article sacrifice (igss)

8/14/2019 Article Sacrifice (IGSS)

1/24

AN EMPIRICAL STUDY ON THE CONCEPT AND

MEASUREMENT OF PERCEIVED SACRIFICE

Md. Humayun Kabir Chowdhury

ABSTRACT

How do consumers cope with the decisions they must make, some of which involve

difficult tradeoffs? In general, it has been argued that the decision making process

significantly depends on the value perceptions that results from the cognitive tradeoff

between perception of quality and sacrifice. Perceived sacrifice is defined as: consumers

perceptions of the degree of pain originated to acquire the product from the amount of

money paid, and the time and labor spent. In this study, a measurement system for

perceived sacrifice and its components is developed for electronic product class. A total of

five items were generated. The scale met standards for the measurement of reliability and

validity. Confirmatory factor analysis was performed to assess the validity whether the scale

is an appropriate operational definition of the construct. The paper concludes with a

discussion of the limitations of this study.

INTRODUCTION

It has been argued that perception of value results from the cognitive tradeoff

between perceptions of quality and sacrifice. Cox (1962) was one of the first

investigators to develop a model of the consumer product evaluation process where he

hypothesized that consumers tend to evaluate cues on two dimensions: predictive

value and confidence value. Predictive value reflected the probability that the cue was

associated with an attribute of the product. Confidence value reflected the certainty

that the consumer felt about his ability to interpret and use that cue. Since then,

1


2/24

several researchers have tested models of consumers perceptions of value with regard

to using several different types of cues. In the past couple of decades a large number of

articles, perhaps more than any other cues, conveyed evidence of price as the indicator

of quality and perception of value (Curry and Riesz 1988; Dodds and Monroe 1985;

Grewal et al. 1998; Monroe and Krishnan 1985; Monroe 1976; Shimp and Bearden 1982;

Szylillo and Jacoby 1974; Wheatley and Chiu 1977). It has been argued that price is

what is given up or sacrificed to obtain a product.1 The role of price has been studied in

economics as a demand/supply equilibrium, monopoly, duopoly, and oligopoly;

psychology as an information cue; and marketing as discounting, penetrating and/or

skimming with other different perspectives. However, recent price models acknowledge

that monetary price is not the only sacrifice made by consumers to acquire a product2 .

Time costs, search costs, and physic costs all enter either explicitly or implicitly into the

consumers perception of sacrifice. To some consumers, the monetary sacrifice is

pivotal: some buyers will invest hours traveling to different stores to obtain the best

bargains. To these consumers, anything that reduces the monetary sacrifice will

increase the perceived value of the product. Less price-conscious consumers will find

value even at the expense of higher costs because time and effort are perceived asmore costly. Many consumers, especially working people in the first world, consider

time an important commodity (Aoki 1994; Bearden and Shimp 1982; Dodds, Monroe,

and Grewal 1991; Zeithaml 1988). Therefore, monetary sacrifice is not the only

sacrifice, as operationalized in most of the previous research, consumers usually incur

to acquire a product.

How do consumers cope with the decisions they must make, some of which

involve difficult trade-offs? Information-processing approach to the study of consumer

choice has argued that rational choice theory3 is incomplete and/or flawed as an

approach for understanding how consumers actually make decisions (Bettman, Luce,

2


3/24

and Payne 1998). The sequential model, as described by Peter and Olson (1993), shows

that product adoption or purchase can be seen as a sequence of behavior, from

prepurchase to purchase and then postpurchase. A common early stage in the

purchase occurs when consumers come into contact with information about products,

stores, or brands. This stage includes behaviors such as reading or observing

newspapers, magazines; listening to radio commercials, watching TV commercials; and

talking to sales persons and friends. Thus, consumers start sacrificing when they start

contacting information, then they gradually proceed to collecting fund, contacting

suitable store, getting contact with products, acquire the product in exchange of

money, and last of all make the consumption. Here, it seems that the stage acquiring

the product in exchange of money directly related to the sacrifice that consumers

make in a purchase. But, a careful look on all the stages reveals that other stages also

require time and energy. These are also the sacrifice that consumers are employing in

order to obtain a product. Previous studies only have considered perceived sacrifice in

the equal meaning of monetary sacrifice in operationalyzing the construct. However, as

long as the sacrifice is concerned, research should incorporate sacrifices made with

regard to time, effort and search in addition to price consumers employ in a deal. Thus,

perceived sacrifice based on the above discussion is defined in this study as:

Consumers perception of the degree of pain originated to acquire the product from the

amount of money paid, and the time and labor spent4

BACKGROUND

Zeithaml (1988) specified a model in which she defined the relationships of

perceived sacrifice, perceived quality and perceived value based on an exploratory

study and other conceptual work from the literature. She argued that there is a

remarkable gap between actual price and perceived price, making it important to

3


4/24

understand how consumers encode prices of products. Nonmonetary costs- such as

time and effort- must be acknowledged. Anything that can be built into products to

reduce time, effort, and search costs can reduce perceived sacrifice and thereby

increase perception of value. To differentiate between proposed relationships and

empirically supported relationships, discussion of each proposition is divided into two

parts. First, propositions are developed on the basis of the qualitative data from an

exploratory study and other conceptual work from the literature. Second, for each

proposition, empirical evidence that supports and reflects the proposition is reviewed.

Finally, Zeithaml concluded that research on how consumers evaluate product

alternatives should be expanded beyond the price-perceived quality relationship.

Dodds, Monroe, and Grewal (1991) proposed a model in which they afford that

(a) perceived quality and perceived sacrifice are the antecedents of perceived value,

i.e., consumers perceptions of value are based on a trade-off between product quality

and monetary sacrifice; and, (b) brand name, store name, and price are the

antecedents of perceived quality and perceived sacrifice, i.e., consumers perceptions

of product quality and monetary sacrifice can be based on extrinsic cues, such as price,

brand, and store name. Dodds et al. tested direct and indirect relationships between

three extrinsic product cues and two evaluative variables suggesting that price, brand

name, and store name are associated with quality and value perceptions. The design of

the experiment allowed analysis of the relative differential impacts of price, brand

name, and store name on the three dependent variables. They found that when price

was the only extrinsic cue available, the subjects clearly perceived quality to be related

positively to price. When other extrinsic information was present, the results were less

persuasive. Finally, they argued and presented the conceptual basis for: (1) isolating

the theoretical reasons for when buyers use price, brand, store, or intrinsic product

information as indicators of quality, (2) determining how quality perceptions influence

4


5/24

value perceptions, purchase intentions, and product choice, and (3) how monetary and

non-monetary perceived sacrifices influence value perceptions, purchase intentions,

and choice.

Teas and Agarwal (2000) tested a model in which perceived quality and

perceived sacrifice mediate linkages between (a) brand name, store name, and price

and (b) consumers perceptions of value. They used two 5-point items (strongly

disagree/strongly agree) to measure perceived sacrifice. Description of the items were:

(1) If I purchased the (watch/calculator) for the indicated price, I would not be able to

purchase some other products I would like to purchase now; and (2) If I purchased the

(watch/calculator) for the indicated price, I would have to reduce the amount of money I

spend on other thinks for a while. Teas and Agarwal (2000) extended the Dodds et al.

(1991) study by examining linkages specified but not tested in the Dodds et al (1991)

study (i.e., linkages involving perceived sacrifice) and by examining the degree to

which perceived quality and sacrifice mediate the relationships between the extrinsic

cues and perceived value. In their model, country name was specified as an extrinsic

cue and as a moderator variable. Their empirical results demonstrate that price, brand

name, and store name are associated with quality and value perceptions. Their study

results revealed that price continues to be a significant quality cue in the presence of

other extrinsic quality cues. The country of origin cue was found to have a significant

main effect on the perceived quality but failed to find support on effects of country of

origin as a moderator variable.

Therefore, to get a clear perspective on the role of perceived sacrifice in

consumer value assessment research, studies are required to incorporate multifaceted

conceptual and operational definitions of perceived sacrifice5 . Based on the previous

conceptual studies, two dimensions of perceived sacrifice can be offered (see Table 1).

5


6/24

THE PROBLEM

As aforementioned, Zeithaml (1988) developed propositions of the related

constructs on the basis of the conceptual work and qualitative data from an explorative

study. Primarily, she obtained evidence from the past research and then made

justification by collecting data on open-ended questions from company, focus group,

and in-depth consumer interviews. The questions pertained to issues such as company

knowledge about quality and value perceptions of consumers, ways the company

determined those perceptions, and how quality and value were communicated to

consumers. Although the model developed our knowledge about producers value

judgment and consumers value perceptions, still the study contains certain caveats

because of its non-experimental nature. Specifically, Zeithamls study failed to establish

the relationship between give and get components of the model. Moreover, her

exploratory study results merely confirm the causal relationships, determinants and

existence of non-monetary sacrifice in the model.

Dodds et al. (1991) incorporated perceived sacrifice in their model. In

describing their model they argued that price can be an indicator of the amount of

sacrifice need to purchase a product. Higher prices represent a monetary measure of

what must be sacrificed to purchase the good, leading to a reduced value.

Consequently, perception of value is a cognitive tradeoff between perception of quality

and perception of sacrifice. However, they specified theoretical explanations and

predictions of why and how monetary sacrifice influences consumer perceptions of

value but surprisingly neither they included non-monetary sacrifice in their model nor

operationalized the monetary sacrifice during the experiment.

The only study in this sphere that operationalized perceived sacrifice in the

experiment is the article by Teas and Agarwal (2000). The concept of sacrifice was

operationalized as a measure of monetary sacrifice. For the internal validity purpose,

6


7/24

they measured perceived sacrifice from a budget constraint perspective. This measure

allowed them to assess the possibility that the perception of sacrifice will vary

depending on an individuals financial situation. Thus, they used two items to tap the

monetary sacrifice construct. Although the theoretical explanations provided in their

study are quite insightful, they also did not consider all facets of this construct.

Therefore, to date, no study has appeared that test and validate an all-

inclusive theory of perceived sacrifice construct. To test the adequacy of the theory and

operationalizing the construct, measures of the construct were needed.

METHODOLOGY

Measures with regard to monetary sacrifice of this study will be the same as

measure scales used in the research by Teas and Agarwal (2000). Sacrifice, other than

monetary those are related to time and effort will be constructed for this study (see

Table 2). The test was performed with a total of 103 students from the Faculty of

Business Administration at YNU with a prior permission of the Professor. Data collected

on three products, computer, TV, and camera because of their familiarity to student

respondents. Because perceived sacrifice requires experience of purchasing similar

products, students were first asked if they ever bought products from that category. All

the students received questionnaire but who did not have experience of buying the

product were requested to refrain from answering. Respondents were then instructed to

express their perception of sacrifice. The questionnaire took about 5 minutes to answer.

Two third of the total sample was males and one third was females. Around 11% of the

respondents were non-business majors. Respondents of business majors were deemed

likely to have been exposed to the concepts considered in this study. The probability

that the students could have anticipated hypothesis being tested, conceivably

producing biased results for the study. To confirm that such bias did not occur, an

7


8/24

ANOVA was conducted in which responses of all business majors were compared to the

combined responses of non-business majors representing in the sample. However,

neither of the mean differences was deemed large enough to produce any bias in the

overall results of the study. Henceforth, it was concluded that no bias was introduced

into the study.

In a theoretical study, Abe (1987)6 deliberately explained various

measurement aspects to tap the validity of a construct. In an international consumer

research setting, Abe (1993)7 mentioned the importance of concept development,

concept operationalization, measure equivalence, and data analysis. Thus, measures of

the study were developed considering the theoretical explanations provided by Abe

(1987, 1993). Procedurally, reliability of the scales was assessed first and when the

reliability of the measures had been established, a structural model was tested. In

doing so, the steps taken to develop the measures were:

Step 1. Internal scale reliability

Step 2. Empirical Analysis of the facets

Step 3. Criterion-related validity and convergent validity

Step 4. Construct Validity by confirmatory factor analysis

INTERNAL SCALE RELIABILITY

A total of five items were generated. First two of these questions about

monetary sacrifice were borrowed from the article of Teas and Agarwal (2000) and the

rest about non-monetary sacrifice were constructed for this study. Because perceived

sacrifice is hypothesized to possess two dimensions (monetary and non-monetary),

reliability was first checked for each dimension. Alpha values were .7870 for monetary

sacrifice items, .8903 for non-monetary items, and .7803 when all the items were

brought into the analysis (see Table 3).

8


9/24

As can be seen in the Table that the alpha values indicate good internal

consistency among items within each dimension (Cronbach 1951). Furthermore, the

combined reliability for the 5-item scale was quite high8 . Therefore, the 5-item scale

was considered to be ready for further testing.

EMPIRICAL ANALYSIS OF THE FACETS

Construct validity measures whether a scale is an appropriate operational

definition of an abstract variable, or a construct. Conducting a factor analysis on a

single summated scale will show whether all items within the summated scale load on

the same construct, or whether the summated scale actually measures more than one

construct (Churchill 1979; 1994). Factor analysis is helpful in identifying tentative

dimensions, as well as suggesting items for deletion and places where items should be

added. A factor analysis using the principal component method can be used to identify

and measure the intensity of the common element. The researcher can specify both the

number of dimensions in the construct and the specific items or scales that are

hypothesized to load on those dimensions a priori.

Factor analysis was performed on these 5 items. A principal components factor

analysis using a varimax with Kaiser normalization technique generated 2 dimensions

with clear factor patterns. All the items for the same dimension loaded high on the

respective factor and low on the others (see Table 4).

CRITERION-RELATED VALIDITY AND CONVERGENT VALIDITY

Criterion-related validity investigates the empirical relationship between the

scores on a test instrument (predictor) and an objective outcome (the criterion). The

most commonly used measure of criterion-related validity is a validity coefficient, which

is the correlation between predictor and criterion scores. An item was constructed

9


10/24

during the questionnaire administration that measured overall perceived sacrifice

served as criterion variable. The item was used to check criterion-related validity by

correlating average scores of all the perceived sacrifice measure items with scores for

the item assessing overall perception of sacrifice (Parasumaman et al. 1988;

Zeichkowsky 1985). Correlation between average scores of all the items and perceived

overall sacrifice was .79 (significant at the 0.01 level). A reasonably high value of the

correlation between average scores of all the items and perceived overall sacrifice

indicates the possession of criterion-related validity of the scale items.

The scales validity was also determined empirically by examining its

convergent validity as advocated by Parasuraman et al. (1988). A one-way ANOVA was

performed with ratings of the overall sacrifice measure as treatment variable and the

average values of the 5-items as the dependent variable. More specifically, the

treatment variable was obtained by constructing an item that measured respondents

overall perceived sacrifice to buy the product. Respondents rated overall perceived

sacrifice by checking one of seven categories extremely likely to-----not likely at all.

Duncans Multiple Range Test revealed significant differences between groups.

Duncans Multiple Range Test revealed differences between groups although all the

groups were not significantly different from each other. Each mean was different from

those of the others (see Table 5). This confirms the convergent validity of the items was

distinguished between different levels of perceived value.

CONSTRUCT VALIDITY BY CONFIRMATORY FACTOR ANALYSIS

According to Churchill (1979),A fundamental principle in science is that any

particular construct or trait should be measurable by at least two, and preferably more,

different methods. Otherwise the researcher has no way of knowing whether the trait is

anything but an artifact of the measurement procedure (pp. 70). The results of any

10


11/24

single analysis are always less than perfectly dependable. The problem is especially

pernicious because the results of a single factor analysis usually look plausible. But

plausibility is no guarantee of validity or even stability (Wells and Sheth 1971). Thus,

Confirmatory Factor Analysis using Amos 4.0 was performed to determine the construct

validity (see Figure 1). If the five-items included in the instrument measure the two

distinct dimensions identified in the previous sections, then the survey data should

produce results that conform to the model.

Measurement Model and Analysis:

The two dimensions identified in Figure 1 are not directly observable; they are

theoretical constructs called common factors. The model supposes the first two items

(Item 1 and Item 2) depend on the unobserved variable called monetary sacrifice. In

addition, the rest of the items (Item 3, Item 4, and Item 5) depend on the other variable

called non-monetary sacrifice. Err 1 through Err 5 are unique factors those represent

any and all influences on the variables that are not shown elsewhere in the path

diagram. The path coefficients leading from the common factors to the observed

variables are often called factor loadings. In the confirmatory factor analysis, the fit of

actual data to the theoretical model is computed by constructing a covariance matrix 9

If the data fit the model, confirmatory factor analysis can supply estimates of the factor

loadings, the correlations among the factors, and the variances of the observed items.

Chi-square goodness-of-fit statistic is commonly used to measure the fit of the

proposed models. It is computed under the null hypothesis that the observed

covariances among the answers came from a population that fits the model. A

statistically significant value in the goodness-of-fit test would suggest that the data do

not fit the proposed model.

11


12/24

Results of the Analysis:

As the Chi-square value (7.125, p = .129) shown at the upper right corner of

the figure, the model fits the data reasonably well. The squared multiple correlations

can be interpreted based on the variance explained with regard to the specific items.

Bagozzi and Yi (1988) suggest that variance extracted should be greater than or equal

to .50. 70%, 61%, 57%, 77%, and 89% of the variance of the items respectively are

accounted for by the variance in the common factors (Monetary and Non-monetary).

The remaining percentage of the variance cannot be explained by this model and are

attributed to the unique factors (Err 1 through Err 5). In this model, Item 2 and Item 3

for accounting low variance should be regarded as a lower-bound estimate of the

reliability (Anderson 1987). However, Factor weights (.84, .78, .76, .88, and .95) of all

the items to explain the latent variables are quite satisfactory.

SUMMERY AND LIMITATIONS

In fact, the construct perceived sacrifice is difficult to define and measure

because of its indistinct characteristics. Sometimes we wish to go for having our dinner

to a distant place but sometimes not, sometimes we spend 2000 yen for our dinner but

sometimes that seems very costly. The purpose of this study was to clarify perceived

sacrifice based on its monetary and non-monetary dimensions and to create a reliable

and valid measure for the facets of perceived sacrifice. Scale items were developed

based on Teas and Agarwal (2000) and other literature. Internal scale reliability was

obtained to check the internal consistency of the items, Criterion-related validity of the

scale were checked to investigate the empirical relationship between the scores on the

predictor and the criterion and convergent validity to see the extent to which the score

converged with other methods designed to measure the same construct. Finally,

validity was assessed whether the scale is an appropriate operational definition of the

12


13/24

construct. From the data analysis, we conclude that the perceived sacrifice profile

should have two distinct facets.

Scale items those measured monetary sacrifice were borrowed from Teas and

Agarwal (2000) and the items those measured non-monetary sacrifice were constructed

based on published discussions of perceived sacrifice (Dodds et al. 1991; Monroe and

Chapman 1987; Teas and Agarwal 2000; Zeithaml 1988). Therefore, missing from the

scale development is the test of content validity. However, one of the purposes of this

study was to see empirically the construct that could lead to evolving knowledge and a

sophisticated understanding of its contents. Henceforth, the content validity of the

construct might be improved over time by further theory building and theory

verification. However, the findings are based on a limited set of brands and hence

generalization beyond that set should be made with caution. Furthermore, animportant limitation lies on the student sample that has been used in this study. Some

scholars have generally cited threats to external validity as their primary concern,

arguing that students are atypical of the general population, and that any findings

based on student samples may therefore not be generalizable to other populations.

However, some scholars disagree on this issue arguing that this situation is particularly

desirable when researchers are engaged in theory testing, or are testing specific

theoretical predictions (Oakes1972). All that is required is that the sample be chosen to

allow a test of the theoretical predictions under consideration. Because the primary

focus of this study was a theory test and not effects generalization, considerations of

internal validity were paramount and a student sample was appropriate (Calder et al.

1982; Cook and Campbell 1975). Concerns about external validity were secondary.

Further research is needed to develop formalized theory of perceived sacrifice

and examine the construct validity based on the theory developed. In the current study,

two dimensions of perceived sacrifice have been considered and found significant

13


14/24

results. However, content validity is specially required to measure the actual

dimensionality of the construct. It might be that the construct is three or more

dimensional instead of two. The dimensions might be different in different product

categories.

14


15/24

Table 1

Perceived Sacrifice Dimensions

Dimensions Definitions Examples

Monetary

Sacrifice

Non-

monetary

Sacrifice

Sacrifice to obtain a product that reduces

consumers wealth

Sacrifice to obtain a product that is not

directly related to money but valued

equivalently by the consumer

Currency like Yen,

Dollar, Mark, etc.

Time Costs, Search

costs, Psychic costs,

etc.

Table 2

Description of the Item Scale

1.

2.

Monetary Sacrifice:

If I purchased the product, I would not be able to purchase some other

products I would like to purchase now.

If I purchased the product, I would have to reduce the amount of money I

spend on other things for a while.

15


16/24

3.

4.

5.

Non-monetary Sacrifice:

If I purchased the product, I would need to make an extra effort in the

beginning to learn about the product that would have to reduce my energy I

could employ on other tasks.

If I purchased the product, I would have to compare different alternatives of

the product at more than one store before the deal that would have to reduce

the effort that I could use for other businesses.

If I purchased the product, I would have to search for the better product that

would have caused the reduction of my time I could use for other purposes.

Table 3

Reliability Coefficients of Perceived Sacrifice Measures

Dimension Cronbach

Alpha

Items

Corrected

Item-Total

Correlation

Alpha if

Item

Deleted

16


17/24

Monetary

Sacrifice

Non-monetary

Sacrifice

Perceived

Total Sacrifice

.7870

.8903

.7803

Item 1

Item 2

Item 3

Item 4

Item 5

All Items

(1)

(2)

(3)

(4)

(5)

.6550

.6550

.7152

.8003

.8540

.4005

.4028

.6552

.6538

.6821

n/a

n/a

.9027

.8349

.7901

.7897

.7842

.7045

.7033

.6974

Table 4

Principal Component Factor Analysis Results

of the 5 Perceived Sacrifice Measure Items

Factor 1 Factor 2 Extractio

n

Item 1

Item 2

Item 3

Item 4

Item 5

.126

.107

.844

.915

.940

.896

.907

.193

.029

.027

.819

.834

.750

.845

.888

17


18/24

The principal component factor analysis results show that all the 5 items loaded on 2 factors

Table 5

Duncans Multiple Range Test

Based on the Item Overall Perceived Sacrifice

TOTSAC

N Subset for alpha = .051 2 3 4 5

1.00

2.00

3.00

4.00

5.00

6.00

7.00

Sig

9

11

27

8

33

7

8

1.7143

2.6750

.061

2.6750

3.5000

.105

3.5000

4.2857

4.3273

. 124

4.2857

4.3273

5.1500

. 108

5.1500

5.7000

.276

Means for groups in homogeneous subsets are displayed. The group sizes are

unequal.

The harmonic mean of the group sizes is used.

.

18


19/24

NOTES

19

MonetarySacrifice

Nonmenetary

Sacrifice

.70

Item1

.61

Item2

.57

Item3

.77

Item4

.89

Item5

.84

.95

.26

Figure 1

Chi-square = 7.125 (4 df)p = .129

a) Latent variables are circled and operationalizations of those latent variables are within

b) Degrees of Freedom = ( Number of Distinct sample moments - Number of distinctparameters to be estimated)

.88

.76

.78

Err 1

Err 2

Err 3

Err 4

Err 5

Standardized Estimates ofthe Confirmatory Factor Analysis


20/24

REFERENCES

Abe Shuzo (1987), Construct Validity and LISREL, in Marketing Theory and

Measurement, Okuda Kazuhiro and Abe Shuzo ed. Chuo Keizai Sha 27-46

Abe Shuzo (1993), Methodological Problems in Cross-cultural Consumer Research,

Yokohama Keiei Kenkyu, 13, No. 4, 31-44

Anderson, James C. (1987), An Approach for Confirmatory Measurement and Structural

Equation Modeling of Organizational Properties, Management Science, 33(4),

525-41

Aoki, Michiyo (1994), Evaluation of Green Products- The Process of Recognizing

Information and Forming Qualitative Judgments. Asia Pacific Advances in

Consumer Research, 1, pp. 36-42

Bagozzi, Richard P. and Youjae Yi (1988), On the Evaluation of Structural Equation

Models,Journal of the Academy of Marketing Science, 16 (Spring), 74-94

Bearden, William O. and Terence A. Shimp (1982), The Use of Extrinsic Cues to

Facilitate Product Adoption,Journal of Marketing Research, 19 (May): 229-239

Bettman, James R., Mary F. Luce, and John W. Payne (1998), Constructive Consumer

Choice Process,Journal of Consumer Research, 25 (December), 187-217

Calder, J. Bobby, Lynn W. Philips and Alice M. Tybout (1982), The Concept of External

Validity,Journal of Consumer Research, 9 (December), 240-243

Churchill, Gilbert A. (1979), A Paradigm for Developing Better Measures of Marketing

Constructs.Journal of Marketing Research, 16: (February), 64-73.

Churchill, Gilbert A. (1994), Marketing Research: Methodological Foundations, 6th ed.,

The Dryden Press, Harcourt Brace College Publishers

Cook, T. and D. Campbell (1975), The Design and Conduct of Experiments and Quasi-

Experiments in Field Setings, in Handbook of Industrial and Organizational

Research, Martin Dunette, ed., Chicago, Rand McNally

20


21/24

Cox, D.F. (1962), The Measurement of Information Value: A Study in Consumer

Decision-Making. in Emerging Concepts in Marketing, ed. W.S. Decker, Chicago:

American Marketing Association, pp. 413-421

Cronbach, Lee J. (1951), Coefficient Alpha and the Internal Structure of Tests,

Psychometrika, 16 (October), 297-334

Curry, David J. and Peter C. Riesz (1988), Prices and Price/Quality Relationships: A

Longitudinal Analysis,Journal of Marketing, 52 (January), 36-51

Dodds, William B. and Kent B. Monroe (1985), The Effect of Brand and Price

Information on Subjective Product Evaluation. in Advances in Consumer

Research, 12, Elizabeth Hirschman and Morris Holbrook, eds. Provo, UT:

Association for Consumer Research, 85-90

Dodds, William B., Kent B. Monroe, and Dhruv Grewal (1991), Effects of Price, Brand,

and Store Information on Buyers Product Evaluation. Journal of Marketing

Research 28 (August): 307-319

Grewal, Dhruv, Kent B. Monroe, and R. Krishnan (1998), The Effects of Price-

Comparison Advertising on Buyers Perceptions of Acquisition Value, Transaction

Value, and Behavioral Intentions,Journal of Marketing, 62 (April), 46-59

Jacoby, Jacob and Jerry C. Olson (1977), Consumer Response to price: An Attitudinal

Information Processing Perspective, in Moving Ahead in Attitude Research,

Yoram Wind and Marshall Greenberg, eds. Chicago, IL: American Marketing

Association, 73-86

Monroe, Kent B. (1976), The Influence of Price Differences and Brand Familiarity on

Brand Preferences.Journal of Consumer Research, 3 (June), 42-9

Monroe, Kent B. and Joseph D. Chapman (1987), Framing Effects on Buyers Subjective

Product Evaluations,Advances in Consumer Research, 14, 193-197

Monroe, Kent B. and R. Krishnan (1985), The Effect of Price on Subjective Product

21


22/24

Evaluations, in Perceived Quality, J. Jacoby and J. Olson, eds. Lexington, MA:

Lexington Books, 209-32

Oakes, W. (1972), External Validity and the Use of Real People as Subjects, Americal

Psychologist, 27, 959-962

Parasuraman, A., Valarie A. Zeithaml, & Leonard L. Barry (1988), SERVQUAL: A

Multiple-Item Scale for Measuring Consumer Perceptions of Service Quality,

Journal of Retailing, 64: 12-40

Peter J. Paul and Jerry C. Olson (1993), Consumer Behavior and Marketing Strategy, 3rd

ed., Irwin Inc.

Peterson, Robert A. (1994), A Meta-analysis of Cronbachs Coefficient Alpha,Journal of

Consumer Research, 21 (September), 381-391

Shimp, Terence A. and William O. Bearden (1982), Warranty and Other Extrinsic Cue

Effects on Consumers Risk Perceptions, Journal of Consumer Research, 9

(June): 38-46

Stewart, David W. (2001), Exploratory versus Confirmatory Factor Analysis, Journal of

Consumer Psychology, 10 (1 and 2), 75-82.

Szylillo, George J. and Jacob Jacoby (1974), Intrinsic versus Extrinsic Cues as

Determinants of Perceived Product Quality, Journal of Applied Psychology, 59

(1), 74-78

Teas, R. Kenneth and Sanjeev Agarwal (2000), The Efeects of Extrinsic Product Cues on

Consumers Perceptions of Quality, Sacrifice, and Value,Journal of the Academy

of Marketing Science, 28 (2): 278-290

Wheatley, John J. and John S. Y. Chiu (1977), The Effects of Price, Store Image, and

Product and Respondent Characteristics on Perceptions of Quality, Journal of

Marketing Research, 14 (May): 181-186

Wells, William D. and Jagdish N. Sheth (1971), Factor Analysis in Marketing Research,

22


23/24

in Multivariate Analysis in Marketing: Theory and Application, David A. Aaker,

eds., Wadsworth Publishing Company, Inc. Belmont, California 94002

Zaichkowsky, Judith L. (1985), Measuring the Involvement Construct, Journal of

Consumer Research, 12 (December): 341-352

Zeithaml A. Valarie (1988), Consumer Perceptions of Price, Quality, and Value: A

Means-End Model and Synthesis of Evidence,Journal of Marketing, 52 (July), 2-

22

23


24/24

This paper was presented at the 23rd Japan Association for Consumer Studies (JACS) Conference,Oct. 2001. The author would like to thank Professor Shuzo Abe for valuable comments on thispaper. However, all errors are the responsibility of the author.

1 ) Price has both objective external properties and subjective internal representations that arederived from the perceptions of price, thus resulting in some meaning to consumers (Jacoby andOlson 1977)

2 ) Convenience, freshness, and time are major higher-level abstractions that combine with priceand quality to produce value perceptions in supermarket consumers.

3 ) Rational choice theory assumes that decision makers possess well-defined preferences that donot depend on particular descriptions of the options or on the specific methods used to elicitthose preferences. Each option in a choice set is assumed to have a utility, or subjective value,which depends on the option.

4 ) Despite the consistency in the main focus of this definition with the previous literature, itincludes all the facets of the construct.

5 ) Marketers are much better served with multidimensional with multi-item than unidimensionaland single item measures of their constructs, and they should take the time to develop them.

This is particularly true for those investigating behavioral relationships from a fundamental aswell as applied perspective, although it applies also to marketing practitioners (Churchill 1979).

6 ) The book (written in Japanese) contains the procedures that should be followed in validatingconstructs and testing construct validity using LISREL.

7 ) The article is about methodological problems in cross-cultural consumer research (in Japanese).

8 ) In the findings of a meta-analysis, Peterson (1994) mentioned, Across 4286 alpha coefficients,1030 samples, and 832 studies investigated, the mean coefficient alpha was .77. Seventy-fivepercent of the observed alpha coefficients were .70 or grater.

9 ) Confirmatory factor analysis is based on the correlation matrix when the data are standardized.

article sacrifice (igss)

Documents