipolar scorings of belief ratings. The main purpose in this analysis was to investigate our suspicion that the bipolar scoring method is theoretically superior to the unipolar method because of the positive contribution towards overall attitude which derives from a combi- nation of negative belief and negative evaluation which occurs with that method (and despite problems with the adequacy of the inverse proportionality in the scoring of ‘believed’ and ‘disbelieved’ behavioural outcomes). Our investigation addressed the empirical dfects of scales and subject matter differing from those used by Hew- stone and Young.

METHOD

We examined data from seven studies, scoring belief scales in both unipolar fashion (i.e. from +1 to +7) and in bipolar fashion (i.e. from -3 to +3). In addition to looking at findings using the standard multiplicative procedure (beliefs x evalu- ations), we also investigated the additive model (also included by Hewstone and

Expectancy-value models 267

Table 2. Summary of studies and belief scales Reference Subject matter Belief scale Belief source Towler and Shepherd Eating meat, meat ‘Strongly disagree’ Elicited in the (Under editorial products, dairy to ‘strongly agree’ manner prescribed review) products and fried by Ajzen and Fishbein

Towler and Shepherd Eating meat, meat ‘Strongly disagree’ Same items as in (In preparation, a) products, dairy to ‘strongly agree’ above study

food (1980) (n = 34)

products and fried food

Shepherd (1988) Drinking low-fat ‘Strongly disagree’ Items adapted from milk to ‘strongly agree’ Tuorila (1987)

Towler and Shepherd Eating potato chips ‘Strongly disagree’ Elicited in the (In preparation, b) to ‘strongly agree’ manner prescribed

by Ajzen and Fishbein (1 980) (n = 22)

Shepherd (1987) Consumption of ‘Strongly disagree’; Items derived from savoury snackfoods ‘disagree’; ‘neutral’; the literature

‘agree’; ‘strongly a m ’

Shepherd (1987) Use of table salt ‘Disagree’ to ‘agree’ Elicited in the manner prescribed by Ajjzen and Fishbein (1 985) (n = 24)

Anderson and Healthier eating ‘Strongly disagree’ Items derived from Shepherd (1989) during pregnancy to ‘strongly agree’ pilot interviews

Excepting the ‘savoury snackfoods’ study, all belief scales have seven points and response options arc given only at scale end-points.

(n = loo)

Young (1988)) which simply involves summing the belief and evaluation ratings. The data derived from both published and yet-to-be published studies (the details of these studies are shown in Table 2). These studies were united by the common theme of people’s beliefs about, and attitudes towards, the consumption of various foodstuffs.

RESULTS AND DISCUSSION

Within the seven studies that we examined, we were able to make 13 comparisons of the unipolar and bipolar scoring procedures (using Williams’ t2 statistic (Steiger, 1980)). Of these 13 comparisons, 10 revealed that bipolar belief scoring resulted in higher Zbiei-attitude correlations than were achieved with unipolar scoring (eight of these comparisons were significant at the 1 per cent level; the other two were significant at the 5 per cent level), two revealed no significant differences between the two methods and one revealed that unipolar belief scoring resulted in higher Cbiei-attitude correlations than were achieved with bipolar scoring (significant at the 1 per cent level) (see Table 3 for a summary of the findings). We suspect that this latter comparison which favoured unipolar scoring may be attributed to the particular structure of the belief scale in that study. That is, the scale end points

268 P. Sparks, D. Hedderley and R. Shepherd

were not marked with qualifying terms such as ‘extremely’ or ‘very’: subjects may consequently have interpreted intermediate points as only indicating degrees of agree- ment (or, conceivably, only degrees of disagreement). The interpretation of intermedi- ary scale points is likely to be easier where end-points indicate extremes of agreement and disagreement and where scales are more obviously intended to balance around the mid-point. The bipolar multiplicative procedure also yielded higher correlations than the additive model in nine out of the 13 comparisons (the remaining four comparisons revealed no significant differences). The unipolar multiplicative pro- cedure produced higher correlations than the additive model in five out of the 13 comparisons, one comparison showed a higher correlation for the additive model and the remaining seven comparisons revealed no significant differences (see Table 3).

Within the work reported here, then, there is a clear trend for bipolar scoring of belief items to result in higher Zb&-attitude correlations than does the unipolar scoring of those items. Our findings are therefore quite different from those of Hew- stone and Young (1988) who present their own empirical evidence to suggest that the unipolar scoring method leads to higher Ebiq-attitude correlations. Moreover, at a theorttical level, the unipolar scoring system does not appear to yield a more justifiable scoring system. What is thus required is an assessment of when and why a (multiplicative) unipolar scoring system for beliefs leads to improved Zbie,attitude correlations. Consequently, the examination of the following issues is an important area for future research: (1) the relationship between beliefs and disbeliefs; (2) the relationship between evaluations of outcomes and evaluations of ‘not-outcomes’; (3) the compatibility of the two methods of scoring beliefs with difference configu- rations of beliefddisbeliefs and outcome evaluations produced within different con- texts.

It should be emphasized that the conclusion to be drawn from this research is not that our findings furnish an indication of which multiplicative procedure should be universally adopted with ‘belief‘ scales for greater predictive success. Following the work reported here, we suggest that what is required is a more careful examination of the nature of data gathered in questionnaire research and the response options which are offered to subjects. The conditions under which unipolar or bipolar scoring of ‘belief‘ items lead to higher Zbiei-attitude correlations necessitate more attention for a fuller understanding of the relationship between measures of belief, value and attitude. The descriptive validity of any combination of belief (expectancy) and value at an idiographic (within-subjects) level is of course not addressed in such research. However, an assessment of the empirical adequacy of combinations of measures of belief and value in predicting measures of attitude is not merely of theoretical interest (because of the widespread influence of expectancy-value models). Rather, it is to be hoped that increased conceptual attention to this issue will augur well for a concerted effort in addressing the nature of the relationship between empirical measures of psycholo@cal constructs (such as beliefs, values, attitudes) and the nature of psychological processes themselves.

ACKNOWLEDGEMENTS

The authors would like to express their thanks to Annie Anderson and Gary Towler for providing data for analyses reported in this paper.

Tabl

e 3.

Sum

mar

y of

fin

ding

s com

parin

g co

rrel

atio

n co

ellic

ient

s bet

wee

n I;b

iei a

nd a

ttitu

des

usin

g bi

pola

r, un

ipol

ar a

nd a

dditi

ve s

corin

g m

etho

ds

for b

elie

f ite

ms

Sour

ce

Subj

ect

Cor

rela

tion

coef

ficie

nts (

r) fo

r (a

) Bip

olar

(b

) Uni

pola

r (c

) Add

itive

D

iffer

ence

@) b

etw

een

tI sc

orin

g sc

orin

g co

mbi

natio

n a-

b a-

c b-

c

Tow

ler a

nd S

heph

erd

Mea

t 240

0.69

0.56

0.60

0.0 I

0.05

ns.

(Und

er ed

itoria

l M

eat p

rodu

cts

240

0.62

0.54

0.48

0.05

0.05

n.s.

revi

ew)

Dai

ry p

rodu

cts

240

0.63

0.53

0.54

0.0 I

0.05

n.s.

Frie

d fo

ods

240

0.54

0.55

0.56

ns.

n.s.

ns

. To

wle

r and

She

pher

d M

eat

529

0.12

0.52

0.54

0.01

0.01

n.s.

(in p

repa

ratio

n, a

) M

eat p

rodu

cts

525

0.64

0.58

0.41

0.01

0.01

0.01

Dai

ry p

rodu

cts

5 34

0.58

0.49

0.58

0.01

n.

s. 0.01

Frie

d Fo

ods

532

0.59

0.50

0.4 1

0.01

0.01

0.

01

P Sh

ephe

rd (1988)

Low

-fat m

ilk

103

0.80

0.69

0.71

0.0 I

0.05

n.s.

Tow

ler a

nd S

heph

erd

Pota

to c

hips

288

0.42

0.4 I

0.28

n.s.

0.01

0.0 1

B

(In

prep

arat

ion,

b)

0

Shep

herd

(1987)

Savo

ury s

nack

food

s I32

0.57

0.46

0.27

0.05

0.0 I

0.0 I

9 Sh

ephe

rd (1987)

Tabl

e sal

t I17

0.59

0.73

0.56

0.01

n.s.

0.01

And

erso

n an

d H

ealth

ier e

atin

g 95

0.32

0.16

0.23

0.05

n.s.

n.s.

Shep

herd

(1989)

in p

regn

ancy

8 $ & 3 i;-

270 P. Sparks, D. Hedderley and R. Shepherd

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Shepherd, R. (1987). ‘The effects of nutritional beliefs and values on food acceptance’. In: Solms, J., Booth, D. A., Pangborn, R. M. and Raunhardt, 0. (Eds) Food Acceptance nnd Nutrition, Academic Press, London, pp. 387402.

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