SCHOOL OF i-GKicuLT.uR_I-._*.7mics AGRICULTURAL ECONOMICS:A AND EXTENSION EDUCATION
ONTARIO AGRICULTURAL COLLEGE UNIVERSITY OF GUELPH Guelph, Ontario, Canada
,PREDICTION OF CONSUMER SUPERMARKET fl=rilaN: AN APPLICATION OF THE MULTI-ATTRIBUTE ATTITUDE MODEL
Thomas F. Funk Mohammed Eoonous Jane G. Funk
Research Bulletin AEEE/78/11 November, 1978
ISSN 0318-1804 TABLE OF CONTENTS
Page
1.0 INTRODUCTION 1.1 Marketing Management and Consumer Attitudes 1 1.2 Attitude Measurement and the Multi-Attribute Model 1 1.3 Issues Involved in Use of the Multi-Attribute Model 2 1.4 The Basic Model ...... • 3 1.5 Data Collection and Analyses . 4 1.6 Research Objectives ...... • •. 5 1.7 Organization of the Bulletin . 5 2.0 QUESTIONNAIRE DESIGN AND DATA COLLECTION 2.1 Introduction 7 2.2 Development of the Attribute List 7 2.3 Socio-Economic and Demographic Variables 8 2.4 Pilot Study • ...... •. • 8 2.5 Questionnaire Design • .. . • . 9
2.6 Sample Selection ...... • • ...• • • • • •• • •...... • • • • • • • • • • 0 0 •. 13 2.7 Sample Profile ... • • ... . 13 2.8 Data Collection and Store Selection 15 3.0 ANALYSIS AND RESULTS 3.1 Introduction .. • . 20 3.2 Profile of Consumer Shopping Behaviour 20 3.3 Comparative Profiles • ...... 22 3.4 Intra-Chain Comparisons 29 3.5 Tests for Significant Differences 30 3.6 Intra-Store Comparisons Across Products 31 3.7 Intra-Chain Comparisons Across Products 38
4.0 CHOICE OF THE MODEL VARIATION • 4.1 Variations of the Multi-Attribute Model 42 4.2 Application of Test to One Store 44 4.3 Results of the Test 44 4.4 Alternate Tests of Predictive Capability • 46 4.5 Confusion Matrix 46 4.6 Spearman's Rank Order Correlation Coefficient: A Test of Predictive Potential ..... • 49 5.0 ATTRIBUTE IMPORTANCE 5.1 Introduction . • • 52 5.2 Factor Analysis ...... 52 5.3 Multiple Regression Analysis 56 5.4 Overview ... .. 57 6.0 DISCUSSION AND IMPLICATIONS
6.1 Introduction •• 61 6.2 Comparisons Among Individual Stores and Among Stores Within Chains ...... 62 - 6.3 Predictive Power of Model Variants • • • 64 6.4 Influence of Store Attributes and Socio-economic Variables on Consumer Evaluations • 65 6.5 Methodological Contributions to Managerial Decision- Making ...... • 67 TABLE OF CONTENTS contd...
Page
6.0 DISCUSSION AND IMPLICATIONS (contd...... ) 6.6 Limitations of the Study and Recommendations for Future Research •0. • • 0 _ •. • 67 7.0 BIBLIOGRAPHY •••••••• ••••• • •••0•••0•••0•••••0•0 69
8.0 APPENDICES .0 OOOOO OOOOOO OO O • 72 INTRODUCTION
1.0 Marketing Management and Consumer Attitudes
In today's complex marketing environment, supermarkets find them:- selves competing for consumer patronage by offering a variety of differentiated products and services. The key to success lies in offering the target consumer the ideal marketing mix of Product, Price, Place, and Promotion -- or the
Four P's, as they are known in marketing. Obviously, it would be of great help to the marketing manager to know what products and services consumers prefer so that he could assemble the best marketing mix possible. It is therefore the intention of this study to provide useful information for the marketing manager by identifying those products and services which motivate consumers to select particular supermarkets. In addition to isolating important in- fluences on consumer preference, this study, by its use of the multi-attribute model to measure consumer attitude, hopes to develop a methodology which management can use to undertake similar studies on its own.
1.2 Attitude Measurement and the Multi-Attribute Model
Central to an understanding of the consumer patronage decision is the concept of attitude; as a result, the measurement of consumer attitudes has understandably been a subject of considerable interest in marketing research. Much of the existing information is based on the work f social psychologists, many of whom feel that "an attitude is a learned predisposition to respond to an object or class of objects in a consistently favourable or unfavourable manner" (Fishbein, 1967, p.357). Although researchers tend to agree that attitude consists of several components, they disagree on exactly what these components are and how they are measured.
In this study, consumer preference for supermarkets was measured by , use of the multi-attribute model. This model involves the use of an attitude 2 scale as a measuring device which yields a single affective (attitude) score.
This score is an indication of an individual's belief about an object; that is,
t indicates the individual's degree of favourability or unfavourability toward that particular object. Initial efforts to derive such a single score as a measure of an individual's attitude toward an object were made in the area of social psychology. Recently, applications have been made in marketing research, specifically in the area of prediction of brand prefernces.
At the intuitive level, the model requires respondents to evaluate their beliefs on each of a set of attributes which describe an object. These evaluative scores are then summed to form the attitude score for that object.
In other words, consumers' preferences/attitudes are seen as a function of a set of characteristics/attributes. In this case, the stores' products and services are viewed as product attributes.
1.3 Issues Involved in Use of the Multi-Attribute Model
The earliest variations of the multi-attribute model (also known as the linear compensatory model and the value-expectancy model) were introduced by Fishbein and by Rosenberg. Later researchers concentrated on modifying these early models to achieve better predictive power. 1 Fishbein's concept is that an individual's attitude toward an object is a function of his beliefs about that object and the evaluative aspect of those beliefs (Fishbein, 1963). Rosenberg's concept of attitude, on the other hand, is functionally related to the intensity of a person's value toward an object and the perceived importance of the attitude object in leading to or
N 1 The model used is: A . E B.a. o 11 i=1 where A = Attitude. . Belief i about the object. Boi a. = The evaluative aspect of Bi. N1 . Number of beliefs. 3
• blocking the attainment of his values. Essentially, value items may be
categorized in terms of a) value importance, or the importance to him as a
source of satisfaction, and b) perceived instrumentality, or his estimate as
to whether and to what extent the value in question will tend to be achieved
or blocked (Rosenberg, 1956).
Studies in marketing research, generally concentrating on prediction
of brand preference, have attempted to validate each of these models, and as
a result, various issues have come to light. Obviously effective use of the
multi-attribute model requires an awareness of these issues. A review of
existing literature indicates that foremost among these issues are the inclusion
and measurement of the importance factor, the predictive power of the model,
•the measurement of the belief component, and the use of summation versus aver-
aging to obtain the final score.
1.4 The Basic Model
The basic multi-attribute, model (Bass and Wilkie, 1973) chosen for
use in this study is expressed as.A.k = I B ik ijk i1= where i = attribute or product (store) characteristic. • brand (store) consumer or respondent such that Ajk • consumer k's attitude score for brand (store) I • the importance weight ik for attribute i by consumer k, and B consumer k's belief as ijk to the extent to which attribute i is offered by brand (store) j.
2 Rosenberg's model is expressed as: A = o i=1
• Perceived instrumentality, the extent to which the person believes that the object o will lead to or block the attainment of value i. V. = Value importance, value i's importance to the'respon- dent as a source of satisfaction. • Number of values. 4
This basic model, in keeping with the aforementioned unresolved
issues requires consideration of essentially four components: Importance
Weights, Beliefs, Model Structure, and Model Tests. Various forms of the
basic model incorporating these components were evaluated before the final
form was chosen as an instrument for this study. This evaluation will be dis-
cussed in a later chapter.
1.5 Data Collection and Analyses
Operation of the above model requires initial specification and
inclusion of attributes which should reflect consumers' perceptions of the
various dimensions of the stores. These attributes were compiled from an ex-
tensive survey of literature, discussions with knowledgeable persons, and a
pilot study. In all, 37 attributes were included.
A questionnaire was devised and administered by personal interview
to the 150 respondents in the survey. The respondents were asked to measure directly the importance of each attribute on a six-point scale. Each attribute was described by favourable evaluative adjectives. Belief ratings were also obtained on each of the 37 variables by use of a six-point bipolar scale ranging from extremely unfavourable to extremely favourable. However, this scale differed from the importance scale in one significant way: the inclusion of a no opinion point. In addition to the above ratings, demographic information was also collected from each respondent.
Every effort was made to select a representative sample of consumers from the city of Guelph in accordance with accepted statistical principles, subject to time and financial constraints. Stratified area sampling was used to select the 150 respondents, while the twelve stores were selected arbitrarily because of their large size and frequency of advertising in the local newspaper.
Analyses performed on the data included simple linear regression and multiple regression. Comparative profiles were also obtained for each store on each attribute by use of the semantic differential technique. The inclusion of 37 variables presented a relatively detailed picture of each supermarket, however, use of such a large number of variables could cause problems in multiple regression analysis. In order to minimize these problems, factor analysis was performed to reduce the variables to a more manageable number.
1.6 Research Objectives
Information for this study was collected in March, 1975, by means of personal interview with 150 respondents in Guelph, Ontario. The specific objectives of the research were:
1. To develop a profile of supermarkets based on consumers' evaluative perceptions of the stores' attributes and to identify significant differences among stores.
2. To determine the extent to which stores within a chain are significantly different in terms of consumers' evaluation of their respective attributes.
3. TO test the capability of the multi-attribute model in predicting consumers' choice of supermarkets.
4. To compare the explanatory power of alternative formulations of the multi-attribute model.
. To investigate the extent to which various store attributes influence consumers' choice of supermarkets.
6. To investigate the extent to which socio-economic and demographic variables influence consumers' choice of supermarkets.
1.7 Organization of the Bulletin
Chapter 2 summarizes the development of the questionnaire, selection of the sample, sample profile, and selection of stores. Attention is also given to the development of the attribute list and measurement scales.
Chapter 3 discusses the analyses and results including a profile of consumer shopping behaviour and a comparison among the stores on the attributes. Results of tests for statistical differences among stores are also discussed.
Chapter 4 gives attention to the predictive power of various forms of the multi-attribute model and advances suggested tests for measuring pre- 2 dictive power other than the usual r value.
Chapter 5 contains the results of factor analysis and multiple regression analysis which were used to single out the most influential attributes.
Chapter 6 discusses the results of the study and their implications both for management and for future research. 2.0 QUESTIONNAIRE DESIGN AND DATA COLLECTION
2.1 Introduction
Careful thought -was given in this study to the development of a valid and accurate questionnaire to measure consumer preference for supermarkets as well as to the selection of a representative consumer sample. This chapter summarizes the issues involved in this stage of the research, including those of attribute selection, selection of demographic variables, choice of measure- ment scales, the concepts of importance and belief, store selection, sample selection, and data collection. Also included is a sample profile.
2.2 Development of the Attribute List
In order to effect a comparative evaluation between stores, a compre- hensive list of store attributes was necessary. The list was compiled through a search of existing literature, discussions with knowledgeable persons, and a small pilot study. A systematic effort was made to classify attributes in terms of product characteristics, store dimensions, and socio-economic and demographic variables.
Emphasis was placed on meat products because preliminary informal discussions with knowledgeable persons and previous research (Norris, et.al.,
1974) indicated that consumers are very concerned about the meat they purchase.
This is understandable since meat usually constitutes a substantial proportion of the average food expenditure.
Studies seem to agree that consumers consider leanness, tenderness, flavour, and juiceness to be important quality characteristics for meat.
Conclusions were mixed on the importance of marbling. In addition to these characteristics, group interviews conducted at the University of Guelph indicated that texture, freshness, colour, fat content, amount of bone, and 8
packaging also influencedconsumers' decisions (Morris et al, 1974). It was
decided to group these latter characteristics under the general description
of quality of meat products.
2.3 Socio-Economic and Demographic Variables
One would expect various socio-economic and demographic variables
to influence consumers' preferences for supermarkets; however, studies in this area have had mixed results (Assail and Wilson, 1972; Danner, 1959; Hudson and
Danner, 1963). Although inclusion of such variables in this study was not necessary for the development of store profiles, they were considered essential for an analysis of the factors related to store choice. Such information is also absolutely essential for effective market segmentation, which is an im- portant step in the formulation of a successful marketing strategy. Thus, in keeping with the findings of relevant studies, respondents were asked to give information on the variables listed in Table 2.1.
2.4 Pilot Study
At this point, it was felt that the review of previous studies did not produce an adequate or suitable list of attributes to satisfy the complex- ity of the attitude model or to produce an effective empirical test. Conse- quently, informal discussions were undertaken with knowledgeable persons at the University of Guelph as well as with a few homemakers and workers. The ideas and suggestions which emerged from these discussions were reinforced by a pilot tudy involving 12 respondents who were asked to evaluate 12 attributes and to include others which they considered when selecting a supermarket.
The most interesting observation which evolved from the above study is that consumers tend to shop as per product class. In other words, their decision to patronize certain supermarkets is based on their perception of the meat, dairy, and grocery products which these stores have to offer instead of
on the basis of other factors such as cleanliness and overall prices. The most important attributes per product class seem to be size of selection, freshness,
quality, and prices.
The final list of 37 attributes obtained from literature review, dis-
cussions with knowledgeable persons, and the pilot study are listed in Table 2.2.
It is realized that although this list will supply valuable descriptive inform- ation, it is also too large to be used effectively in statistical and econo- netric models. As a result, factor analysis was used to obtain a more condensed list of image dimensions for further analysis.
2.5 Questionnaire Design
The development of measurement scales to measure consumers' preference for supermarkets involved much thought about the concepts of importance and belief which are major components of the multi-attribute model used in this study.
Researchers disagree on exactly what is measured by the V (value) and • a (evaluative) components in the model. Some see them as direct measures of the importance of attributes, while others feel that they are more measures of the satisfaction or evaluation of the attributes by the respondent. One of the major issues in this debate involves the conceptualization of the impor- tanceweights (W.), value importance as a source of satisfaction (V) the evaluative aspect of belief (a ). Another issue involves the question of for- i mulation and the need to avoid ambiguity.
Consideration was given to both of these issues in designing the questionnaire. For the purposes of this study, it was decided that Wi, Vi, and a would be viewed direct measure i as a of the importance respondents attach to attribute i. It is represented as I in the basic model. Justification for - 10 -
TABLE 2.1
Selected Socio Economic and Demographic Variables
Selected Socio Economic and Demographic Variables
Local Newspaper Readership
Food Ad Readership
Shopping Transportation Method
Sex of Respondent
Size of Household
Age of Household Members
Occupation of Household Head
Number of Workers in Household
Years of Local Residency
Educational Level of Respondent
Income Level of Family
Age of Respondent - 11 -
TABLE 2.2 .
List of Attributes
General Description Components
Meat Products Range of selection of meat products Freshness of meat products Convenience of package size Prices of produce Value for money spent Quality of meat products Produce Range of selection of produce Freshness of produce Prices of produce Value for money spent Quality of produce Dairy Products Range of selection of dairy products Prices of dairy products Value for money spent Quality of dairy products Freshness of dairy products Grocery Products Convenience of package size Prices of grocery products Value for money spent Range of selection of brands Quality of dairy products Store Characteristics Cleanliness Ease of finding items Ease of moving through store Quickness of checkout service Convenience of shopping hours Fully stocked shelves Attractiveness of displays Helpfulness of personnel Presence of personalized services Nearness of store Ease of finding parking place Convenience of location Nearness of store to ancillary services Informative ads Many coupons Large number of items specially priced - 12 -
this decision lies in the belief that consumer preferences for supermarkets
are a function of the importance attached to each attribute and not of the
satisfaction derived from each attribute. For example, the attribute nearness
of location cannot be evaluated directly as a source of satisfaction as can
some attributes in other studies -- i.e., the taste of toothpast (Talarzyck,
1969).
Once a decision was reached on the above issue, attention turned to
the construction of a scale which measures the importance consumers attach to
each attribute with the least ambiguity. Thus emphasis was placed on the spe-
cificity of each attribute. Consumers were asked to rate each on a six point
scale which ranged from extremely unimportant to extremely important. Each
attribute was described by favourable evaluative adjectives. It is acknowledged
that the use of favourable adjectives could cause an upward bias of the impor-
tance ratings; however, this approach was considered necessary in order to avoid
ambiguity and achieve precision.
The belief component was measured for each attribute on a similar
scale. The adjectives involved ranged from extremely unfavourable to extremely
favourable. This scale differed from the importance scale in one significant
way: the inclusion of. a no opinion point, which was necessary to avert forced
evaluation. Justification for this is considered fairly obvious; for example,
if respondents do not read local newspapers, they cannot be expected to have
an opinion on the informativeness of the ads.
The no opinion point was placed away from the main evaluation scale
and arbitrarily assigned a neutral value of 4. The belief scale was thus a
seven point scale. There was only a small incidence of no opinion responses
and it affected all attributes for all stores. Thus any bias which might have resulted was minimum and evenly distributed. - 13 -
2.6 Sample Selection
As earlier stated, every effort was made to select a representative
sample in accordance with accepted statistical principles, subject to the usual
constraints of time and funds.
The sample selection procedure used is known as two-stage area sam-
pling. The City of Guelph was taken as the universe and was divided into nine 1 planning districts, each of which constituted an autonomous area. The districts
were then subdivided into clearly demarcated and easily identifiable blocks 2 from which 30 were randomly selected by means of a table of random numbers.
Because of the wide disparity of population among districts as shown in Table
2.3, column 2, the number of blocks selected from each district varied according
to the proportion of the population within that district. It was difficult to
establish the a priori probability of household distribution per block. Conse-
quently, with the exception of a few cases, five households were selected per block. Table 2.3 presents the breakdown of the sample area in terms of number
of blocks and sample size from each district.
The population figtire of 62,998 used in this survey was obtained from the 1973 census and was unadjusted for the years 1974 and 1975. The number of 3 households was calculated on the average of 2.5 persons per household. As a result, the population universe was taken to be 25,199 households from which
150 were selected to constitute the sample.
2.7 Sample Profile
The percentages presented in Table 2.4 describe the sample population in terms of the socio-economic and demographic variables used in the study.
1 See Appendix B. 2 See Appendix C. 3 Figures used in this section were obtained from City Hall, Guelph. TABLE 2.3
Sample Distributions as Per District
Districts Population No. of Blocks Sampled Sample Size (1) (2) (3) (4)
Hanlon 1,657 1 4
Southview 2,115 1 5
University 6,509 3 15
Eramosa ' 16,807 8 40 1 Eastview 2,752 1 6 1---. •P•• 1 Central 1,585 1 4
Edinburgh 19,607 9 47
Willow West . 684 1 2
Riverside 11,282 5 27
TOTAL 62,998 30 150
NMI 11111 IIIIII MIMI all MINI MIMI MIN 11111 MIN Ell MIN 111111 11E11 11111111 11111111 MEI 11111 IMO - 15 -
The distributions seem to indicate that the sample covered a reasonably .rep-
resentative cross section of the population. This is particularly true in terms
of the important variables of age, occupation, education, and years in Guelph.
Eighty percent of the sample was between the ages of 20 and 60 years, and 78
percent had lived in Guelph for over five years. With the exception of the
Student category, occupational distribution also appears representative. Sim-
ilarly, the educational distribution is representative with the exception of
the 'some college' category. Representative distribution is also present in the
size of the household. The income category shows that 48 percent of the res-
pondents earned between 10,000 and 20,000 dollars a year, which corresponds to
the average income in Guelph.
As one might expect given the subject of the survey and the time
of data collection, 91 percent of the respondents were female. Well over 90
percent shopped by car, and approximately 80 percent read the supermarket ads in the local newspapers.
2.8 Data Collection and Store Selection
Because of the complexity and length of the questionnaire, data was
collected by means of personal interview. In the interests of accuracy, one
professional interviewer did all the interviewing thus minimizing interviewer
bias. Response bias was also minimized by use of multiple choice questions.
An average of five respondents were interviewed per block. The inter-
viewer was asked to estimate the number of households per block and divide the
estimate by five. The resulting quotient was cumulated successively to deter-
mine each household until the established sample size per block was reached.
Time constraints precluded the use of recall, so successive households were substituted in the event of unavailability. Most interviews were done during
the day with a few done in the evening. -16 -
TABLE 2.4
Sample Profile
Percentage Category of Respondents 1 Newspaper Readership Guelph Mercury 81 Guelph Life 25 Read food ads 79 1 Shopping Transportation Car 95 Bus/Taxi 5 Other 15 Sex of Respondent Male 9 Female 91 100 Size of Household One member 7 Two members 26 Three members 17 Four members 23 Over four members 27 100 1 Age of Household Members Under 5 years old 25 6-9 yrs.bld 30 10-19 yrs.old 41 20-59 yrs.old 80 Over 60 years old 20 Occupation of Household Head Professional 26 Skilled 31 Semi-skilled 23 Student 1 Retired/Unemployed 19 100 Employment Status of Household Head Full time 79 Other 21 100 Number of Workers in Household One or less 72 More than one 28 100
Contd -17 -
TABLE 2.4 contd...
Sample Profile
Percentage Category of Respondents
Years of Local Residency Less than 1 year 4 1-5 years 18 Over 5 years 79 100 Educational Level of Respondent Less than Grade 9 19 Some High School 30 Complete High School 25 . Some College 10. Complete College 16 100 Income Level of Family Below $2,000 1 $2,000 - $10,000 29 $10,001 - $20,000 48 $20,001 - $30,000 9 Over $30,000 13 100 Age of Respondent Under 20 years 2 20 - 34 yrs. 30 35 - 60 yrs. 46 Over 60 years 22 100
1 Percentages do not all sum to 100% since categories are inclusive. -18 -
Each respondent was asked to indicate the importance they attached to each attribute, to rank and rate the stores with which they were familiar, 5 and to provide certain socio-economic and demographic information.
The stores rated in the survey are listed in Table 2.5. They rep- resent the major chains and independents in Guelph. The remaining foodstores are small convenience stores which do not carry a full line of food products and therefore were not considered appropriate for this study.
For analytical purposes, response ratings were assigned numerical values. Importance ratings were assigned the values of one through six while belief ratings took the values of one through seven for each segment of their respective continum. The smaller the value, the less important or less favour- able was that respondent's rating. Each of the other responses was assigned the value of one if checked by the respondent and zero if not checked. Excep- dons were made to frequency of shopping (question 3) and age distribution of members in the household (question 14). In the case of frequency of shopping, the numbers one through seven were assigned to the seven classifications res- pectively, while the actual number that fell within an age group was entered in each age distribution category.
5 See Appendix A for questionnaire. 11111 11111 1111111 Mill BIM 1111111 MIN 11111 =II 111111 1111111 111111 111111 NMI 11111 IIIIII
TABLE 2.5
Stores and Their Descriptions
Identification No. Stores Status Description 2 A & P Individual 1. Located in small shopping plaza near several apartments and townhouses. 2 Dominion Eramosa Chain 2. Shares small mall with discount store 3 Dominion Speedvale Chain 3. Part of large shopping plaza in res- idential area. 4 Leaders Individual 4. Located by itself near Dominion Eramosa. 2 5 Miracle Food Mart Individual 5. Recently opened as part of a large shopping mall on edge of city. 6 Pelosos - Individual 6. Family owned and operated in resid- ential area. Reputation for high quality meats. 2 7 Sunnybrook Individual 7. Located in small plaza on edge of city. 8 Zehrs Edinburgh Chain 8. Part of small plaza in residential area. 9 Zehrs Victoria Chain 9. Part of small plaza in residential area. 10 Zehrs Wellington Chain 10. Part of small plaza near residential area. 11 ' Zehrs Willow West Chain' 11. Part of large mall in residential area. 12 Zehrs Woodlawn Chain 12. Part of small plaza on edge of city near apartments and townhouses.
1 For store locations See Appendix C. 2 These are really chain stores which are treated as individual stores because only one branch of their respective chains operates in Guelph. - 20 -
3.0 ANALYSIS AND RESULTS
3,1 Introduction
The key to a successful marketing strategy lies in the dictum "know
your customer." This includes both an understanding of how consumers view the
various products and services and a knowledge of their shopping behaviour. By
presenting the results relating to consumer shopping behaviour and comparative
store profiles, this chapter provides information to aid management in the
formulation of the most effective marketing mix•
3.2 Profile of Consumer Shopping Behaviour
Since the following summary statistics have been extracted primarily
for descriptive purposes, they are represented graphically. The resulting
description of consumer shopping behaviour is a fairly detailed one; however,
it should be noted that because no statistical tests were conducted on the data
used in this section, the resulting comparisons should be interpreted with
caution.
During each interview, the respondent was asked to rank each of the stores she was familiar with. The results of these rankings are presented in
Figure 3.1. Each rank is represented by a bar. The fifth rank was excluded because of relatively few observations. The chart shows that, generally, the chain stores were ranked first by those who evaluated them. The exceptions to this are A & P and Miracle, both of which received more third place rankings.
In addition, Miracle received the lowest first place ranking of any chain store.
It is interesting to note that although both A & P and Miracle are members of large chains, they are the only representatives of those chains in Guelph.
Pelosos was ranked second by most of its patrons, and Leaders ranked second and third. Sunnybrook, the third independent, was the only store to be ranked OM 11111 MINI IIIIII NM MINI 111111 . 111111 SIM 11111111 MINI INN 111111 NIS III. MN 11111 OM
FIGURE 3.1 FREQUENCY ()FRANKS
* 100
90 First Rank 80 Second Rank Third Rank
70 Fourth Rank Percent age
Distribution 60
50
40
30
•••••1 20
10 II• a
A & Pi Dominion Miracle ;.;unnybrook Zehrs Zehrs Speedvale Victoria Willow W. Dominion Leaders Pelosos Zehrs Zehrs Zehrs Eramosa Edinburgh Wellington Woodlawn 1 Read 21 percent of those who evaluated A & P ranked it first, -22 - fourth by the majority of those who rated it. It also received the lowest per- centage of first place rankings of any store.
The frequency with which consumers shopped at each store is presented in Figure 3.2. Generally, a higher percentage of consumers tended to shop once a week, especially at chain stores. The exceptions again were A & P and Miracle.
Among the independents, results were mixed. Here again, it must be emphasized that these figures are only indicative of trends, and conclusions are therefore tenuous. To illustrate this point, the 21 percent who shopped once every month at A & P were probably shopping more frequently at other stores.
Figure 3.3 describes consumers' shopping behaviour with respect to the products which were purchased from each store. It is apparent from the graph that respondents tended to purchase all products at the stores they pa- tronized rather than buying specific items at specific stores. This is espe- cially true of the chain stores with A & P being the only exception. Patrons tended to shop there more for grocery products. Among the independents the same trend is evident except for Pelosos where patrons tended to shop more for meat.
3.3 Comparative Profiles
One of the major objectives of this study was to develop comparative profiles for the stores on each of the 37 attributes. It is felt that these profiles will give management an indication of their store's comparative strength or weakness on each attribute as evaluated by consumers.
The semantic differential technique'was employed to obtain these
1 This technique is a measuring device which entails the use of bipolar scales with opposing adjectives at each end of the scale. An even or odd segment continuum separates each pair of adjextives on which a respondent is asked to check the point which describes her feelings most closely on each attribute. A seven-segment continuum was used to measure belief (B. in this study. 1-)•k Each segment on the continuum represented a different evaluative per- ception of each attribute which ranged from extremely unfavourable to extremely favourable. For a concise discussion of semantic differential technique, see Boyd and Westfall, Marketing Research, Text and Cases. 11111 NIB MN MN INN Mil 111111 11011 VIM 111111 NMI MIS MI IIIII
FIGURE 3.2 FREQUENCY OF SHOPPING
100
90 Eir.= Between Two and Your Times Per Week,
80 =73 ()pee Every Wettit rcentato ( :=SSr/14 Onf:e Every Two Weeks Frequency Onen Every Month
60
50
CA.) 40
30
20
A& P Dominion Sunnybrook Zehrs Zehrs Speedvale Victoria Willow Dominion Leaders Pelosos Zchrs Zehrs West Eramosa Edinburgh Wellington
1 Read 5 percent of those who shopped at A & P did so between 2 and 4 times per week. FIGURE 3.3 FREOUENCY OF SHOPPING PER PRODUCT CLASS
100 VA Meat EU Produce LNI Dairy 90 Grocery C:1 All Productc
CO •••••••T
, Percentage 70 Frequancy 60
50 Ni -P•••
40
•••••••\
30 ••••••••••,
20
•••••• 1
•
A & P Dominion Miracle Sunnybrook Zehrs Zchrs Zehrs Speedvale Victoria Willow Woodlawn Dominion Leaders Pelosos Zehrs Zehrs West Eramosa Edinburgh Wellington
1 Read 18 percent of those who shopped at A & P bought meat there.
11111 MI SIN OM NM 11111 UM MO 11111 OM OM NM OM 11E1 MIN NM MIN -25 -
profiles which were generated by the following equation:
E B /N ijk
where B. = the belief ratings of attribute i by consumer k for store j.
= the number of respondents who rated store j.
The average score was obtained for each store on each characteristic by taking
the sum of the belief ratings of the respondents who evaluated that particular
store and dividing it by the number of respondents (N). The results obtained
are reported in Table 3.1.
Since graphical representation of all 12 stores would be impossible to decipher, the stores' relative standings are discussed using Table 3.1. The difference between their mean scores on each attribute gives some idea of the difference perceived by consumers on that attribute. The higher the mean, the more favourably the store is viewed on that attribute. Given the values used on the belief scale in the questionnaire, ratings could vary from 1 to 7.
A bkief look at Table 3.1 shows remarkable similarity among stores on the product attributes with most ratings clustered between 5 and 6. Under meat products, exceptions to this are the low rating received by Miracle and Zehrs Victoria on meat prices (i.e., they were perceived as having higher prices). Perhaps most striking, however, is Sunnybrook's consistently low rating on all meat attributes. This is consitent with.Sunnybrook's low over- all rating (most consumers ranked it fourth). It emerged with the most adverse overall image.
Another exception to the general clustering of meat attribute ratings is the high rating received on all attributes by Pelosos. This is consistent with earlier findings that those who shopped at Pelosos bought more meat than anything else there and with Pelosos's reputation for quality meats. TABLE 3.1
Average Evaluative Scores
cii U) • 4 O -6 z aoUi 4J o a) P cd 0.) 'CI 0 ci /4 04 0 ra Q 0 41 Cl) 0 0 ,--i Store Attributes r=40 1-I ,--1 0 0Q d .H U) CL) U) 1:11 0 0 W Woodlawn sr-I P r-I 0 0 CU 0 (I) CO Cn (0 (J) 4-4 rCi a/ 0 ciP $4 P P 0 cti 0 CD -I-1 a) i a) a) a) a) P, N N N N (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) MEAT PRODUCTS Wide selection of meat 5.1 5.9 5.7 5.1 5.4 6.3 4.9 5.6 5.0 4.7 5.6 5.7 Freshness of meat products 5.4 5.7 5.6 5.3 5.4 6.4 4.6 5.8 5.1 6.1 5.9 5.9 Convenient package size 5.2 5.7 5.5 5.2 5.2 6.1 4.6 5.8 5.1 5.9 5.7 5.8 Low prices 5.2 5.6 5.3 5.1 4.9 6.2 4.9 5.8 4.8 5.8 5,5 5.4
Good value for money spent 5.3 5.7 5.7 5.2 5.1 6.6 4.9 6.0 5.2 5.9 5.9 5.8 t‘..) Good quality meat products 5.3 5.8 5.8 5.3 5.4 6.4 4.8 5.8 5.4 5.9 5.8 5.7 PRODUCE Wide selection of produce 5.4 5.7 5.8 5.2 6.1 5.2 5.0 6.1 5.6 5.7 6.2 6.0 Freshness of produce • 5.5 5.6 5.7 5.3 6.1 5.2 5.3 6.3 6.1 5.8 6.2 6.1 Low prices 5.1 5.4 5.3 5.1 5.2 5.0 5.2 6.1 5.3 5.7 5.8 5.9 Good value for money spent 5.4 5.7 5.7 5.2 5.6 5.0 5.1 6.4 5.7 6.0 6.1 6.1 Good quality produce 5.5 5.6 5.7 5.3 6.0 5.0 5.0 6.3 6.0 6.0 6.3 6.0 DAIRY PRODUCTS Wide selection of dairy products 5.8 5.8 6.0 5.9 5.8 5.9 5.7 6.0 5.6 5.6 6.0 6.1 Low prices 5.7 5.6 5.6 6.0 5.1 5.6 5.7 5.8 5.6 5.6 5.7 5.6 Good value for money spent 5.9 5.7 5.9 6.0 5.5 5,8 5.7 6.0 5,5 5.8 5.8 5.6 Good quality 5.9 5.8 6.0 6.1 5.7 5.8 5.9 6.1 5.9 5.8 6.0. 5.7 Freshness of dairy products 6.0 5.7 5.9 6.1 5.7 5.7 5.9 5.9 5.9 5.6 5.9 5.9 GROCERY PRODUCTS Convenient package size 5.7 5.8 5.9 5.9 5.9 5.0 5.6 6.1 5.8 5.8 5:9 5.7 Low prices 5.6 5.8 5.8 6.0 5.3 5.4 5.4 5.8 5.5 5.9 5.6 5.6 Good value for money spent 5.7 5.9 5.9 6.0 5.6 5.4 5.6 5.8 5.7 6.1 5.8 5.9 Wide selection of brands 5.8 6.0 5.9 5.7 5.9 5.3 5.3 5.9 5.5 5.9 6.0 5.8 Good quality 6.0 5.9 6.0 6.0 6.0 5.3 5.6 6.1 6.1 6.1 6.2 6.0
contd.... NIB 1111111 111111 111111 INS 111111 INS MINI MIMI 1111111 all INS 1111111 1111111 US NW- SIMI 11111111 111111 11111 NM 1111111 UN SIN MI 1111111 VIII MN MINI ,
TABLE 3.1 (contd....)
Average Evaluative Scores
cti o cr, • • o 4 O 'Ci Z CO .I.1 •-• Ei (1) •ri cd W $.4 9:41) P ra. 0 0 •:11 0 ELI Cl) 0 4J H H Store Attributes 4.4 o O H H o 0 0 •ri a) 6,1 Woodlawn P-4 sr-i0 •r40 PU) HW oU) ,n;-1 Edinburgh ro 0 0 a) u m co U) (1) 0 •,-1 ro co 0 0 co cz P H 0 ..) o C) •ri a) 0 a) a) a) Zehrs ZPArn Zehrs N N N (9) ) - (2) (3) (4) (5) (6) (7). (8) (10) (11) (12) (13) STORE CHARACTERISTICS Cleanliness 6.0 5.9. 6.7 6.0 6.6 6.3 4.4 5.9 6.2 6.1 6.2 6.4 Ease of finding items 6.0 5.5 6.2 6.1 5.8 6.1 4.9 5.9 5.9 6.0 5.9 6.0 Ease of moving through store 6.0 5.7 6.0 6.0 6.3 6.0 5.0 5.8 6.1 5.9 5.7 6.1 Fast check-out service 5.8 4.9 5.5 6.5 3.8 6.0 5.3 5.9 6.0 6.0 6.1 6.4 Fully stocked shelves 5.9 5.8 6.1 6.0 6.0 5.5 5.0 5.8 5.9 5.6 5.9 6.3 ,4 Attractiveness of displays 5.2 5.3 5.6 5.0 5.8 4.5 4.0 5.3 5.7 5.3 5.7 5.8 Helpfulness of personnel 6.0 5.8 6.0 6.4 4.4 6.4 5.2 5.7 6.2 6.1 6.1 6.4 Presence of personalized service 4.7 5.1 5.3 4.8 4.2 6.2 4.3 4.8 4.7 5.3 5.1 5.2 Nearness of store 4.5 5.1 5.1 5.7 2.6 4.5 4.2 5.2 5.0 5.9 4.9 6.4 Ease of finding parking place 5.9 5.9 6.2 6.4 4.7 5.9 5.8 5.9 6.0 5.1 5.5 6.4 Convenience of location 4.5 5.2 5.3 5.9 2.7 4.9 4.4 5.4 5.0 5.9 5.4 6.5 Nearness of store to ancillary service •2.7 3.8 4.9 3.8 4.5 2.3 3.3 3.0 2.4 3.8 5.1 6.0 Informative ads 5.6 5.5 5.7 5.8 5.8 4.5 4.8 5.6 5.8 5.7 5.6 5.6 Many coupons 4.0 4.3 5.0 3.8 4.0 4.0 3.7 3.8 3.1 3.9 4.6 5.0 Large no.of items specially priced 5.7 5.6 5.6 5.6 5.2 4.7 5.4 5.8 5.7 5.9 5.8 5.6 Number of Observations 43 64 71 51 82 22 29 36 22 30 6.0 25 -28 -
In the produce class, the highest ratings seem to belong to Miracle,
Zehrs Edinburgh, Zehrs Willow West and Zehrs Woodlawn, all of which rated highly on all produce attributes. The only exception is Miracle's comparatively poor rating on produce prices. The other stores were perceived as being very similar in this area.
Ratings for dairy products again show great similarity for all stores on all attributes as do the ratings for grocery products. It is noticeable, however, that Miracle once again received the poorest price rating in both these categories; in fact, Miracle was perceived to have comparatively high prices over all categories.
Much greater diversity is evident in the ratings for store character- istics. Overall, Sunnybrook seems to have fared the worst here, but other stores received particularly low ratings on certain attributes. In the area of fast checkout service, Miracle 'received by far the worst rating as it did on helpfulness of personnel. Pelosos, Leaders, and Zehrs Woodlawn received comparatively high ratings on these attributes, as one would expect since they are smaller stores and therefore. may tend to give more personalized service.
Miracle again fared badly on the nearness of store and location ratings.
Possible explanations for some of these ratings will be discussed in a later chapter.
Since Zehrs and Dominion are the major chains in Guelph, each having more than one store, comparison between them was effected based on the means in Table 3.1. Zehrs Willow West (column 12) and Dominion Speedvale (column 4) were chosen for the comparison because of the comparatively large number of respondents who evaluated them and because they were believed representative of their respective chains. As one might expect, the means in Table 3.1 show that the two chains were perceived as being quite similar by respondents. They -29 -
received very close ratings in the areas of meat, dairy, and grocery products with the possible exception that Zehrs Willow West was perceived as having slightly fresher meat products. Larger variations are noticeable in the pro-
dacearea where Zehrs Willow West was clearly perceived as being superior. This is not surprising since earlier discussion of Table 3.1 indicated that Zehrs
Willow West had one of the highest ratings on produce. Under store character- istics, Dominion rated higher on cleanliness. Once again, this is not sur-
prising because that store was perceived as being the cleanest of all stores.
Other differences can be noted in checkout speed and ease of parking.
Again it is pointed out that all the above results, though they give an idea of a store's comparative standing; are indicative only of trends.
Later statistical testing will reveal whether or not the perceived differences are indeed significant or rather due to random variat„ion.
3.4 Intra-chain Comparisons
Further study of Table 3.1 results in intra-chain comparisons between
the two stores in the Dominion chain and' among the five stores in the Zehrs
chain. Miracle Food Martand A & P are the sole representatives of their respective chains in Guelph, so obviously intra-chain comparisons are not
possible for them.
The profiles of the Dominion stores (columns 3 and 4) indicate very similar with the most dispersion in the area of store characteristics. There
are noticeable differences here in the areas of cleanliness and ease of moving
through store as well as in nearness to ancillary services.
Members of the Zehrs chain are profiled in columns 9 through 13.
Once again, they are perceived as being quite similar in all product character- istics with the exception of Zehrs Victoria which did not compare particularly well in the meat category. Here too, there is more dispersion in the area of -30 - store characteristics, particularly in the areas of location, parking and near- ness to ancillary services. Of course, no firm conclusions can be drawn without D further testing.
In general, then, it appears that the stores within chains were per- ceived as being very similar by respondents with the most diversity coming in the area of store characteristics.
3.5 Tests for Significant Differences
The presentation of means offered in Table 3.1 allows management to compare their store's standing on the attributes with that of other stores.
This can be very enlightening, but it does not fully answer the important management question: which of the comparatively low ratings is law enough to call for corrective measures? A partial answer to this can be obtained after one establishes which of the apparent differences are statistically significant.
Once this is done, management has more information on which to base the decision to employ corrective measures. What is needed, then, to supplement the semantic differential profile is a method to test for statistically significant dif- ference.
In this survey such tests required the establishment of two null hypotheses:
H Based on mean scores there is no difference between 1 attributes of stores where each store retains its identity.
H Based on mean scores, there is no difference between 2 the attribute evaluations of stores within the same chain.
These hypotheses were tested for each characteristic using the conventional unpaired observations and unequal variances and computation of the Student 2 statistic. Each attribute per paired store was tested at the 95 percent
2 See Eoonous, Appendix D for formula. - 31 -
3 level of probability.
3.6 Intra-Store Comparisons Across Products
Tables 3.2 through 3.6 present the results of the tests for signif- icant differences between stores (H ). Stores in the left-hand column are com- 1 pared with those across the top on the various product attributes. The presence of a negative sign indicates that the store in the left column was rate. sig- nificantly lower than the store across the top on that attribute. The initials
N.S. indicate that no significant difference existed between the stores on any of the attributes in question.
Table 3.2 presents the significant differences for meat products and confirms the earlier result that Pelosos was the highest rated store in this area. On the other hand, Sunnybrook was the most unfavourably rated. All other stores were favoured over it in this area, excepting Leaders which.was not viewed as being significantly different.
The table also shows that the Dominion and Zehrs chains were rated significantly higher on meat products than the independents, with the exception of Pelosos. A & P, on the other hand was not significantly different from
Leaders, nor was Miracle. Both A & P and Miracle rated generally higher than
Sunnybrook, as one might have expected. Comparisons between chains shows that
A & P and Miracle rated generally lower than Dominion and Zehrs. As one would have expected from Table 3.1, no significant differences were found between the representative Dominion and Zehrs stores (Speedvale and Willow West).
Table 3.3 presents a similar comparison of stores on the five produce attributes. Here Zehrs Edinburgh seems to have rated significantly higher than all other stores excepting fellow Zehrs stores where no differences were found.
3 See Eoonous, Appendix E for complete results. -32 -
TABLE 3.2 1 Significant Differences -- Meat Products
a
Mart
West
Speedvale
Eramos
Food
rook M M Edinburgh Victoria
Wellington
Woodlawn P 0 Willow W M "d 0 0 "4 0 0
Dominion Dominion
Sunnyb
Zehrs
Miracle Zehrs
Zehrs --1 cLi Zehrs Zehrs -1,-3 -1 N.S. N.S. -1,-3 1,2 -3 N.S. -1,-2 -1,-2 -3 A & P -4,-6 -6 -5,-6 -4 -3,-4 -3 -5 -52-6 -6 N.S. 1,3,41,3,4 -2 1,2,3 N.S. 1,4 -2 N.S. N.S. Domion Eram. 5,6 5,6 5,6 -4 4,5,6 _5
1,5 5,6 -2 1,2,3 -4 1 -2 N.S. N.S. Domion Sp. 6 -4! 5,6 -4 _ -5 N.S. -1,-2 N.S. -3 N.S. -1,-2 -1,-2 -5 Leaders -3,-4 , , -5 -5,-6 -6 -1,-3 2 -3 N.S. -2,-3 -2,-3 -3 Miracle -4,-5 -4 '-4,-5 -4,-5 -5 _ . .. . -6 , -5, -6, -6 1,2 5 1,2 5 124 4,5 Pelosos 4,5 3,4 5 6 _ 5,6 -1,-2 -1 -1,-2 -1,-2 -1,-2 Sunnybrook -3,-4 -3,-4 -32-5 -3,-5 _ , -6 75 ' . 3,5 •N.S. 5 N.S. Zehrs Edit. . , -2 -2 N.S. Zehrs Viet. -3 , -5 N.S. N.S. Zehrs Well. - N.S. Zehrs W.W. 1 . ,
Zehrs Wood. ...._ • , , 1. Selection 2. Freshness 3. Convenient package size 4. Price 5. Value 6. Quality
Read for example, A & P was rated significantly lower than Dominion Eramosa on selection, Convenient Package Size, Price & Quality. No significant diff- erence were found on freshness and value 33 -
TABLE 3.3 Significant Differences -- Produce
Mart
West
Speedvale
Eramosa
Food W
Edinburgh
Victoria
Wellington
Woodlawn P Willow W 11 al W
Dominion
Dominion
Sunnybrook Pelosos
Zehrs Miracle
Zehrs Zehrs
Zehrs
Zehrs
1 N.S. -. ,- N.S. - N.S. N.S. 1,-2 N.S. -i,-2-2,-3' A & P _ -3,-4 _5 1 N.S. 1,4 -2 4 1 r-2,-3 N.S. -1 -2,-4 N.S. 1 Domion Eram. 1_4._5 -5 -5 1 i
1,4 -1 4 1 F2,-3 N.S. N.S. -2,-3 7 ' Domion Sp. 5 4,-5 5
-1,-2 N.S. N.S.-1,-2 -2 -3 -1,-2 -1,- leaders -5 1 r3,-4 -5 -4 -3,-4 -3,-4 .-5 _5 _5 _5 1 j -3 N.S. -3 -3 N.S. ' Miracle .. 2 2 -4 -4 5 N.S.-1,-2 -2 -3 -1,-2--1,--2 Pelosos ,-4 .- -4 ,-4 -3,-4 -5 _5 . _5 _5 -4 '-1,-2-1,-2 Sunnybrook -1,-4 -5 _5 _5 . _5 N.S. N.S. N.S. Zehrs Edin. i
N.S. N.S. Zehrs Viet. N.S.1
N.S. N.S. Zehrs Well.
N.S. Zehrs W.W.
Zehrs Wood. I 1. Selection 2. Freshness 3. Price 4. Value 5. Quality - 34 - I.
Zehrs Willow West also rated quite well. Generally, the independents rated lower than the chains on the produce attributes. Zehrs was higher than both
Dominion and A & P. Miracle seems to have fared much better here than in the meat category; in produce price, however, Miracle was rated significantly lower
(i.e., more unfavourably) than several of the Zehrs stores.
The five dairy attributes are compared across stores in Table 3.4.
What is most striking here is the number of non-significant comparisons. This indicates that consumers saw few differences among stores in terms of dairy
products. What differences were perceived seem to be mainly those of price (2),
quality (4) and freshness (5). Once again Miracle was perceived as having
higher prices than most other stores in this area. As expected, there are no
significant differences between the representatives of the Dominion (Speedvale)
and Zehrs (Willow West) chains. It is perhaps surprising that more differences
were not noted between the chains and independents on the characteristics of
selection (1) and freshness (5).
- The area of grocery products (Table 3.5), like that of dairy, also
shows few significant differences between stores. What differences ere perceived
seem to be mainly in package size (1), price (2), selection (4), and quality (5).
It is not surprising that Sunnybrook should have the most negative image here.
Pelosos also seemed to fare badly in this area, while the remaining storeswere
viewed as being very similar. No differences were noted between the Dominion
and Zehrs compared earlier.
s For ease of presentation, store characteristics have been broken into
three groups, in-store, location convenience, and promitional. Tables 3.6
through 3.8 present the significant differences for each of these groups.
Results shown in Table 3.6 reveal several interesting differences. For instance,
Pelosos rated significantly higher, than all other stores on presence of •
- 35 -
TABLE 3.4 Significant Differences -- Dairy I
. - Mart West Speedvale Eramosa Food Edinburgh
m Victoria Wellington Woodlawn Willow C) -%i cz C) Dominion Dominion Sunnyhrook Pelosos Zehrs Miracle Zehrs Zehrs Zehrs
.-1 Zehrs N.S. N.S. N.S. N.S. N.S. N.S. N.S. N.S. N.S. N.S. A & P 1 N.S. -2 N.S.I N.S. N.S. N.S. N.S. N.S. N.S. Domion Eram.
N.S. N.S. N.S. N.S. 1 N.S. N.S. N.S. Domion Sp. 3 4 2 N.S. N.S. N.S. 3 N.S. N.S. N.S. Leaders
N.S. -2 - N.S. Miracle . -3 -4 N.S. -5 N.S. Pelosos
N.S. N.S. N.S. •N.S. Sunnybrcok
N.S. N.S. N.S. Zehrs Edin.
N.S. Zehrs Vict.
. 1 N.S. Zehrs Well.
N.S. Zehrs W.W.
Zehrs Wood. 1 ! 1. Selection 2. Price 3. Value 4. Quality 5. Freshness - 36 -
TABLE 3.5 Significant Differences -- Grocery
1 t 1 _ Mart West Speedvale Eramosa Food Edinburgh
M Victoria Wellington Woodlawn o Willow m o W Dominion Sunnybrook Dominion Leaders Zehrs Zehrs Zehrs Miracle Zehrs P-4 Zehrs i N.S. N.S. N.S. N.S. 1 N.S. N.S. NS. N.S. A & P
N.S. N.S. 2 1 4 N.S. 4 N.S. N.S. N.S. Domion Eram. 4 5 N.S. 2 1 4 N.S. N.S. N.S.N.S.. N.S. Domion Sp. 4 ' 5 1,5 2 N.S. N.S. N.S. 2 N.S. Leaders 3 2
1 4 •-2 N.S. -2 N.S. N.S. Miracle 4 _3
N.S. - - -1 - Palosos -4 . -5 :1 _51 -4 - -4 -41 N.S. Sunnybrook - - ...51
• N.S. N.S. N.S. N.S. Zehrs Edin. .
-4 N.S. Zehrs Viet.
N.S. Zehrs Well.
• • Zehrs W.W. •
Zehrs Wood. I , I I . 1. Convenient package size 2. Price 3. Value 4. Selection 5. Quality - 37 -
TABLE 3.6
Significant Differences -- In-Store Characteristics
'
West ,
Speedvale Eramosa
:.1 rook
Edinburgh
Victoria
Wellington
Willow P Woodlawn W
7J osos
1 M W
Dominion
Dominion
Pe k--1 Sunnyb Zehrs
Zehrs Zehrs
Zehrs
Zehrs
Jf 4 -4 oo 1,5 N.S. N.S.N.S. N.S. -1,-5 A & P 4 - -8 2,6 3,7 -2 -2 -1, 7 -1 6 1,6 _ _ -1,-5 Domion Eram. -4 -4 -3, 8 -2,-8 3,7 - - _ -4,-7
_7 4 -4 5,8 r—i r—i
^ ^ 8 5 N.S. -4, CJ CJ ' 8 -Irm,-8 •D
Domion Sp. 6 4 6 ^ co co
-7 817
in in r-i r-i
-1, 7 ^
- C\rel
/ 4 1 -1 Leaders 4, 8 ar-oo - -6
-6 -,/* I I , 6 1,6 1,61, ,- 1,-7 -4 Miracle -4,-7 i -7 3,-7-4 4 3 -8 -7 -8 ,4 -4 -7 - -4 -8 1,7 8 -6 8 -6 -5 Pelosos , 2,8 8 8 -6 3 8 • -1,- -1,-5 -1,-6 -1,-5 -1,-5 Sunnybrook -2,-6'-6 -2,-7 :.7;'6 -2'-6 -3 :34:- "=:-8 )--'87 -_...,Ig N.S. N.S. N.S. -7 Zehrs Edin.
N.S.' N.S. N.S. Zehrs Vict.
Zehrs Well. '
N.S. Zehrs W.W.
Zehrs Wood. 1 , 1. Cleanliness 2. Ease of finding items 3. Traffic flow 4. Speed of 5. Well-stocked 6. Attractive display 7. Helpful personnel checkout shelves 8. Personalized services. (e.g., butcher, etc.) -38 - personalized services - e.g., butcher. This is consistent with Pelosos' earlier high ratings in meat products and with their reputation. Miracle rated well in cleanliness but compared very poorly in speed of checkout and helpful personnel. Possible reasons for this will be discussed in the final chapter. No significant differences were observed between Dominion Speedvale
Zehrs Willow West, strengthening the earlier conclusion that consumers perceive little difference between these major chains.
The final two groups of store characteristics are presented in
Tables 3.7 and 3.8. Table 3.7 shows the significant differences for location convenience characteristics. Consumers perceived many differences here, as the relatively few N.S. notations indicate. It is notable that the more out of the way stores, particularly Miracle, rated significantly lower on these characteristics except for that of convenience of hours. This particular characteristic seemed to be only significant in the case of Pelosos. Pelosos and the other independents again rated low on promotional characteristics as seen in Table 3.8. Generally, few differences were seen between the chains in this area with the exception that Dominion Speedvale was seen as having more coupons. Both tables show no significant differences between the representative
Zehrs West) and Dominion (Speedvale) stores.'
3.7 Intra-Chain Comparisons Across Products
The analysis was extended to test the hypothesis that there is no difference between the attributes of stores within the same chain (H ). Results 2 are presented in Tables 3.4 through 3.8. In the case of Dominion, the only significant differences between stores seem to be in the ease of finding items, speed of checkout, and nearness to ancillary services. More differences were found among the Zehrs stores with Zehrs Victoria rating comparatively low.
Despite this, the hypothesis is accepted in areas where all stores within a •
_39_
TABLE 3.7 Significant Differences -- Location/Convenience Characteristics _ Mart West Speedvale Eramosa Food rook Edinburgh Victoria Wellington Willow Woodlawu Dominion Dominion Leaders Sunnyb Pelosos Zehrs Miracle Zehrs Zehrs Zehrs Zehrs L N.S. - -2 2,-5 1 N.S. N.S. & P -4 -3 -3 -2,-5A 3 -5 -5 -4 4 5 2, 4 N.S. 5 _ _5 Domion Eram. -3, 3 3,-
-2, 5 2 1 2, -2 N.S. ,- Domion Sp. -4 3 5 4 3 ,-5 4 5 j5 2 22 3 2 3 2,-52 3 4 3 3 3 -4 4 54 4 4 2, 51-2, 2, 5 -2, 5 -2 -2,-5 Miracle -3 :-3 b3 -3 -3 -3 -4 4 -4 -4 -4 -4 1 N.S. N.S. N.S. -2 -5 -1,-4 relosos -4 1,-5 1 _5 N.S. - . -51-2,_S Sunnybrook - -4
,-5 Zehrs Edin. _
,- ,- Zehrs Vict. 3 - -4 _ _ _3 Zehrs Well. 4 5
-2,-5 Zehrs W.W. _3 -4 _ I. Zehrs Wood.
1. Convenience of hours 2. Distance 3. Parking facilities 4. Convenience of location 5. Nearness to ancillary services -40 -
TABLE 3.8 Significant Differences -- Promotional Characteristics
1 Mart West' Speedvale Eramosa Food Edinburgh Victoria Wellington
Cl) Woodlxwn o Willow m- o ,..4 o Dominion Dominion Leaders Sunnybrook Zehrs Miracle Zehrs Zehrs Zehrs P.4 Zehrs i z * z • N.S. N.S. N.S. 1 1 N.S.t N.S. cn cn • A & P . 1 1
N.S. N.S. N.S. 1 1 N.S. N.S. I.) z . Cl) • Ni Domion Eram. •1
, 1 1 r.) z . cni Z • ci) . . Dowion Sp. 2 3
1 i I i i
N.S. 1 1 N.S. N.S. . i
Leaders . . . . 1 r 1 z cr) Ni . N.S. N Miracle I
, -, i I 1 I.) IL F I-1 -1 1---
_3 _3 I 1 (.1.) u4.3
Pelosos li,-) .,.
1
, I 1 1 1 I—,
1-.1 -1 1 .
). 1 I 1
Sunnybrook 1 ( t..) 1 1 1 . z ci) . N.S. r.) Zehrs Edin.
cil .1 i)
Zehrs Vict. .
1 1 ) & z1.) ci) . t Zehrs Well.
1 I
...... , z
Zehrs W.W. ..______
1
Zehrs Wood. 1 I r 1. Informative ads 2. Number of coupons 3. Number of specials 1 - 41 - chain pursue a common policy. This and other results will be explored more fully in the final chapter. - 42 -
4.0 CHOICE OF THE MODEL VARIATION
4.1 Variations of the Multi-Attribute Model
Two of the stated objectives of this study were to test the capability of the multi-attribute model in predicting supermarket choice and to compare the explanatory power of several variants of the multi-attribute model in predicting supermarket choice. These objectives are discussed in this section, and it is hoped that the results will be useful for both purposes of predicting consumer behaviour and clarifying management decisions.
To accomplish the above objectives, seven variants of the multi- attribute model as used by Bass and Wilkie (1973, pp.265) were investigated.
These variants are listed in Table 4.1. In accordance with suggestions made by 1 Bass and Wilkie, belief ratings were normalized to adjust for variation of responses between consumers. Importance scores were not normalized because such a procedure would have resulted in an average importance rating. Belief ratings used in the models were measured by bipolar scales involving the semantic differential technique, while importance weights were obtained directly by a specific question.
Table 4.1 shows that several of the variants investigated used average scores while others used summated scores. As mentioned earlier, the question of average versus summated is one of the issues in the use of the multi-attribute model. Thus they were included here in order to assess their impact on the explanatory power of the model.
1 Normalization was achieved by use of the following formula:
SB B /(E. B.. /P.) ijk ijk j ijk 1
where SB = the normalized belief score
Pi the number of the respondents who rated attribute i for each store. -43 -
TABLE 4.1 Variants of Basic Model
Summated Belief Scores:
P = f(A ) E B. jk jk i=1 lik Average Summated Belief Scores:
P f(A jk) jk = (. E B, )/N i=1 1-31(
3) Summated Belief Scores of Reduced Variables
P = f(A ) = E B. jk i=1 ijk
Average Summated Belief Scores of Reduced Variables
= f(A ) = ( E B.. )/M Pjk jk ijk i=1
5) Belief Times Importance Scores of Reduced Variables
P = f(Ajk ) =EBI jk ijk ik i=1
Average Belief Times importance Scores of Reduced Variables
P= f(A = ( E B I )/M jk jk) ijk ik i=1.
7) Normalized Belief Scores
P = f(Ajk ) = E SB.. jk i=1 1Jk
where: P is consumer k's preference rank for store j jk A is consumer k's attitude score for store j jk B. is consumer k's belief as to the extent to which attribute i is offered by store j
I is the importance weight given to attribute ik i by consumer k
= 37 - the original number of variables 7 - the reduced number of variables and 5 = normalized belief scores -44 -
Obviously, the study wanted to use the variation of the model with
the highest predictive power for the stores in the study. Thus all the variants
were first applied to one store in order to establish the one with the highest 2 coefficient of determination (r ). This variant was then applied to the other
stores in the study. As mentioned earlier, most studies of the multi-attribute 2 model rely on the r value as a measure of predictive capability. Although this
study contends that a more valid measure exists, it too, for the moment, will 2 rely on the r coefficient obtained from simple linear regression. A later
section will offer an argument in favour of a different measure of predictive
capability.
4.2 Application of Test to One Store
Before choosing the model variant to be applied to all stores, the
seven variants were applied to Miracle Food Mart because it had the largest
number of observations. Eighty-two of the 150 respondents evaluated it, and
this provided sufficient degrees of freedom for the regression analysis.
Seven simple regressions were executed with P (actual rank) as the jk criterion variable and A (attitude score) as the predictor variable. jk 2 Table 4.2 presents a summary of the r coefficients obtained. It is immediately
obvious from Table 4.2 that none of the variants resulted in particularly high 2 2 r values. In fact, the highest r obtained was .37 for variant 7, normalized
belief scores. This implies that respondents' attitude scores explained 37 per-
cent of variance of actual rank.
4.3 Results of the Test
A comparison of the variations using summated and average scores 2 (1 and 2, 3 and 4, and 5 and 6) shows that the identical r values resulted in each case. Thus the conclusion of no difference between summated and average attitude scores appears to be well substantiated. Mill MIN MIN OM 111111 IIIIII MIMI NM 11111 111111 11111 all MI Ell MIN MINI OM
TABLE 4.2 Regression Results of Seven Variants
2 (a) (b) (c) Variant Descriptions R Square (r ) B BETA F
1. Summated Belief Scores .17303 -.01956 -.41597 16.739
2. Average Summated Belief Scores .17303 -.72364 -.41597 16.739
3. Summated Belief Scores of Reduced Variables .20993 -.10241 .45818 21.257 .
4. Average Summated Belief Scores of Reduced Variables .20993 -.71686 -.45818 21.257
5. Belief Times Importance Scores of Reduced Variables .23270 -.01641 -.48239 24.261 Ln 6. Average Belief Times Importance Scores of Reduced Variables .23270 -.11484 -.48239 24.261
7. Normalized Belief Scores .36986 -.89316 -.60816 46.955
(a) B = the unstandardized coefficients
(b) BETA = standardized coefficients
) F = F statistics, all of which are significant at the .01 level of significance. -46 -
The original 37 variables were used to form the attitude score in
both variations 1 and 2 while the remaining variations relied on scores obtained .2 from seven reduced variables As expected, the longer variable list yielded 2 lower r values (.17). This seems to indicate that fewer composite variables 2 did indeed produce higher r values and thus explained a greater proportion of
the variance in preference rank.
As a result of this and other tests, later multiple regression
analysis for the stores involved mainly variant 7, normalized belief scores.
4.4 Alternate Tests of Predictive Capability
2 Based on the highest r value, a common if questionable measure of
predictive ability used in studies of the model, the normalized belief score
variant (7) was tentatively chosen for further analyses. However, although 2 this variant did give the highest r of the seven, it still accounted for only
37 percent of the variance. This implies that 63 percent of the variance of
the actual rank is left unaccounted for. There are several explanations for
this undeniably poor showing, including failure to .select relevant variables and exclusion of socio-economic and demographic variables. However, based on available evidence, the most plausible explanation seems to be the inadequacy 2 of the r value as a predictive measure. Two other methods were therefore used: the confusion matrix and the Spearmen's rank order correlation coefficient (r ). s
4.5 Confusion Matrix
The first of the aforementioned methods to measure the predictive strength of the model is that of the confusion matrix. Confusion matrices were constructed for the seven attitude models for Miracle Food Mart. The full set
2 A discussion of factor analysis used to reduce the original variable list follows in Chapter 5. •
-47- of matrices are contained in Eoonous, Chapter 15. For illustration, Table 4.3 presents the confusion matrix for variant .1, summated belief scores. A summary of the percentage of correct prediction obtained for each variant from the con- fusion matrices is presented in column 2 of Table 4.4.
In Table 4.3, the raw entries represent respondents' predicted ranks while the column entries represent their actual ranks. Reading across row one, seven respondents who actually ranked Miracle first were predicted to do so by
the model; one respondent ranked it first but her predicted rank was second, while one actually ranked it first but was predicted to rank it fourth or fifth.
The figures enclosed in parentheses may be viewed as the percentage represen-
tation of the frequency distributions of respondents' predicted rank given their
actual rank. The cumulative percentage values of the main diagonal give the
percentage of correct prediction.
• The confusion matrix method is in keeping with the rationale behind
the whole idea of the attitude niodel; that is, the predicted rank derived from
the evaluative attitude scores of respondents (Ajk) should be identical to their
actual rank of the stores (Pik). In other words, the higher the store is ranked,
the more favourable attributes it should possess. Consequently, the attitude
score for the highest ranked store should be higher than that for any other
store.
This represents, of course, the ideal situation and results in perfect
prediction. In a confusion matrix, its occurrence will result in a dominant
main diagonal with no off-diagonal elements. • This is because each off-diagonal
element represents a case where the predicted rank failed to agree with the
actual rank. An examination of Table 4.3 shows a dominant main diagonal. The
cumulative sum of this main diagonal gives the percentage of correct prediction
while the off-diagonal cumulative score gives the percentage of incorrect pre-
diction. -48 -
TABLE 4.3
Summated Belief Scores
Predicted Rank Actual Rank 1 2 3 4 5
1 7 1 1 0 0 (8.5) (1.2) (1.2)
0 15 3 1 0 (18.3) (3.7) (1.2)
3 0 4 27 7 0 (4.9) (32.9) (8.5)
4 0 0. 2 12 0 (2.4) (14.6)
5 0 0 0 0 2 (2.4)
Percentage Correct Prediction = 76.7
Number of Observations .= 82 - 49 -
An examination of column 2 of Table 4.4 shows that, with the excep- donof variant 3, the percentage values obtained from the confusion matrices for each variant are only marginally different; however, variant 7, normalized belief scores, seems to give the highest correct predictive percentage.
Although the confusion matrix method is a useful and easily understood test, it has certain limitations, primarily its apparent lack of statistical varification. This method gives primarily right and wrong classifications without accounting for the distributions of observations within the matrix,
the strength of the relationship between the actual and predicted rank, and
the statistical significance of the measure. As a result, it is not a popular method of predictive capability.
4.6 Spearman's Rank Order Correlation Coefficient: A Test of Predictive Potential
In this study, the distribution of the observations within the matrix
assumed great importance. Therefore, the acknowledged limitations of the con-
fusion matrix method made it necessary to find an additional, more relevant
measure of predictive capability. Such a measure is the Spearman's rank order
correlation coefficient (r ) which establishes the strength of the relation- s ship between the actual and predicted rank, explains the variances of the
criterion variable (actual rank), and provides a test of statistical signif-
icance.
This study contends that the Spearman's rank order correlation co-
efficient (r ) is a better test of the predictive potential of the model. s This idea was tested by using the attitude scores (Ajk) derived from the seven
regression equations to obtain the predicted rank of the respondents. The
actual ranks (Pjk) were then regressed with the predicted rank ) and the (jk resulting r values were used as a test of the predictive capability of the s variant. - 50 -
The r values, obtained are listed in Table 4.4 along with the level s of statistical significance. It is noticeable that all variants have reasonably high predictive power. Generally, however, variants 4 and 5 seem to have the weakest prediction potential while variants 2, 6, and 7 have the strongest. The differences in these last three are marginal. It is noted that the statistics from the confusion matrix for Miracle (column 2) are not the same as the r s values (column 7). This is understandable because the r has accounted for the s variances of observations within the matrix and this has changed the predictive capability of the variants. Since many of the differences among variants are not significant, results are not conclusive as to which has the highest predic- tive power. However, variant 7 does seem to yield the most consistent rs values as well as the highest correct prediction percentage from the confusion matrices.
Based on this, variant 7, normalized belief scores, was used as a measure of the predictive capability of the model.
A look at the last row of Table 4.4 shows that with the possible exception of A & P, the model, as represented by the normalized belief score variant, established a very strong relationship between the actual and predicted ranks with acceptable statistical accuracy. In fact, the results are all sig- nificant at the .001 confidence level. MINI II= 111111111 1E11 11111 INN WIN MIN ale IIIIIIII MIN MI MINI OM OM 11111 11111
TABLE 4.4 1 Spearman's Rank Ordc:r Cor:-elcation (':oefficient3 ) 12 Stores S
4 W. 0 OO 0 0 0 •r4 4.1 Era, 0 Woodlawu Edinburgh 0 Willoy flodel Variant NA 0 1.4 14 X ii 0 Zehrl
Zehra 0 Do=icion
(2 (3) . (4) (5)__•__j). (10) (11) (12) (13) (141
1) Sur:mated Belief Scoreu 7.6.7. .7401 .6802 .7559 .8774 .8160 .7164 .8189 .7854 .6188 .7350 .8148 .9680 (.001) (.061) (.001) (.001) (.001) (.001) (.001) (.001) (.001) (.001) (.001) (.001)
2) Average Summated Belief Scores 76.7 .6501 ..7447 ,8600 • .8059 .8335 .8760 .8731 .7934 .7442 .8663 .8910 .9914 (.001) (.0)1). (.001) (.001) (.001) (.001) (.001) (.001) (.001) (.001) (.001) (.001)
3) Suited Belief Scores of Reduced 75.5 .6706 .7824 .7547 .8376 .8232 .7297 .7779 .6339 .8312 .7271 .8709 .9206 Variablen (.001) (.001) (.001) (.001) (.001) (.001) (.001) (.001) (.001) (.001) (.001) (.001) It) Delief Tim,!s Importance Scores of 76.8 :1721 .7280 .6973 .6106 .7868 .6711 .7593 .6238 .7597 .7070 .7427 .9166 Eeemeed Variables (.135) (.001) (.001) (.001) (.001) (.001) (.001) (.001) (.001) (.001) (.001) (.001)
)Ave!rage Baief Times Importance 78.0 .3"J72 ,7791 .7080 .8218 .7679- .7690 .7337 .8063 .9002 .6961 .7451 .9721 Scurea of Reduced Van:Coles (.014) (.001) (.001) (.001) (.001) (.001) (.001) (.001) (.001) (.001) (.001) (.003)
6) Avarage Summatzd Belief Score's 78.0 .6275 .5008 .3627 .8103 .8090 .8993 .8561 .6965 .9430 .8759 .3732 .9E08 of Raduced Variables (.001) (.001) (.001) (.001) (.001) (.001) (.001) (.001) (.001) (.001) (.001) (.001)
7) Wormplized Belief Scoren 79.2 .6C37 :8154 .8301 .8218 .8141 .8760 .8002 .8913 .8938 ,.8578 .8875 .9721 (.001) (.001) (.001) (.001) (.001) (.001) (.001) (.001) (.001) (.001) '(.00.1) (.001)
1 Numbers in parendieses indicate significance level. .
9 From coufusion matrices. - 52 -
5.0 ATTRIBUTE IMPORTANCE
5.1 Introduction
The results summarized in Chapter 4 indicate that the normalized
belief score variant of the model yielded the best prediction potential.
Since the attitude score (Ajk) used in this variant is made up of the sum of 1 several store characteristics, it is obviously of interest to both management
and researchers to determine which of these attributes are the most important in
in the determination of consumers' preference for supermarkets. It was also
considered useful for both market segmentation and future research to invest-
igate the importance of socio-economic and demographic variables in determin-
ing supermarket choice.
In order to accomplish the above objectives, factor analysis and
multiple regression analysis were used. The remainder of this chapter summa-
rizes these procedures and their results.
5.2 Factor Analysis
The original 37 store characteristics, though useful in the semantic
differential technique, provided problems for regression analysis. The large
number of criterion variables imposed a severe constraint on the degrees of
freedom, especially since the number of observations were relatively small. 2 In order to circumvent this problem, factor analysis of importance
ratings was employed to reduce the 37 variables into fewer heterogeneous factors.
It also provided a confirmatory measure to test the hypothesis that in their
evaluation, consumers consider product category along with other physical and
1 See Table 4.1 for formula. 2 See Eoonous, Appendix F for a brief description of factor analysis. -53 - service characteristics rather than individual attributes such as price, quality of product, and so on.
The data reduction capacity of factor analysis hinges on the rationale that every hypothetical factor incorporates variables which are easily iden- tifiable and which describe the same general concept. The procedure trans- formed each of the 37 variables into a linear combination of nine hypothetical 3 factors. Table 5.1 presents the summary statistics for the nine reduced var- iables. Those seven whose eigenvalues exceeded one were selected for further analysis. Together these seven factors accounted for 93.1 percent of the total variance of the original list of variables. Factors eight and nine were ex- cluded because they contributed only marginally to the cumulative percentage scores. However, many of the excluded variables loaded fairly high on some 4 of the included factors and thus were classified accordingly.
The seven new variables were:
1) Dairy Products 2) Meat Products 3) Produce 4) Grocery Products 5) Ease of Shopping Locational Convenience 7) Promotional Activities
These variables are listed in Table 5.2 along with the original variable des- criptions and their respective factor loads. In this bulletin, they are re- ferred to as reduced variables and are used for most of the regression analyses, including that discussed in Chapter 4.
3 See Eoonous, Appendix G for complete factor loadings. 4 A more detailed description of the procedure is found in Eoonous, Chapter 4. 1111111111
MO
72.3 28.9
45.7
80.4
87.0
97.2 93.1
100.0
.59.8
Cumulative
Percentage
INS
ISO
NO
1111111
Factors of
5.1
2.8
8.1 4.1
6.6
6.2
28.9
14.1
16.8 12.5
Variance
Percentage
lila
TABLE
Reduced
IMO
NIB
.
SIM
3.873
2.868
1.526 1.855
3.293
1.415 6,645
0.938
0.637
SIM
Eigenvalues
UN
OMB
7
2
3
4 6
1 5
Factor
MIN
11111 -55 -
TABLE 5.2 NEW VARIABLES AND THEIR COMPONENTS * New Variables Components Factor Load
Dairy Products Wide selection of dairy products 0.69 Low prices of dairy products 0.78 Good value for money spent 0.93 Good quality dairy products 0.93 Fresh dairy products 0.93 Meat Products Wide selection of meat products 0.58 Fresh meat 0.79 Convenient package size 0.52 Low prices 0.76 Good value for money spent 0.94 Good quality meat products 0.92 Produce Fresh produce 0.87 1 Wide selection of produce 0.48 Low prices 0.55 Good value for money spent 0.87 Good quality 0.92 1 Grocery Products Low prices 0.29 Good value for money spent 0.72 Good quality grocery products 0.80 Ease of Shopping Ease of finding items 0.70 Ease of moving through store 0.92 Fast check-out service 0.621 Convenient shopping hours 0.41 Ease of finding parking place 0.37 Locational Convenience Nearness of location 0.83 Convenience of location 0.85 . Nearness to banks, etc. 0.47 1 Promotional Activities Informative ads 0.29 1 Many coupons 0.23 Large number of items specially priced 0.57
1 These variables load marginally higher on other factors, but because the factorial complexity is greater than 1, that is, there is no one dominant factor except for f lo prices of grocery products', which explain the communality, it was considered convenient to reclassify them with the corresponding new variables. - 56 -
The clearly identifiable product classifications which emerged from factor analysis do indeed lend support to the hypothesis that consumers' se- lection of supermarkets is governed by their assessment of product category along with locational convenience, ease of shopping, and promotional activities.
It should be noted, however, that each product category implicitly accounts for the attributes of price and quality. In other words, the new variables could be viewed as summary representation of more detailed components.
5.3 Multiple Regression Analysis
Important store characteristics and socio-economic and demographic 5 variables were investigated using multiple regression analysis, in which each variable was allowed to retain its identity. Respondents' actual ranks of each store were regressed with the seven store attributes and ten socio-economic and demographic variables were included on a step-wise basis. Since iterations continued until the F-values became insignificant, it was arbitrarily decided to extract significant variables from the first iteration where all the ex- 6 cluded variables had F-values of less than one.
5 The following equation was used:
P. = a +bEB +cz+cz +... cz i=1 ijk 11 22mm where P consumer k's preference rank for store j. jk X. = store characteristics. z dummies for socio-economic and demographic variables. k a = constant. and b and c = regression coefficients. For further details, see Eoonous, Chapter 6.
6 See Eoonous, Appendix H for examples for each store. - 57 -
Table 5.3 presents the summary statistics of the significant coeffic- ients obtained from the regression analyses of the 12 stores. Column 1 pre- 1 sents the description of the variables used in the analyses while columns 2 through 13 reproduce both the standardized and unstandardized beta (b k) co- efficients for each store. The standardized coefficients are enclosed in parentheses. Each coefficient was tested at the 0.05 percent level of signif- icance, but those noted were found to be significant at the 0.1 percent level of significance. The presence of the minus sign in front of each store char- acteristic implies that if all other variables are held constant, a one unit increase in the value of one variable will result in a decrease of the value of the rank by the size of the corresponding unstandardized coefficient. Con- sumer ranking of stores ranged from 1 to 5 with the higher numbers indicating a poorer ranking. Therefore, a decrease in rank resulting from a minus sign indicates an improvement in the store's evaluation.
Interpretation of the unstandardized socio-economic and demographic coefficients is made with respect to the reference categories which are iden, tified by the second footnote. Once again the negative sign implies improved evaluation, while 4 positive sign indicates inferior evaluation.
An idea of the actual importance of each significant characteristic
as a determinant of store choice is given by the standardized coefficients,
often referred to as beta weights. The larger the beta weight, the more
important that characteristic is in the store's evaluation.
5.4 Overview
The above discussion is meant to aid the reader in interpreting
Table 5.3 for himself since a detailed discussion of each store is not prac-
tised. This section will, however, provide an overview and discussion of the
general trends which emerge from Table 5.3. - 58 -
TABLE 5.3 1 Disaggregated Regression Results: 12 Stores
4,1„...... V et3 . A CU V el C :1 V ,..., i is Z t,C , F to A .3 0 •4 III ine' X C .. •4 7 8 -0 c., Variable Descriptions Ito g g s )4 w ..il 5 ra 11 c c . ig It.5.1 t. 0 1 CO C to Vt 4 li -1:1 ". ..1 C A ..0 A . ✓ 0 < A O ..1 • A A A (2) (3) (4) (5' (8) ) (10) _(11) i17) Ileat -1.59 -1.20 -2.78 -1.91 (-0.18) (-0.20) (-0.47) (-0.27) (121 Produce -2.49 -2.85 -2.3e (-0.47) (-0.37) (-0.36) Dairy -1.86 -2.54 -5.73 (-0.22) (-0.44) (-0.44) Crocery -3.42 (-0.32) (,0.27) Lase of. Shopping -2.69 -8.40 (-0.26) (-0.60) Locational Convenience -1.24 -1.54 -1.41 -2.28 -1.37 -2.15 -1.29 -1.66 -1.78 -1.02 (-0.31) (-0.88) (-0.35) (-0.42).(-0.50) (-0.45) (-0.43) (-0.34) (-0.54) (-0.39) Promotional Activities -1.02 -6.20 (-0.16) (-0.37) (-0.3.5) "tel.; Local Newpaper 1.04 -1.13 -1.89 -1.39 1 ( 0.44) (-0.41) (-0.58) Zid Not Itead L:ctl Fspers2
Tr;yste TrALaportLtion (cars)
2 Criers (Public Trans., walk, etc)
2 Yobers in Hourthold -0.49 1.52 2 (-0.23) • (0.20) Over 2 rer.bers
E-ofessional Vorkers
Cther Wotketz 1.43 0.73 ( 0.67) (0.35) Students, Unexrp1o7ed,1etired
Live Less than 5 years in Guelph
Live 5 years and over i Cuelph-
Soft: Ugh School Education
Sate ColleEe Education 0.92 (0.32) C.92 2 (0.45) Cauplete College Education.
Incost less than $10,000 • -1.18 letween $10,000 and $30,000 (-0.41)
O'er $30,000 '2
Degree of tresdaa 1/28 1/53 1/62 1/41 1/72 1/10 1/17 1/21 1/10 1/17 1.147 1/16 1 ••••••••••••••••••• Sivniticant at .1 Level of Significance, all others are significaot at .05 level. 2 These variables did Lot cater the eq4Acion. They were used as reference category. -59 -
Based on the significant store attributes listed in Table 5.3, no store emerges with a distinct profile. It is interesting to note that the significant store attributes are all negative, indicating that they result in an improved rank in each case. This seems to indicate that consumers have no strong objections to any of the stores on any of the attributes.
The attribute which is important for the most stores is that of locational convenience, which is significant in 10 out of 12 cases. The im- portance of this attribute is supported by the consistently large beta weights obtained for it. Thus, in each case it would appear that locational conven- ience plays an important role in consumer evaluation of supermarkets.
Meat also appears to exert an influence on consumer preference. This is particularly true for Pelosos, which is what one might expect given earlier results. Locational convenience, on the other hand, is not significant for
Pelosos, indicating that consumers disregard it totally when evaluating this store.
The Dominion chain does not _emerge with a distinct profile. This is surprising since they stress meat as their strong point. Meat is indeed sig- nificant for Dominion Speedvale,.but only at the 0.1 level. The accompanying small beta weight indicates that it is not as important a characteristic as some others for that store. The most important attribute for the Dominion chain appears to be locational convenience.
The Zehrs chain, on the other hand, seems to have a relatively distinct profile on produce. Generally, Zehrs is evaluated mainly on produce
and locational convenience. The significance of produce here is not unexpected,
considering earlier results.
Given the emphasis placed on promotional activities, it is interest-
ing to note that this attribute does not seem to be a particularly important -60 - influence on consumer choice. Overall, it can be said that locational conven- ience emerges as the predominant influence on consumer evaluation with meat and produce exerting some influence. The other attributes are significant only in isolated cases.
There are remarkably few significant socio-economic and demographic variables in Table 5.3. Those that are significant have a mixture of favour- able and unfavourable effects on consumer evaluation. If, for instance, a respondent reads the local newspaper, this seems to have an adverse effect on her rating of Pelosos, probably because Pelosos' small ad compares badly with the larger more impressive Zehrs ads. Other significant variables here could perhaps be explained by their relationship to the all-important variable, locational convenience. Generally, socio-economic and demographic variables do not seem to effect consumers' evaluation of supermarkets.
The overriding influence exerted by locational convenience prompted further investigation. When respondents' first rank stores were related to the relative distance of the stores' locations,128 of the 150 respondents
(85 percent of the sample) were found to have ranked the store nearest their home first. This seems to confirm that locational convenience is indeed the most influential factor in determining consumers' supermarket evaluation.
In summary, the model confirms that the overriding determinant of consumer preference for supermarkets is locational convenience. In certain cases, meat, produce, dairy products, and promotional activities are somewhat important, but this is far from universal; in fact, only meat could be said to exert any real general influence. It also seems that socio-economic and demo- graphic variables have little influence on store preference.
Obviously these findings have certain implications for management which will be discussed in the next and final chapter. - 61 -
6.0 DISCUSSION AND IMPLICATIONS
6.1 Introduction
This bulletin discussed a study which measured consumers' preference for supermarkets by use of the multi-attribute model and identified the attrib- utes which motivate consumers to prefer a particular supermarket. Data was obtained.from a questionnaire measuring belief and importance ratings as well as various socio-economic and demographic information. It was administered to
150 respondents in Guelph, Ontario, by means of personal interview. The twelve stores rates were selected to represent major chains and independents. Each store was rated on 37 store and product characteristics. The study also in- vestigated certain methodological issues, including the predictive power of the multi-attribute model in general and of various forms of the model in particular.
Specifically, the objectives'of the study were the following:
1. To develop a profile of supermarkets based on consumers' evaluative per- ceptions of the stores' attributes and to identify significant differences among stores.
2. To determine the extent to which stores within a chain are significantly different in terms of consumers' evaluation of their respective attributes.
3. To test the capability of the multi-attribute model in predicting consumers' choice of supermarkets.
4. To compare the explanatory power of alternative formulations of the multi- attribute model.
5. To investigate the extent to which various store attributes influence con- sumers' choice of supermarkets.
6. To investigate the extent to which socio-economic and demographic variables influence consumers' choice of supermarkets.
The following sections contain a brief discussion of the study's findings on
each of these points along with the resulting managerial and methodological im-
plications. Limitations of the study and suggestions for future research are
also included. -62-
6.2 Comparisons Among Individual Stores and Among Stores Within Chains
The supermarket profiles developed by use of consumer evaluations in the semantic differential technique proved very useful in highlighting the comparative weaknesses and strengths of the various stores. Accompanying statistical tests identified significant differences among stores on the attributes. The results indicated that chains were generally rated higher than independents by consumers. The lowest rated store of the twelve proved to be Sunnybrook, and this evaluation seems to be supported by the fact that
Sunnybrook was subsequently converted to a warehouse.
The most signicant differences among stores appeared in the areas of meat and produce; few appeared in the dairy and grocery areas. This is particularly interesting because, while most stores carry basically the same lines of branded grocery and dairy products, the meat and produce stocked are more in the line of "house brands;" in other words, the meat and lettuce stocked by Zehrs can be regarded as "Zehrs meat" and "Zehrs lettuce" while the dairy products will be Donlands or GayLea. Thus it is only logical to expect more differences between stores in the areas of meat and produce.
Several differences were found in the area of in-store character- istics, particularly in check-out speed and helpfulness of personnel, as well as in location/convenience characteristics. Few differences were found for promotional characteristics except overall between independents and chains, as one might expect.
A discussion of the rating received by Miracle Food Mart provides an illustration of the technique's usefulness in supermarket evaluation.
Overall, Miracle was by far the lowest rated chain store of the group, although in the areas of cleanliness and produce it rated very well. There are several logical explanations for this: Miracle is the newest store in the group. -63 -
It is undeniably spacious bright, and clean, and deserves the high cleanliness . rating it received. It displays a large amount of fresh, appetizing produce on well-ordered and well cared for displays -- thus the high produce rating.
However, as the newest store, it also incorporates some new concepts which are not familiar to consumers. Chief among these is its check-out system where cashiers both check out and pack the groceries before sending them out to a car pick-up station. Miracle rated very low on check-out speed, which is understandable since cashiers must both check and pack the groceries. Conceiv- ably, since the store had just opened, cashiers had not yet achieved the level of speed and confidence necessary to utilize the system to the best advantage.
This could also account for Miracle's poor rating on helpfulness of personnel.
A harried cashier, concentrating on her machine, is likely to be of little help in answering questions.
Miracle also received poor ratings on locational convenience.
A glance at the map in Appendix C will give some indication why. Miracle
(number 5) is located well away from the areas of densest population. Given the importance of location, this would seem to be an overwhelming handicap.
However, one speculates that Miracle has almost certainly located here in anticipation of future population growth. There is definitely indication of large scale building in the area. Management is thus willing to sacrifice some present volume in hope of future greater volume and would not be unduly upset by their present comparatively low rating on locational convenience.
It is unquestionable that at present, Miracle's location seems out of the way to the majority of respondents.
What is of chief interest to researchers and to management is that this study correctly identified the above as areas of comparative weakness for
Miracle; time will tell whether or not they remain areas of weakness. -64 -
When the profiles of stores within a chain were compared, few sig- nificant differences were found. In fact, the only differences appeared to be concentrated in the areas of freshness and selection. These are areas affected by sales turnover and by individual store management, and some dif- ferences are therefore to be expected. More important was the lack of dif- ferences in areas which are governed by a common chain policy -- the areas of pricing, newspaper advertising, And quality of product. Here all the stores within the chains were viewed as similar, as well they should have been.
These results indicate that the semantic differential is more than adequate to show .the comparative standing of stores, particularly when accom- panied by tests to determine significant differences.
6.3 Predictive Power of Model Variants
Attempts were made in this study to establish the multi-attribute model as an acceptable tool to predict consumers' choice of supermarkets, as well as to compare the predictive power of several variants of the model. 2 Results were based on the traditional but questionable r value, confusion matrix, and Spearman's rank order correlation coefficient (r ). Of these s methods, the r value was argued to be the most acceptable as a measure of pre- s dictive power. Based on the r values, all variants investigated produced statistically acceptable relationships between actual and predicted rank. No significant differences existed between the three variants with the -highest predictive power. All variants also produced high percentages of correct pre- diction as measured by the confusion matrix. The highest percentage was pro- duced by the normalized belief score variant. Based on consistency of r results across stores and results of the confusion matrix, the normalized belief scores variant was used in further analyses.
Thus the results of the study provide support for the use of the -65 - multi-attribute model in the prediction of consumer preference for supermarkets.
It also puts forth the Spearman's rank order correlation coefficient (rs) as 2 a more effective measure of predictive power than the traditional r measure.
6.4 Influence of Store Attributes and Socio-economic Variables on Consumer Evaluations
Factor analysis and regression analyses were used to determine the importance of the various store attributes and socio-economic and demographic variables on consumer evaluation. It is felt that the results will be par- ticularly useful in helping management develop an effective marketing strategy.
First of all, the results of factor analysis indicate that consumer preference is based on assessment of product category and other physical and service characteristics rather than on more traditional individual attributes such as price, quality, etc. Subsequent multiple regression analysis isolated locational convenience as the most influential attribute. Meat and produce were also determined to have some influence, but promotional activities had little. Socio-economic and demographic variables exerted no real influence on preference.
Obviously, these results have important implications for management.
The indicate that the most important characteristic consumers look for in a supermarket is locational convenience. Some secondary consideration is also given to the meat and produce offered. In traditional marketing terms, the
Place and Product of the Four P's have assumed ascendancy ofer Price and Pro- motion. Because consumers shop by product category, price did not even emerge as a significant factor on its own, although it was implicitly considered in each category. This seems to be in keeping with the comment made by a Stein- berg supermarket executive: "There is no such thing as price competition any more. Price competition is practically absent. It's service competition that
11,1 is taking place .00.0
1 Guelph Mercury, Wednesday, June 16, 1975, .17. Made by an official of the Steinberg Food Store Chain of Montreal. -66 -
The failure to discover any significant socio-economic or demographic
variables and the overpowering importance of locational convenience indicate
to management that effective market segmentation is best confined to the
geographical location of the store. Ideally, a store should be located in a
densely populated area. In areas where several stores are located, emphasis
should be 'placed on meats and produce.
The failure of Promotion (i.e., newspaper advertising) to emerge as
a significant influence is once again in keeping with the comment made by a 2 Steinberg executive: "It's wasteful advertising. It doesn't increase buying".
The results of this study lead one to suggest that stores can cut down on their
advertising space and confine what advertising they do to informing consumers
of specials, especially in the areas of meat and produce.
This study seems to confirm that Price is not the most important element in the marketing mix, at least not to consumers. This is supported by a recent article in the Globe and Mail (February 8, 1978) suggesting that supermarkets cease selling "the price discount story" and "do some solid market research to determine what customers really want." The most influence now seems to be exerted by the locational convenience of the store (Place), meat, produce, and service characteristics (Product), and finally, Promotion.
The study also indicates that attempts to carve out a target market will be most effective when based on geographical location rather than on socio-economic and demographic variables. This is especially true for chain stores. Specialty stores or those that cater to specific ethnic groups are a different case and were not included in this study, although to some extent Pelosos could be clas- sified as a specialty store because of its concentration on meat. Significantly,
2 Guelph Daily Mercury, op.cit. 67 - meat products rather than locational convenience proved the most influential attribute for Pelosos. This seems to provide further confirmation for the method used to measure consumer preference in this study:
6.5 Methodological Contributions to Managerial Decision Making
This study found that both the semantic differential technique and the regression analyses provide useful information for management. In cases where management is interested in a detailed description of the store's image in comparison to other stores, the semantic differential is particularly rec- ommended because it handles long lists of variables effectively. This tech- nique is very useful for revealing relative strengths and weaknesses, partic- ularly when accompanied by statistical tests to determine significant diff- erences. If management is only interested in making comparisons among stores on a list of attributes, the semantic differential obviously has much to offer; however, if management wants to know what motivates consumers to prefer a par- ticular store, then regression analysis is more appropriate.
This study found that both basic linear regression and multiple regression provided useful information; in fact, this study tends to view them as a single model which involves two steps. The first step establishes the reliability of the data as well as its predictive capacity, while the second step indicates to management which attributes are the significant influences in determining consumer preference. Other than a respondent ranking of stores, the regression model requires the same basic information as the semantic dif- ferential technique, so the two can be used together quite easily.
6.6 Limitations of the Study and Recommendations for Future Research
No study, however well planned and executed, is without certain limitations. In this case, the limitations resulted from the usual financial constraints. In order to acquire reliable information on the 37 original - 68 -
variables, the personal interview technique was necessary and a professional
interviewer was hired. Unfortunately, the resulting cost imposed a restriction
on the sample size. In addition, most interviews were conducted during the day,
and because no recall procedure was used, the survey included mainly non-working
wives. These limitations, though not considered serious, are noted for future
research.
The seven variables which emerged from the original.37 should be of
help to future researchers in overcoming the above limitations. These seven
variables reflect current business emphasis and are therefore considered 3 reliable. Obviously, a much shorter and simpler questionnaire could be used
to gether information on them. Such a questionnaire could be effectively and
inexpensively administered by mail to a much larger sample than used in this
study.
The importance of locational convenience also prompts a suggestion
for future research. All the stores in the study, with the exception of
Dominion Eramosa and Leaders (See Appendix C), were located well away from
each other. If stores compete within the same geographical area, undoubtedly
other variables would assume greater importance since location would be held
. constant.
In closing, it is felt that this study, despite certain acknowledged
limitations, has provided useful information which will aid both management
and researchers in the area of measuring consumer preference.
3 In addition to the seven variables, it is also recommended that the product category 'frozen foods' be included in future research. A few respondents have noted the exclusion of this category from the questionnaire. From dis- cussion they appeared to have definite beliefs about this category. -69-
.7.0 BIBLIOGRAPHY
Assael, Henry and C. E. Wilson, Integrating Consumer and In-store Research to Evaluate Sales Results. Journal of'Marketing, Vol.XXXVI, No.2, April 1972.
Bass, M. Frank, Fishbein and Brand Preference: A Reply. Journal of Marketing Research, Vol.IX, November 1972.
, Edgar A. Pesemier and Donald R. Lehmann, An Experimental Study of Relationships Between Attitudes, Brand Preference and Choice. Behavioral Science, Vol.XXII, November 1972.
, and W. Wayne Talarzyk, An Attitude Model for the Study of Brand Preference. Journal of Marketing Research, Vol.IX, February 1972.
, and William L. Wilkie, A Comparative Analysis of Attitudinal Predictions of Brand Preferences. Journal of Marketing Research, Vol.X, August 1973.
Beckwith, E. Neil and Donald R. Lehmann, The Importance of Differential Weights in Multiple Attribute Models of Consumer Attitude. Journal of Marketing Research, Vol.X, May 1973.
Bettman, R. James, Noel Capon and Richard J. Lutz, Multiattribute Attitude Theory: A Test of Construct Validity. Journal of Consumer Research, Vol.1, March 1975.
Boyd, W. Harper and Ralph Westfall, Marketing Research, Text and Cases, 1972.
Brayshaw, G. H., E. M. Carpenter and R. J. Perkins, Consumer Preferences for Beef Steaks. University of Newcastle-Upon-Tyne, Report Department of Agricultural Marketing, Report No.2, 1967.
Carpenter, E. M., C. E. Hinks and R. J. Perkins, Price Premiums for Quality Beef Steaks: A Supermarket Experiment. University of Newcastle-Upon-Tyne, Department of Agricultural Marketing, Report No.11, 1968.
, D. Lesser and J. H. D. Prescott, Butchers' Meat and Customers' Opinions in Five Towns. University of Newcastle-Upon-Tyne, Department of Agricultural Marketing, Report No.15, 1972.
Churchill, A. Gilbert Jr., Linear Attitude Models; A Study of Predictive Ability. Journal of Marketing Research, Vol.IX, November 1972.
Chen, B. Joel, Martin Fishbein and 011i T. Ahtola, The Nature and Uses of Expectancy Value Models in Consumer Attitude Research. Journal of Marketing Research, Vol.IX, November 1972.
Danner, N. J., Beef Preferences and Purchasing Practices. Agricultural Exper- iment Station of the Alabama Polytechnic Institute, Circular 131, June 1959.
Eoonous, Mohammed, An Application of The Multiattribute Model to Consumer Selection of Supermarkets, Unpublished M.Sc. Thesis, University of Guelph, 1976. -70 -
BIBLIOGRAPHY contd...
Fishbein, Martin, An Investigation of the Relationships Between Beliefs About an Object and the Attitude Toward that Object. Human Relations, Vol.XVI, August 1963.
, A Consideration of Beliefs and Their Role in Attitude Measurement: Readings in Attitude Theory and Measurement, ed., Martin Fishbein, 1967.
, Attitudes and the Prediction of Behavior. Readings in Attitude Theory and Measurement, ed., Martin Fishbein, 1967.
Forbes, S. M. C., M. Naisery and R. Dramant, The Relationships Between Consumer Criteria for Choosing Beef and Beef Quality. Agriculture Canada, Research Station, Brandon, Manitoba.
Green, E. Paul and Donald S. Tull, Research for Marketing Decisions. Prentice Hall, Inc.
Guilford J. P. and Benjamin Frucher, Fundamental Statistics in Psychology and Education.
Hayman, H. Harry, Modern Factor Analysis. The University of Chicago Press, 1967.
Harrel, D. Gilbert and Peter D. Bennet, An Evaluation of• the Expectancy Value Model of Attitude Measurement for Physician Prescribing Behavior. Journal of Marketing Research, Vol.XI, August 1974.
Hudson, A. C. and M. J. Danner, Meat Buying and Preparation Practices of Professionally Employed Women. Agricultural Experiment Station, Auburn University, Circular 144, June 1963.
Juillerat, M. E., et al., Consumer Preference for Beef as Associated with • Selected Characteristics of the Meat. Virginia Polytechnic Institute and State University, Research Division. Bulletin 72, 1972.
Lancaster, Kelvin, Consumer Demand, A New Approach. Columbia University Press, New York and London, 1971.
Lehmann, R. Donald, Television Show Preference: Application of a Choice Model. Journal of Marketing Research, Vol.VIII, February 1971.
Malik, J. Henrik and Kenneth Mullen, A First Course in Probability and Statistic.
Massy, F. William, Discriminant Analysis of Audience Characteristis: Multi- variate Analysis in Marketing: Theory and Application, ed. David Aaker,1971.
McCarthy, E. Jerome, Basic Marketing; A Managerial Approach, Richard D.Irwin,Inc.
Montgomery, B. David, New Product Distribution: An Analysis of Supermarket Buyer Decisions. Journal of Marketing Research, VolXII, August 1975. 71
BIBLIOGRAPHY contd...
Morris, J. L., T. F. Funk and H. V. Courteney, Consumer Attitudes to Meat and Meat Products. University of Guelph, AE/74/4.
Morrison, G. Donald, On the Interpretation of Discriminant Analysis. Multi- variate Analysis in Marketing: Theory and Application, ed. David Aaker, 1971.
Mukerjee, Bishwa Nath, A Factor Analysis of Some Qualitative Attributes of Coffee: Multivariate Analysis in Marketing: Theory and Application, ed. David Aaker, 1971.
Nakanishi, Masao and Bettman, R. James, Attitude Models Revisited, Journal of Consumer Behavior, December 1974.
Nie, H. Norman, et al., Statistical Packages for the Social Sciences, 2nd.ed.
Richmond, B. Samuel, Statistical Analysis.
Rodgers, Cleta, et al., Comparison of Objective and Subjective Evaluations of Tenderness of Beef, University of Missouri, Agricultural Experiment Station, Research Bulletin 844, October 1963.
Rosenberg, J. Milton, Cognitive Structure and Attitudinal Affect, Journal of Abnormal and Social Psychology, Vol.LIII, November 1956.
Shanteau, James and C. Michael Troutman, Commentaries on Bettman, Capon and Sutz. Journal of Consumer Research, Vol.1, March 1975.
Sheth, N. Jagdish, Reply to Comments on the Nature and Uses of Expectancy Value Models in Consumer Attitude Research, Journal of Marketing Research, Vol.IX, November 1972.
, and Wayne Talarzyk, Perceived Instrumentality and Value Importance as Determinants of Attitudes, Journal of Marketing Research, Vol.IX, February 1972.
Steele, G. D. Robert and James H. Torrie, Principles and Procedures of Stat- istics with Special Reference to the Biological Sciences.
Steiner, D. Ivan and Martin Fishbein, eds., Current Studies in Social Psychology.
Stephenson, Ronald, Identifying Determinants of Retail Patronage, Journal of Marketing, Vol.XXXIII, July 1969.
Talarzyk, W. Wayne, An Empirical Study of an Attitude Model for the Prediction of an Individual Brand Preference for Consumer Products, Unpublished Doctoral Dissertation, Purdue University, 1969.
, A Reply to the Response to Bass, Talarzyk and Sheth, Journal of Marketing Research, Vol.IX, November 1973.
Wilkie, William L. and Edgar A. Pessemier, Issues in Marketing's Use of Multi- Attribute Attitude Models, Journal of Marketing Research, Vol.X, November 1973. - 72 -
8.0 APPENDICES
8.1 APPENDIX A - Qucstionnaire 11
CONFInKNTIAL: For Statistical Use Only Questionnaire o.
Interviewer note: Refer Respondents to Sheet 1 for their answers to qucotions 1 through4.
111 1) Vhich of the fancying supermarkets are you familiar with? "FaTiliat" r_ens the supcmarket(s) where you normally shop or have visited at sometime or another. PlmlLe refer to column 1 -of sheet 1. end check (/) on the lines besidu Ithose stores ;ou are familiar vitn.
2) In ter7.s of your preference, ho: do you rank the stores checked in colut:.n 1? P!aase refer to coluna 2 of sheet 1 and indicate your rank by nuzr,bers such that 1 reflects youc fivst choice, 2 reflects your second choice and so on. Place the number(s) beside thc. stoma(s) checked in .colut_n 1 on the lines provided.
3) On the average how often do you shop at the supermarket(s) checked in column 1? Please refet•to columns 3 through 9 and check (I) only one for each store on the lines pro,..ided.
4) If you shop at mote than one cupermarket regularly, what productn do you generally buy at each supermarket? rieale refer to columns 10 throuzh 14.
Note: 1) Include those stores you checked off in colurn 1 If they apply.
2) There tre fcur product classes:
a) )eat refers to all neat and meat products. b) Produce refer to all fruits and vegctebles. c) Dairy products refer to such items as milk, cheese, butter, egzs and so on. I d) Grocery refers to =ost proJuco found in a supamarket vith the exception of those listed in a, b and c, above.
3) You ray check rore tban cne category for each ctore. I
interviewer note: •Refer Respondents to Sheet 2 for their answers to question 5.
• $) Foy much Importance do you attach to each of the characteristics shown on this sheet? yote that the order of :7-rortance ronees fron number 1 extremely unirnortant to number 6 — extre=11v .in::ortant. klease put a check tark (X) on the nu=!)er that s4ows hov you rate each characteristic. See exi=ple.
Interviewer note: Refer Respondents to Sheet 3 for their answers to question 6.
6) Vhat best describes your feelings about each of these characteristics toward the store mentioned at the top of this sheet? For each statement, put a check mark (X) on the number that best describe/ your feelings for this store. Note that 'zilch totement ranys fren number 1 — extremely unfavournble to number 6 — extrem.,!lv favourable. The core uniavour.101v you: 1:ou: a cnara7A,:ri..tic for a r.artic.Lr 1:or., the nur,l,er ushouic Tr, t,:,trole.your .1:;out a charleterLstic tnulnrr,r tn..: runner you = -:.)uld cher%. At the end of each scaterear a line is provided. It you have dosolutelv no oplaion aoout a scazement then you should check No (.7.,inion.
?lease note that there are no rtr.ht or wron answers. Only your opinion counts. 11 ME NM MIS 1111. MI MI IIIIIII 111111 MB MI IIIIII 110111 OW OM MI IMO
Sheet 1
CONIIDEnTIALt For Statistical Use Only Questionnaire No.
Frequency of shoving. Check (I) cn17 Product n purchescd at one colusnn 3 thrcugh 9.for ench super=arket(o). Check (6 of rop, OTTICZ USE chop. tho3e products that are store where you Cards No.1-12 applicable. For example, If you 'erally buy only U .., O >4 moat et Dominion, then you () IV u.. V put the.erleck mark (I) on , J1 ..,4 ..4 meat 1,enide Dominion on the .)4 Cl 0 C 3 40 .11 0 line(a) provided below.
day Cl ) A
?l$4 r Cl 0 Cl 0 n o. checked
er No. every C) 40 ao IS, et U L. 05 0 14 4) • 0 • W Cl V V V AP .0 t-' 0 U V U ..-4 :* .1 0 .4 0 ttal C 49 t1 CI i4 Cl41
Once ClU
O ;t:;t:114 Ei Stcre S C:1 Store 8 0 Respondent 11 2 3 4 5 6 7 6 9 10 12 13 14
A an:: F (I— 13)
Dominion (Craoaa toad) _i_Liem,1 It
Dominion (Spccdvale ruzA) tb131 ii I
Ltrders (roo4 Land) • i_tio.41. 1 1 I hiracic rlod )Art 111051 I 1 i 1. Pcloaol. JjbJ I 1 1 Sunnyb rook _J—Lid 1_1 L.L.u.i...L!
Zchra _Hlod I I I (Edinbur0 Nara)
11,91 1111-1-1. Ultra ••••••••• IN..., 40 11.1111.0.111 • ...... ammo.. I (Victoria snd Crange)
Zebra JfiSi()1 I I ill!! (Wellington Plaza)
Zeiro ••• ...... • I IJIILL, (Willov Went Hall)
Zebra —Jill I J. Lit I 1 1 1 (Woodlavn and Victori‘j - 74 -
Sheet 2
QuoctimLeire Ho. ... CONFIDENTTKL: For Statietical Use Oaly
Extrcve.ly Moderetcly Slightly Slightly IfoderAtcly Extremely For Officc Use HEAT Pr.coitc..-rs unirport4nt unimporti.nt unir.2ortAat Sr:portant itnorcnt iv2or:.a.nt , Card Na.13 Vide selection of c,c2t products 0 0 0 0 0 0 L FrerhnesL of reat pro:lucts ca o o 0 El 0 Convenient package aize 0 El 0 0 0 0 La.: prices CD 0 0 0 0 0 Good value for money tpcnt C3 0 0 0 CD ID Coed quality mat products i= 0 0 CD 1:3 0 .11.111.1.1.111 PRODUCE Vide eelection of produce o G 0 I= 0 Cl Freshness of produce CD 0 0 0 0 0 Los, prices C:3 0 0 I= EI CI Good value for money spent 0 0 .0 0 0 D Good quality rroducc El 0 C3 ED CD 0
DAIRY PRODUCTS Vide tclection of dairy 0 0 0 CI 0 pr.>ducts 0 (15) Lost price?. 0 CI 0 0 ED 0 &?04 value. for money &pont CD 0 0 0 0 0 Good quality 0 0 0 C721 D Cl Freshness of dairy products 0 0 0 0 CD 0
OCERY PRODUCTS
packine rite 0 Conveaient ED 0 0 0 0 .1.0.1111 (20 Lole prices 0 0 0 0 0 p Good value for money spent 01 C3 0 1:3 ED 0 of brands ride selection 1= 0 0 C:3 E3 CI 0.111111.1..11 Good kuality P El 0 El ID El
STORE CEARACTERISTICS
Cleanliness (25) Ease of finding items Ease of uoving through store Fast checkout cervice Convenient shopping hours T411), stocked shelvea (ao) Attractiveness of displays Relpfulness of personnel
.110.1.11111
of personalized 000000000
Presence 000000000
000000000 000000000
000000000 000000000 000000000 000000000 service e.g. butcher's
Yearness of rtc7e 111111111..111•11
00 00 M M Ease of finding parkin 00
place (35) 0 0
of I.catioa 0
Cfmvenience 0 .111,111.1011. Fcsrcess of store to
Pharmacy, Zeck, 0 0 Cleaners.ttc. El Informative ads Many cou.pons
'Large nut:bet of items ODD ODD s7ecially priced DOD 00) - 75 -
”:7TM:TI,..?..: For Srztictical Use Only Sheet 3
III St ore: Questionnaire .• ...
Extranely YodIrttely Slii,htly Slightly Moecretz.ly ExtrenQly No TOR CiFIC 7AT rAODVCTS unfavourable unfavourablu unfavourable favourahle favourable favoural,le 17AT 7.7c,nu:7s CFINIC,N mom. • ...... ,1 v selcction Wide 'election Cirds No. at products C:3 El Cl Er of rest products --- (1 tale products ED ED Fresh products n --renient package size ci o ci ci 0 CT Convenient packaga size i prices Loy prices EDDOC:IEDM. 111..11.1. (2 .o....III value for m.ney a?ent ED El CJ CI El El Good value for r_....ney spent oor quality neat products CD CD 0 EJ.Q 0 Good quality.ueet products 7(Ct PRODUCE o v selection of produce C3 E3 ci El 0 ci Wide aelection of produce :ale products ODOM E:30 Fresh products iillprices D. ci 0 [7.3 ci ED Lad prices - (2 • velue for =oney spent ED D 0 C:3 0 I'D Good 'clue for money spect ocr quality produce CI I= 0 ci 0 El Good quclity produce PROMTTS DAIRY rnoT.:c7s av selectioa of Wide selection of dtiry A.., products C:3 ci o C:3 0 El products igh pr:cts ClCII D Cl 0 ED* Low prices o vslue for money spent ci E3 ci CD Good velue for Lz.iey spent o qi.%.1ity dairy proCuarr o ci Good quality dairy products .tale products ci o o leech producte •Z 7:Vf nODUC7S GLOCERY PvCOUCTS vcniect package use Cl D El Cl CI ci Convenient pzetAza size ltlx prices ILI ci 0 ci 0 EL Lou prices 'oor value for money spent 0 C3 C:1 ci C:1 ci Good value for money spent • stlectioc of breads C3 ET:i ID CD Vide selection of ,orand. o quality pa ci Et Good quality TO77. :RAAACTERTSTICS STCRE CR.1-7.A.C7TER Di Clean )i .cult to find items Easy to find iter...t. Difficult to cove Essy to move through DOD OM ODD :hrouth store ODD store - (4 31 Check-out service Feet check-out service 19 El In .veaient shopping %ours Convenient chopping hours Un4-r-stocked shelves Fully-stocked shelves DOD 1:10 ractive display Attractive display of • ems items Ushelpful personnel Eelpful personuel 0000E1 (4 personalized Presence of personalized it cc e.g. butcher's service e.g. butcher's "Eat of Near 0000000000 DODO DO Di111 DODO [MOQUE] Difficult to find Easy to find perking
ping place :1 place 1 I vcalent location Convenient location DO F . froa Phsraucy, Near to Pharmacy, Sanks Cleaner:, etc. Cleaners, etc. 'crmative ads Informative ads C.upott: ?lefty Coupons 1300E30 00000 00000 ODO Intl w.,mber of ices Large numNer of iteux O D
prired M1DDQ U O specially priced Shect 4 que:tionniire CC::YIN-7!:TIAL: For Sttictical Uoe - 76 - No. ...I
For Officc, C. 7) VnIch of the following ptl.ers do you normall) red? Card No.13 Guelph gercury I t 1 (4) Guelph Li:e
Guelph Shopper •••• None
8) If you checked any of the papers hated in question 7, do you nomally reed the advertisenznta?
Yes No
9) How do you usw.11y get to the super=arket(s)?
Cnr But Taxic (10) Valk Other
10) Sc" (check one)
Yale Tensle
11) Nov Lany rmbers are in your houtchold? Check aca.
One
Three Four 1/./I0/..•••••••••/ 11111.11.••••••••01P Over four.
12) Bow. rely are: See Card Uc.1
below 5 years? ------0110.1010.....11110 betveen 5 and 10 years? (20,1 • betveen 10 and 20 year;? between 20 and 60 years? -- above 60 years? d
• 13) what vork doe; the head of the huuseold do? Specify pleaLa .(28)
14) Does he/she work full tine or part time? Check one plette.
Tull ti= ------Part tict (33)
15) I: there another ae earner in the household? No Yes 4.111,••••••01.11.
16) If yes, into whet category doer: be/she fall? Check ore please.
Full tine . Part time Unemployed Student (35)
17) Roy long have you been living to Guelph? Check ono.
• Less than 1 year 411.1M111.11.111M.P.
Between 1 and 5 years ,----- SIMM11.1■11.1111..... 5 years Over 4.1.0MMONIP YINO
18) Kindly check the educationsl cstr.gory applicable to you. See Card No.2
Leas thur. Grade 9 Soaa high scbool (40) Complete high schnl Some college c.,!ucation OP•Illmadr.0111P Complete college education 4111118!Mar! Ommommearre 19) Kindly check the category/of your average annual (artily incone (rot, all tourers. Sau Card No..3
Delos, $2,000 .01.0MM164,411.r. Between $2,•110 and $10,000 -or Between $10,000 and $2,,,C00 411.1.11WWWM01.1,0 Between $20,000 and $10,000 O'er $30,000 11,111111....01.10 20) In what age group are ye-1? .saa No.4
Belay 20 year: 411.1•11111...110.1.10 Between 20 and ;5 years (50) Xetwetn 35 and 60 years .1111....11.M.11.0.1111 Above 60 years W•MINNW. 41.M.111MTIONP•OINP
Address of Ltsponeent: Block No.
Data of Intetviev: lemoimmarmirmiiMmeimegi iimmork. 118,,44 ef Inttrview.r: 8.2 APPENDIX B Population as Per Sample District MB UM MEI MIN MEI NM NMI NIS EMI MN 11111111 IIIIM IMO NM IMO NMI INN
I r ...... ___ ...... _...... _...... r...... ,___1 - it\ 5, 1; )1 '` ,ti, II 0,- ,---...... 7...... „ :: . "2...- ...... -...... —.-...„...... -.--.-„,--,- .. ,,, ...7..:-.-....--.:..e..„:, ,.. :...... -.! -...... j, 1 ____...... ;.„1 ,...... :-...... i • ...... ,••••••••"...... ii '...... ==••••'...... "..' ,...... r.•••••••••••••• '''.."‘.‘,... 0- 'i i .. . ; ...... :,, , ., :
t a II I i
1. i! I '')..k. Il i .1 \\ i •• 0...... `.....-...' 1. V .. •••• 1'r VC,..'''''n• ,c,"; I '..; - 11 . 1! . ii'''' -7-r --•' 1 7Z ..' :....,..,.../a.....,,O•....MOO, 11 ...:.\'''• ,•., :1 -.. • .II 1: „...1.:.....i, . . ..-.‘ ---. '..) ; '.$. 1 1! —i t1 .:(2 — II r i 1;) 11 tre.r; .. -It .: --, 11 'I g:' 4.J I 1 ,, -,i r-----• I cc•-•:- T.'% .1 1.:•.".,:,' - .ii. ,.,-.• si ..., / ...c...... - ..!! dr (7; . f.Iv ,I ______,,,,,,...... ,--,)-•,- 1.,, • .,i! !.• ...,7f- t_- j./ 1:."."--Nr, .... -,,:: .,,, ._.: -..:: .A..1! .1.!.; ,,„...... , f , 4 i V'",i I .___...... ,,,.-, ____.. /_,,______...... - ..—,,...rnIZP_...... ) ...... !.„. 1= " 1:7-:::....J ..:..___ _ .1, ..... J. • ... ._ 4 0 .." .41 -1, 1 L ._. f ,,, ,je: i f .,, 1,...... _ •i T •,...... 1 Weealoc----X1.,Vic-r---Aluir=..ti_..- 7..„ .::::,-,--,; - ,T - •• —•-- - .. e e •, ,• e.,,( )r - - i, r ...... :, _, ;1 1.' • s-) cs '7-1 ---,----'1\---,7r, il...) t;i7-----,,/.,,.----,,,, , F.,:i k . ‘.,,.--,.;,.; _Jr ?":.---- .-_,_ ,. . 0 1,1,, N. _ ..\\ 4,.,, • ---, , J .i ...) .--) • --.=- :, ,•1 . _ i iii„,, ,,i_. ,,,, ..,--.-. , .,., ., :------"-•\, ss..• '1 - --. • -- ,! 0‘ ,11, ,•:._...... -j I ,..., -2);' s ),....4,,..__ i ... it , ti i\, ,._-_:._..,,,\ "%,...---_,..) . ):..1.t:, ,..... ;t, :JA. ...t. I I : ). !, -)1,;,---)'-,..'.!jsC , ,i 'iri''''''-')' ni ':' rt.- 11 ''". :•-•!----..),.__,'''- 1:::'. .1 -I —',':':. -' 1 os 8 -;;',,,,,,.. •:',.7.,.!,4 .11'.. ;.-.,i ., I! ft I, ..--,; ../ .I -..,.. CC) i ( I, .: :I (.:' .1 „ —. ,.., 1` . . . (.. _. )1 ...-11. I:: 1 1, l'if :t ...1i..:!! (... 1 1 f: I: - • I. 11 ti!iitii% II.::-.;,1- l' -Wi,i'',,;,'...1 ,..i.1 C;(1...,11::,,.), ,;; IN li\-,------).; 1 1 liji '....e.*:f .1.- .--. lilir /AI, •-i '.Z: :' . .- I ),, •.; • ,i-s •• --= ------,•. - - „Pl..1;.1.0 ,', '1.7.1
,'-4‹....7„....11 :: : ':' ,t i:iih Or') -_ ii ' ii....it 'it."'./ 'IV is;ii -' ) !;11 i'.1;17-..-. 's\-11 -7-7 11 'II .,,' 4'7". _ Al ii..:„.11=--:-, ,,\ ii-- ,,...... , /.1},-, (f) 1 -\\ Li' i. :.:•: ,-_-_-....,--,'-;,Y; --, It:, !i,-..':V ...)( ,)C)I,- 7. 'e,. ..1;41,A,:"/,' 1.1 '`:::1 r ill',V .. •„.‘ -,..,. _,,,s;,•,,, r.:• vi / CI \ "i-1-: ii _I ,sk-,. '-'--•• • 1 iii - — —t, •.-. ,-...!,-,--. ""..,., ... .., -,\„;.,.,,, ‘,, ,- ,,, 1 ss-.-- „ ,---. - ill. :------, ._.---,:-,c ,,,A, ,..- j 111`—=1. .<;,7 -7 4„ et tre5:4-fi-- -)- r ...... ,:•__;-,vt ithl:.•"\\-.1.‘e{:.-sl. n 11_,4,1 t___. m N il IL _____ ,J; i; ;:!a fic IA)! !; 1! -:, ii,,,., j..,.,-If ....:,... 11 •,, 71 ''. V —1:13. (____,,,, ___J _ x. 't .1 =ii-..-:'- li'4'.:‘4'..flit ilidillii‘i:1 .1I ,..i :....., I . il - 11 los, 111. -.."-"`" i-r si .i" I . rf---1 1,i-;;',(;,:,,-,)*•Li ci ,:,!.:.,--;;`,.1 ,-....-:-./....:;!lii ,•;-,;.', co 1 I ji---il --.N."..!!,,:...,.'.'Jk-;-,.--- ,--ic-ii;M- _ 0j,, :2 1 li 11 0. ..) ,.- -ir ,- •;1 ,,!!p!..;lifit !pi1:y r-C.--"____ v: ,------=;i-,)- ii ,1 _. ll,_____11.2.•:•.:',.*:tii;,1 , u: Ili if ji ;1.-',';(. 0 l'.- ,/,1 /,. ,1 1,1[10 ::iJ ft IL, 1 :1-11111! I 7;0 1 1 J II' ir.,-.--_--.- '-- -- -1 II '.---- — ' 1'.- ,I --II ifh it '!„"iii i ,4 -I °I! :, l ---,,,,,,q:_-..-:i-V. --.11 -1,0! ','! lit:-J;i I 'II ii" ,-. 1 iLid[g I C _ ____ri--!ii.:=--__1- it rc-, • , _•. .ICP • • ildilf, lit ;! ,,,i.-‘ iil.:1411 \\If 11/ li )111 U c... -7"1-----ra"rn------1[--- II ,j i •,. 6'-1 c •.,:, --_--)..r- .-__,-. .-__—_-,.-1---_-_,11---7--iTT_.-ii i[ 1( 111';',//p...:(...-it ( [ .,--4 1 - If ,-. I . . _.:2 .., . ;h \\\!,,._-)r ,) -I ,, ‘,"-t c- ",:,--.--,- "=- V — ikb,"---C-1.,- ; ()ITO?: .0 ' 6; ,-. •. t _ ., ,----...,L :1 ,i1 ,-4- ..I ..2 - - -- .- If •I i r / i91 .., [ t-----i, CrIJI4 •7•1 ,, •; jr 4.) 1i ,. , '1 IF--C72!' ---'--L--;:-Li.*•/ \\j---ri''-'. cv r— — —1 . :'I ?ills',i WI.: V•71 X (1) :--,---...,—._ =,::; .-E= 1::::y,16H--_- .r.4 1,.1/1'47, , r 7 ,-..,:-.' 1%.- -Y-1) 1 'fl , r — 1—it- 1 if()..r.:'1! ill' ‘, v. . i ---.1 . \ riL- i --., - I 0: ..., , .,,,...... 1 i ..---.....-J ! -!.... i---, 1 r\ ,1 1 ,i, : • ..‹..., 7. g t )'::•i'i, .11. 104rir W 2-. ‘vc if
,- • ...... , 4...... at•ra,...rta :,...... \--mmew:amonormt.-‘111re• 1 riiiimarilMate.m.a ine...... eer, -...... 1-j"..-=---"-----"---1" —li li ill \ 1 Cr) ill) 11 vi 11 1 i t • 111111 ME 11111111 OM NM NMI PUS MPS MI NMI NMI 1111111 EMI IMIN NM MS MIMI MOS MINI L I I I 1 I I I I I I I I I I I 1 I I I