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STOCKOUTS IN FASHION MERCHANDISING: CUSTOMER

REACTIONS AND CONSEQUENCES FOR THE RETAILER

By

Gerrit Pieter van Nederpelt

A DISSERTATION

Submitted to
Michigan State University
in partial fulfillment of the requirements
for the degree of

DOCTOR OF PHILOSOPHY

Department of Marketing and Transportation
Administration

1984

ABSTRACT

STOCKOUTS IN FASHION MERCHANDISING: CUSTOMER
REACTIONS AND CONSEQUENCES FOR THE RETAILER

BY

Gerrit Pieter van Nederpelt

One critical decision retailers face in their role in the
distribution channel involves the dimensions of the assortment to be
carried. It is impossible to always have a "perfect" assortment and
retailers need to strike a proper balance between overstock and under-
stock. Traditionally, a stockout has been considered a negative
business experience, and the more stockouts were feared, the more
safety stock was carried. This research shows that the expensive
method of protection, carrying safety stock, is but one alternative
to deal with stockouts. Fashion apparel merchandising was primarily
chosen due to the social risks to the consumer of this merchandise.
Few consumers have distinct choice criteria in their purchasing
behavior, which contributes to the importance of store image in this
field, and affects the applicability of previous stockout research.

The first objective determined customer responses to stockouts,
and the second, factors influencing such responses. The third
objective investigated the effect of stockouts on store image and, the
fourth determined the influence of store perceptions prior to a stock-
out experience.

The inadequacy of the traditional definition of a stockout became
evident, and a broader definition was suggested. Further, the robust-
ness of fashion store images, was substantiated. Using both scenarios

and actual experiences, the attribute concerning the store's sales

Gerrit Pieter van Nederpelt

force was shown to be of great importance in the establishment and
maintenance of image. The price level also proves to be a sensitive
element.

Customers' expectations regarding the store's merchandise assort—
ment were influential in determining their stockout responses and the
accompanying annoyment. Also, the research determined the benefits of
creating an atmosphere in the store to encourage customers to express
themselves to store personnel about assortment inadequacies. Generally,
demographics and other situational variables showed little influence
on stockout responses as opposed to frequency of stockout occurrences,
and the intention behind the store visit.

The research contributes an improved perspective on merchandise
assortment planning and the role of personnel involved in this
activity. Also affected is the important role a retailer plays, or

can play, in the distribution channel.

Dedicated to my parents,

Henny and Jan van Nederpelt

ii

ACKNOWLEDGMENTS

The time period involved in dissertation work, by its length,
causes a number of people to have an influence on the completion of
this requirement for the doctoral degree. Due to some unusual circum-
stances in the case of this study, the time period was especially long
and, consequently, many people have played a role during the process.
To all these people I express my sincere gratitude.

One person who very definitely deserves a lot of credit is
Dr. M. Bixby Cooper, chairman of the dissertation committee. Throughout
the whole process, Dr. Cooper stuck with the effort, even though I am
sure he had his doubts at various times. However, his patience, advice,
and general support were very instrumental in the ultimate completion
of the project.

The other committee members to be mentioned in this respect are
Dr. Donald A. Taylor and Dr. Forrest S. Carter. Dr. Carter made many
contributions from a quantitative method perspective and it was very
educational, and a pleasure, to work with him. I am very grateful to
Dr. Taylor who played an important role in the total period of time
I have spent at Michigan State University. I was very fortunate to
come to the University when Dr. Taylor was chairman of the Department
of Marketing.

Dr. Taylor's role is also shared by the late Dr. Hendrik

Zwarensteyn, Associate Dean Dr. James F. Rainey, Dr. Donald J. Bowersox,

iii

and Dr. Leo G. Erickson. All have played important parts in my
adjustment to a different cultural and academic environment, and I
am grateful for the influence they have had on my life.

Dr. Jeffrey R. Towle needs to be mentioned as one of the main
sounding boards for the original development of the topic of this
research. Without Dr. Towle, much in my teaching and research
background would not have been possible.

Along the way many a fellow student, secretary, and friend had
important effects on the successful completion of the doctoral program.
Dr. R. Eric Reidenbach, Ms. Lori Shirey, and Ms. Margaret Keane serve
as examples, respectively, even though many others also qualify.

They all helped create a very educational atmosphere during my
doctoral program.

Since joining the faculty at Oklahoma State University, I have
greatly benefitted from the support of various people, particularly,
Dr. Ruth H. Krieger and Dr. Raymond P. Fisk. The former, through her
own research efforts, provided a lot of inspiration. The conditions
under which Ruth worked especially inspired me to continue my own
research. Ray Fisk, through his patience and expertise, provided
invaluable psychological support, and I sincerely appreciate having
served on the same faculty with him.

Personally, the greatest amount of credit goes to my wife, Karen,
who not only had to endure many adverse times with me, but also made
important sacrifices in helping me complete this dissertation. My
parents, back in the Netherlands, were many times oblivious to the
events occurring during the doctoral program. However, they will never

fully realize how much their support and the upbringing they have given

iv

me, has meant to me, and will continue to mean, in my endeavors in
the U.S. Therefore, this dissertation is dedicated to them.
To all those mentioned, and those not mentioned, who played their

role: Thank you very much!

Chapter

I.

II.

III.

TABLE OF CONTENTS

INTRODUCTION . . . . . . . . . . .

OUt-Of-StOCk o o o o o o o o o 0
Fashion Merchandising. . . . . .

Stockout Measurement in Fashion Merchandising.

Objectives and Contributions . .
Description of Research Setting.
Overvj-ew O I O O O O O O O O I 0

REVIEW OF THE LITERATURE . . . .

Introduction . . . . . . . . . .
Definition of a Stockout . . . .
Customer Reactions to Stockouts.
Introduction. . . . . . . .
Conceptual Developments . .
Conceptual Modeling Efforts

Empirical Measurement Efforts
Store Image and Product Unavailability

Introduction. . . . . . . .
Definitions of Store Image.

Retail Store Image Determinants
Store Image Measurement Methods
Retail Store Image vs. Customer

Dissatisfaction . . . . .
Fashion Merchandising. . . . . .
Introduction. . . . . . . .
Definitions . . . . . . . .

Channels of Distribution in Fashion Merchandising
Merchandise Assortment Planning .

Conclusion . . . . . . . . . . .

MTHODOLOGY . O O O O O O O O O O 0

Introduction . . . . . . . . . .
Research Purpose . . . . . . . .
Hypotheses . . . . . . . . . . .
Measurement. . . . . . . . . . .
Methods of Analysis. . . . . . .
Questionnaire Development. . . .

vi

Page

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34
35

38
42
42
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52

54

54
58
59
64
69
7O

Chapter
IV. DATA ANALYSIS AND RESULTS. . .
Introduction . . . . . . . .

Sample Characteristics . . .
Scenario Reliability . . . .

Measurement: Dependent Variables.

Hypothesis Testing . . . . .
Hypothesis One. . . . .
Hypothesis Two. . . . .
Hypothesis Three. . . .
Hypothesis Four . . . .
Hypothesis Five . . . .
Hypothesis Six. . . . .
Hypothesis Seven. . . .

Other Important Findings . .

V. SUMMARY AND CONCLUSIONS. . . .

Introduction . . . . . . .
Research Summary . . . . . .
Research Design. . . . . . .
Experimental Design . .
Conclusions. . . . . . . . .
Hypothesis One. . . . .
Hypothesis Two. . . . .
Hypothesis Three. . . .
Hypothesis Four . . . .
Hypothesis Five . . . .
Hypothesis Six. . . . .
Hypothesis Seven. . . .
Implications . . . . . . . .
Stockout Definition . .
Buyer Evaluation. . . .
Sales Personnel . . . .

Implications for Store Image. . .
Channel Role of the Retailer. . .

Limitations. . . . . . . . .

Suggestions for Future Research. . . .

Appendix
A. DEMOGRAPHICS OF STREETS' STORE
B. COVER LETTER . . . . . . . . .
C. SCENARIOS A AND B. . . . . . .
D. COPY OF THE QUESTIONNAIRE. . .
E. DEMOGRAPHICS OF THE SAMPLE . .

B IBLIOGRAPIIY O O O O O O O O O I O O 0

vii

LOCATIONS

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Table

10.

ll.

12.

13.

14.

15.

LIST OF TABLES

Page

A. Comparison of Demographic Characteristics by
Scenario Using ANOVA . . . . . . . . . . . . . . . . . . 78

B. Crosstabulation of Education with Scenario Type. . . . . 8O
Reliability Coefficients for Individual Scenarios. . . . . . 81

Image Measurement Scale Reliability Coefficients and the
Effect of the Price Component. . . . . . . . . . . . . . . . 82

Factor Analysis of Image Measurement Scale Components
(for the Actual Store) . . . . . . . . . . . . . . . . . . . 84

Split-Half Reliability Coefficients. . . . . . . . . . . . . 85

Likelihood of Alternative Responses to the Hypothetical
Stockout Experience. . . . . . . . . . . . . . . . . . . . . 86

Alternative Reactions to an Actual Stockout. . . . . . . . . 88

Crosstabulation of Stockout Responses with Purchase
Intentions O O O O O O O O O O O O O O O O O O O O O O O O O 89

Crosstabulation Analyses Between Stockout Reactions and
Demographic Characteristics. . . . . . . . . . . . . . . . . 91

Crosstabulation Analysis of Stockout Responses with
Selected Situational Variables . . . . . . . . . . . . . . . 94

Crosstabulation Analysis of Purchase Intention and
Level Of Annoyment O O O O O O O O O O I O O O O O O O 0 O O 96

Summary Table of Crosstabulations of Stockout Reactions
with Various Demographic and Situational Variables . . . . . 97

Oneway Analysis of Variance: Type of Shopping
Experience and Likelihood of Return Visit. . . . . . . . . . 98

Opinion Change Due to a Stockout Experience. . . . . . . . . 98

Crosstabulation Analysis of Opinion Change with
Selected Situational Variables . . . . . . . . . . . . . . . 99

viii

Table

16.

17.

18.

19.

20.

21.

22.

23.

24.

25.

26.

27.

28.

Level of Expectations and Scenario Type. . . . . . . . .
Crosstabulation Analysis of Levels of Assortment
Expectation with Likelihood of Patronage and Leaving

Store Without PUIChase O C O O O O C O C O O C O O O O O

Crosstabulation Analysis of Level of Expectations with
Stockout Responses and Level of Annoyment. . . . . . . .

Three-Way Crosstabulation of Level of Expectations and
Purchase Intentions by Level of Annoyment. . . . . . . .

Relationship Between Scenario Type and Stockout Response

Relationship Between Scenarios A and B, Type of
Experience, and Store Perceptions. . . . . . . . . . . .

Paired T-tests Between the Specific Type of Store and
Likelihood of Patronage. . . . . . . . . . . . . . . . .

Paired T-tests Between Likelihood of Returning Under
Different Conditions in the Store. . . . . . . . . . . .

Test of Proportions Involving "Exit" versus "Voice"
BehaVior . C C O O C C C C C 0 C O O C O C O C O I O O 0

Factors Influential in Determining Stockout Reactions
as Reported on by Respondents. . . . . . . . . . . . . .

Factors Considered Important for an Annoyed Shopper to
Return 0 O O O O O O O I O O O O O O O C O C O O O O O 0

Factor Analysis of Important Reasons to Return to a
Store After a Stockout Experience There. . . . . . . . .

Respondent Perceived Alternative Retailer Actions. . . .

ix

Page

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108

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114

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118

Figure

LIST OF FIGURES

Walter's Stockout Model . . . . . . . . . . . . . . .

Supplier Effects of Customer Reactions to Stockouts . .
Example of a Want Slip. . . . . . . . . . . . . . . . .
Image Attributes Popular in the Literature. . . . ... .
Distribution Channels in Fashion Merchandising. . . . .

ResearCh MOdel O O O O O O O 0 O O O I O O O O O O O I 0

Customer Related Variables as They are Expected to Affect

the Seriousness of a Stockout Reaction to the Retailer.
Scenarios Used in the Image Measurement Process . . . .
Alternative Reactions to the Stockout in the Scenarios.

Perceptual Map of the Images of the Scenario Stores . .

Page
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24
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56

61
68
72

112

CHAPTER I

INTRODUCTION

In most instances, an out-of—stock situation is a negative
experience for a business. Except for a few situations where occasional
unavailability may increase the shopper's perception of demand for the
product, there is a general agreement that businesses should make at
least a reasonable effort to avoid stockouts (see for example:

Progressive Grocer,1968; Ballou,1973; Bowersox,1974; Coyle and Bardi,

 

1980; Johnson and Wood.1982). Many studies have measured the impact
of these occurrences and determined how a business should attempt to
avoid their negative consequences. Discussions have centered around
general frameworks modeling alternative customer responses, or have
involved investigations of monetary cost implications in very specific

settings.

Out-of—Stock

Traditionally, an out-of—stock situation is where a seller does
not have stock at the time a customer wants it. As a matter of fact,
much of the literature implies this definition. This view may be too
narrow.

A retailer's efforts in marketing the product assortment affect
customer expectations regarding the items included in that assortment.
Subsequent decisions to delete a product from the store's offering can
'result in unfulfilled customer requests. Customers may also have prior
expectations, through previous experiences with other stores, word-of-

'mouth, etc., and assume the assortment has a greater variety than that

actually carried. Thus, both customer expectations and retail manage-
ment's marketing efforts can cause an out-of-stock situation to exist
with potentially negative consequences for the retailer.

With respect to these consequences, stockouts have been viewed
as having three general alternative results (Bowersox,1978):

l. The customer postpones the purchase;

2. the customer purchases the product elsewhere;

3. the customer purchases the product elsewhere and ceases to

patronize the original outlet.

Clearly, the impact on the seller increases in severity in the same
order. To measure that degree of severity, studies have centered around
two types of costs, actual costs and loss of store image. On the one
hand, actual costs have been identified and discussed in various
settings (e.g., Schary and Becker,1978; Walter,1975; Heskett et al.,1973).
On the other hand, particularly in the retailing literature, image
studies have been undertaken with merchandise availability as one of the
determinants of store image (e.g., Lesser,1981; Lindquist,1975).

Inadequate inventory levels can be the result of many factors.
Marketers can rarely predict demand accurately. Also, they may
encounter obstacles such as timely replenishment of inventory, clerical
errors, etc. Those factors are not always under the retailer's control.
Regardless of cause, the only method to prevent stockouts is to carry
extra inventory, thus the greater the uncertainty, the greater the
amount of safety stock carried. Simulation models have been developed
to determine optimum levels for inventory, and expanding technology is
giving us the tools to implement answers to this sort of problem.

The amount of effort spent on attempts to balance understocking

annd overstocking indicates a recognition of the seriousness of the

problems of inventory control. According to Ammer (1974), these
problems have led to a style of decision making that operates without
sufficient information on implications of stockouts to justify such
decisions.

. . . in generalmanagement tends to overprotect themselves

against stockouts. All too often they are unwilling to

accept the idea that if they want tight inventory control

they must be willing to risk an occasional stockout. It

takes a courageous manager to risk running out of stock

when he knows it pays to take risks. When the stockout

does occur, his boss is all too likely to think only of

immediate loss and forget the enormous gains that come

from low safety stocks and close control (p. 347).
However, the question of how much a stockout will cost has never been
answered satisfactorily, although the literature shows evidence of many
measurement attempts (e.g., Coyle and Bardi, 1982; Heskett et al., 1973;
Burgin, 1970; Progressive Grocer, 1968).

Decision making has come under more pressure due to the recessionary
periods witnessed in recent years. This pressure also has resulted in

more emphasis on the development of techniques to improve the management

of inventory levels.

Fashion Merchandising

Merchandise assortment planning for a retailer is a constant
struggle to decide which items to carry in stock on the one hand, and
how many of the selected items to include on the other hand. If we
refer to merchandise assortment as the total product offering of a store,
we can further identify the term "assortment" by its dimensions.
According to Kotler (1980), the number of product lines carried deter-
xnines the width; in other words, the greater the variety of different

'products offered, the wider the assortment. The depth is determined

by the number of different options available within each product line.
Options here include alternatives to (package) sizes, brands, price
ranges, etc., as well as the number available per stockkeeping unit.
In fact, the number of items available per stockkeeping unit, labeled
"support" by Mason and Mayer (1978), is the only element of depth
considered in the retailing literature (see also for example, Davidson,
Doody and Sweeney, 1975). The wider an assortment, the greater the
chance that a broad range of customers can be served, yet the smaller
the chance that the demand for each individual item can be adequately
forecast. Thus, wider assortments lead to a greater chance that a
stockout situation will occur.

Merchandise assortment planning involves many such trade-offs
(Lusch, 1982). For example, the wider the assortment, the "shallower"
it has to be as storage and shelf space become important issues.

Also, the deeper the assortment, the more difficult (i.e., expensive)
it becomes from an inventory control perspective. In any case, width
and depth of an assortment are important elements in determining the
image of a retail outlet (for example, see Martineau, 1958; Berry,
1968; May, 1973; Hirschman, 1978).

A third dimension of the assortment, consistency, is generally
overlooked. Consistency refers to how closely the different product
lines relate to one another within the assortment (Kotler, 1980).

Like width and depth, this dimension also has very important conse-
quences for the customer's image of a store. Retailer decisions
regarding width and depth affect the consistency of the total assortment.
IFor'example, additions to width and/or depth, especially if advertised

(Jr passed along by word-of-mouth, can invoke expectations of an even

more expanded assortment. As a result, a consumer may expend the effort
to visit the store, only to learn a particular item is unavailable.

When retailers delete products from the assortment, conveniences such

as the telephone book's "yellow pages" and other methods help reduce

the customer's frustration with the product's unavailability because

the amount of effort expended is not as high as a store visit. However,
it is still a negative shopping experience and the frequency of it
occurring can intensify the negative consequences for the retailer just
as traditionally defined stockouts can.

Many prominent authors recognize the great amount of risk involved
in merchandise assortment planning (Kotler, 1980; Bowersox, 1978).
Rachman (1975), particularly, identifies an "internal risk" for retailers
and a "consumer risk". An internal risk, as it relates to a policy of
carrying more inventory than is needed for the purpose of protection
against stockouts, involves the risk of markdowns. Not only are
markdowns a heavy price to pay for overstocking, but there are also
factors such as ordering and carrying costs to consider.

According to Rachman (1975), a consumer risk is incurred when a
retailer does not carry enough inventory and thereby risks losing a
sale.

In theory, the retailer may not only be losing a sale but

in the long run he may lose most of his customers simply

because the buying public may tire of not finding what they

want . . . the consumer may balance (1) the probability of

finding a set of items in a store versus (2) the cost

incurred in making the purchase. Obviously, the lower the

probability of finding the wanted item, the less likely the

consumer will be to shop in the store. In essence, this

theory suggests that the retailer who is not in stock most

of the time is faced with a possibility of losing not only
a sale but also a customer (p. 284).

The major focus of this research is on "consumer risk", a risk of
particular importance in fashion merchandising, where width, depth
and consistency of assortments need to be planned far in advance of
the actual selling season, increasing the uncertainty in these

activities.

Stockout Measurement in Fashion Merchandising

Much has been published in terms of stockout costs although little
has been applied to the fashion industry, particularly in the area of
complementary products. For example, when a customer selects a blouse
and looks for a skirt to go with it, will the fact that the right size
is not in stock cause her to abandon the intention of purchasing the
blouse? If she decides to purchase the blouse, will she wait for the
skirt in her size or will she go elsewhere to find a comparable
combination? The effects on the image of the store can readily be
assumed to be present, but are extremely difficult to measure.

Fashion merchandising is a difficult field with respect to the
measurement of stockouts for other reasons as well. For example,
routine reordering is not as large a part of retail fashion buying as
it would be for another type of retailer (Greenwood and Murphy, 1978).
Also, the pressure on inventory decision making is even greater
because there is very little prior knowledge of consumer demand beyond
demand for apparel in general. This pressure is intensified by there
being little opportunity to correct errors in assortment planning
through backordering (Greenwood and Murphy, 1978).

Studies involving stockouts have been very situation and product

specific due to the existence of factors unique to that situation or

product. Costs and image implications have been investigated in such
settings as metal wholesaling firms dealing with manufacturers, grocery

product retailing, etc. (Chang and Niland,l967; Progressive Grocer,1969).

 

In these research efforts, the researchers have a high degree of
control over the setting. In the fashion merchandising industry,
however, such control does not exist to the same extent. Relatively
few customers will ask store personnel about the availability of a
product, even if they have a clear idea of what they want. Also, many
customers shop for social reasons rather than for accomplishing a
specific purpose. Fashion shoppers, furthermore, seem to have a
tendency to continue shopping despite having found something to their
liking (Troxell and Stone,1981). These factors confound the measure—
ment of customer reactions, which may explain why research on the
consequences of stockouts for fashion retailers is non-existent.
Although studies relating to fashion store image have shown that
merchandise assortment problems such as unavailability are influential,
there is a lack of research investigating the direct effects of

stockouts on store image.

Objectives and Contributions

Even though many studies have focused on the role of stockouts
in inventory management, little or nothing has been done in the
area of retail fashion merchandising. It is the purpose of this
research to investigate the following four issues:

1. how customers respond to product unavailability in a fashion
retail store;

2. the factors that affect customer responses to product
unavailability in a fashion retail store;

3. the influence of product unavailability on customer image
of fashion retail stores;

4. the influence of store image on customer responses to
stockouts in fashion retail stores.

This research provides insights into an area of retailing heretofore
not included in stockout research. Even though cross-sectional, the
research also provides further insight into the phenomenon of stockouts
and the implications for retail store management. Up to now, it has
appeared to be more beneficial for a retail buyer personally to risk
understocking rather than overstocking, as costs of the latter are
measured more readily through the amount of markdowns required to
eliminate excess inventory. Greater knowledge of stockout effects on
the retailer also provides improvements in the evaluation of a buyer's
performance. Furthermore, such insight affects the evaluation of the
salesperson who can be trained to persuade the customer to substitute
another item for the out-of-stock item. Of course, knowing more about
the effects of stockouts affects the merchandise plan that the retailer

follows.

Description of Research Setting

This research involves a sample of customers of a chain of women's
apparel outlets that cater to higher income shoppers. This setting is
considered more polarized with regard to shopping behavior than in
environments such as a department store. In department stores a
“variety of products with a variety of uses attract a variety of shoppers
which merely confounds the research without aiding it (e.g., May,1971;
Rich and Portis,l964). The setting in this reserach offers a greater

specificity in shopping behavior. Yet, it is still difficult to measure

exact monetary costs of product unavailability, due to the type of
shopping behavior encountered (Troxell and Stone,1981; Greenwood and
Murphy,1978). Therefore, the impact of stockouts on store image is
of great consequence to retail store management.

Limitations of this setting relate to the ability to generalize
the results beyond fashion merchandising. This is particularly affected
by the constraints on image measurement with regard to the product
category and the type of retail establishment involved (Engel, Kollat
and Blackwell,1974). Another limiting factor stems from the cross-
sectional nature of the research. Time related elements influence

the measurement process as well (e.g., Andreasen,1978).

Overview

Following the introductory chapter, Chapter II presents a literature
review exploring the various research efforts relating to stockouts and
fashion merchandising. Chapter III presents the methodology. The
analysis of the data is described in Chapter IV as it relates to the
relevant stockout issues. Chapter V contains a description of the
implications for retail management, as well as a summary and

conclusions.

CHAPTER II
REVIEW OF THE LITERATURE
Introduction

Questions surrounding the implications of stockouts are very
difficult to answer in terms of actual cost, customer reactions, etc.
It is much easier to focus on overstocking and the cost involved in
that activity (Ammer, 1974). However, in proper merchandise assortment
planning, finding the correct balance between understocking and over—
stocking is a key ingredient in achieving profitability (e.g., Nelleman,
1975). 'Making the proper inventory decisions has also been identified
as a very risky activity (e.g., Bowersox, 1978; Rachman, 1975).

To put the issue of merchandise planning in a better perspective
it is appropriate to look at the issue of risk associated with carrying
inventory, both from a retailer and a customer point of view.

According to Bowersox (1978), risk can be looked at in terms of width
and depth, as well as along time dimensions. Compared to manufacturers,
retailers carry large numbers of products. As a result, retailers
assume a degree of risk that can be considered wide, but not very deep
since, by comparison, they do not have much inventory per stockkeeping
unit. Manufacturers' risks are defined as narrow, but very deep. In
this respect, it is understandable that a proper balance between width
and depth is not only in the financial interests of the individual
organization, but also a key ingredient in the success of the whole
channel of distribution.

Rachman (1975) identified in this context as internal risk for

retailers: carrying more inventory than needed means risking markdowns.

10

11

Markdowns essentially imply that a retailer cannot move the merchandise
and that a retailer could pay a high price for overstocking. Further-~
more, marking down does not guarantee a moving of the merchandise. Of
course, as Rachman adds, there are other costs associated with this
internal risk, carrying costs and ordering costs are the most obvious.
Particularly, he noted the following concerning inventory costs and
markdowns:

Inventory costs that can be documented approximate 6 percent

of sales in a large department store. However, markdowns

and the cost of losing sales add to this estimate (p. 286).
It is interesting, to say the least, that he leaves the "cost of losing
sales" virtually untouched.

Risks in inventory are intensified when economic pressures exist.

The Wall Street Journal in August 1980 noted the importance of inventory

 

control in inflationary periods.

Inventory control gains in importance when interest rates

and inflation run high. That's because inflation raises

the value of goods in inventory and high interest rates

raise the cost of financing, cutting into current profits.

Despite all the attention inventory has got in the past

five years, however, keeping just the right amount of goods

on hand has proved neither simple nor painless (p. 15).

To provide an input in this risky decision area, it is necessary
to look at the possible impacts of stockouts. In this chapter the
following outlines will be used. First, a discussion on the definition
of stockouts is presented. A review of studies related to customer
reactions to stockouts follows including both conceptual and empirical
writings. Also, situational variables identified as related to customer

stockout perceptions are discussed. Third, the relationship between

store image and product availability as previously researched is explored.

12

Lastly, a review of the relevant fashion merchandising literature is

presented.

Definition of a Stockout

Throughout the literature, the term stockouts generally implies an
evil that should be avoided if at all possible and, it not always
possible, limited to a minimal chance of occurring (e.g., Bowersox,

1978; Heskett,1973; Ballou,1973). In all these writings, there is an
implicit assumption of a standardized definition of what a stockout is:

a situation in which a retailer does not have an item on the shelf when a
customer demands it. This definition does not seem complete. For
example, a customer asks a retailer for an item that the retailer does
not carry as part of the assortment, some writings would not consider

this a stockout (e.g., Progressive Grocer,1968). Yet, the effect on

 

the consumer is still that she walks out without her wants satisfied,
which has possible implications for the customer's perception of the
store. For the purposes of this paper, it is necessary to take a closer
look at the definition of a stockout.

Some of the more frequently quoted sources in the literature have

an explicit definition. A study done for Progressive Grocer (1968)

 

defined the failure to serve the customer:

A product of any brand, size, shape, flavor, color or type
is out-of—stock if the item is usually carried in the store,
but is not found on the shelf at a give time. This includes
items which are missing from the shelf as the result of
careless or faulty ordering practices—-so—called 'lost
items' (p. 8-22).

This is actually the most complete definition found as it also addressed

theaproblem of not being on the shelf, yet on the premises. Furthermore,

13

the definition covers a situation which arises when a customer request
remains unfilled as a result of a conscious retailer decision to delete
the item from the assortment.

If the item is in the backroom, but not on the shelf it is

still considered out; if it was ordered by the store, but

not sent out by the warehouse for one reason or another, it

is still recorded as out, although a separate record may be

made that the out is not the fault of the store. If an item

is authorized by headquarters, but is deliberately not

carried by the store, because it is deemed a poor mover or

unnecessary for variety, it is not considered as out-of-stock
(p. 8-22) 0

For this particular paper the issue is not so much the specific reason
why the product is not on the shelf as the consumer does not know why
the item is unavailable, is not interested in that reason or feels

she will be given an excuse anyway, such as: "The truck has not come

in yet" (Progressive Grocer,1968, p. 8-31). Instead, the point needs

 

to be made that when a customer asks for an item a retailer does not
carry, she must somehow have expected the product to be there. As a
result, she could have the same feelings of disappointment experienced
by a customer who finds a regularly stocked item unavailable.

Mason and Mayer (1978), even though explicit, proposed a definition
of a stockout that seems rather narrow.

A situation in which a retail store does not have enough items

of a particular kind to meet customer demand; thus, the

product is not available when consumers come into the store

for the purpose of purchasing the item (p. 709).
They not only refer to products the store is supposed to carry, but
also limit the definition to customers entering the store for the
eXpress purpose of buying the out-of—stock item.

Johnson and Wood (1982, p. 265) identified a stockout as occurring

when "the supply of an item is exhausted and a customer wants to buy

14

the out of stock item." Ballou (1973, p. 282) stated that "out-of—stock
costs are incurred when a customer places an order and the order cannot
be filled from the inventory to which it is normally assigned." Even
Bowersox (1978) leaves one to assume that stockouts refer only to
situations where you do not have on hand what the customer wants. Other
notables following this patterns are Heskett et a1. (1973) and Stock
(1982).

The question still remains, however, of what to call a situation
in which a customer asks for an item that a retailer does not carry
for strategic reasons. Therefore, for purposes of this paper, a
stockout is defined as a situation which occurs when a customer is
unable to buy a wanted item due to the unavailability thereof in that

particular outlet.

Customer Reactions to Stockouts

Introduction

 

Bowersox (1978) noted that without the proper assortment of
inventories, serious marketing problems can develop in revenue genera-
tion and customer relations. Wingate and Friedlander (1978, p. 119)
stated: "The ultimate test of a stock is its capacity to satisfy the
demand of the one customer standing at the counter."

Throughout the literature it is recognized that stockouts are
expensive. Johnson and Wood (1982, p. 265) stated "the determination
of stockout costs is difficult and inexact, but nevertheless real."
Coyle and Bardi (1980) summarized the problem of calculating stockout

COStS.

15

While the determination of the cost of carrying safety stock
inventory may be relatively easy, determining the loss (cost)
of not having an item for sale may be much more formidable.
If a company is dealing with raw materials or supplies for a
production line, a stockout would mean shutting down
operations in whole or in part. The opportunity loss from
such a shutdown would have to be calculated. Most companies
would be able to determine the hourly or daily production
rates, which could be multiplied by the loss of_profit on
the number of units not produced . . . The calculation of
stockout costs for finished goods where a customer will be
affected is usually a more formidable task than for raw
material stockout cost (p. 91).

The following discussion on customer reactions to stockouts is divided
into a review of conceptual developments and an analysis of empirical

efforts to measure such reactions.

Conceptual Developments

 

Coyle and Bardi (1980) contended that three possible events can
occur as a result of a stockout: a backorder, a lost sale or a lost
customer. They went on to say that "from the viewpoint of most
companies, these three possible outcomes of a stockout are stated
from best to worst in terms of desirability" (p. 91).

Heskett, Glaskowski and Ivie (1973) discussed these costs in terms
of "hard" versus "soft" costs with "hard" costs being, for example,
for duplicate order processing, extra communication and LTL transporta—
tion costs. They found that the "soft" costs are almost never
considered and nearly impossible to measure; they define them as costs
of lost selling time and foregone contribution on lost sales.

Heskett et al. (1973, p. 349) recognized that "in many situations,
the 'soft' costs exceed the 'hard' ones, particularly for products
for which substitutes are readily available to the buyer." Morrell

(1967) in this respect stated that

16

. . . a factor which may have to be taken into account when
considering stockouts of finished products is customer
goodwill. If, because of inadequate stocks, a customer's
order must be refused or unduly delayed, this may lead to
the loss of some or all of any future business with that
customer. The more competitive the market, the more
important this factor becomes, although even when there is
little competition there may be a feeling of moral obligation
to meet any demand. It should be borne in mind, however,
that in a competitive market customers may be gained from,
as well as lost to, competitors (p. 7).

In trying to get a better understanding of the cost of stockouts
Heskett et al. (1973) recognized that lost sales are a function of
consumer buying behavior. Johnson and Wood (1982, p. 265) contended
that "estimating the cost . . . (of) a stockout involves an under—
standing of customers' reactions to a seller being out of stock at the
time the customers want to buy an item." They listed a set of six
possible consumer reactions and discussed their effects with the
inclusion of a "for the sake of simplicity" (p. 265). All (including
Lusch, 1982) seemed to recognize with Lambert and Stock (1982) that

. . . in consumer goods companies, it is difficult to determine

the cost of lost sales associated with different levels of

customer service. Usually customer service levels are

measured between the manufacturer and intermediaries excluding

the consumer, the person who purchases the product at the

retail level (p. 66).

In any case, there is agreement with Lambert and Stock (1982, p. 66)
that "in order to determine the cost of lost sales at the retail level,

it is necessary to know what the consumer is likely to do when faced

'with a stockout."

17

Conceptual Modeling Efforts

Several models have been developed that deal with responses to
stockouts, ranging from very mathematical ones to graphic, descriptive
ones depicting alternative consumer reactions.

Sasieni (1961) took a mathematical approach. Through an intricate
set of formulas and derivations, he attempted to apply queuing theory to
the inventory problem. Using a taxi stand and the resulting queues of
passengers and/or taxis as his basic starting point, his application
defined the backlog of orders as corresponding to the queue of customers,
and items in stock to the taxis. He assumed that orders not filled in
a certain time are cancelled, and that items are perishable, unable to
be sold if stocked too long. As such, his approach could be applied to
fashion apparel. Sasieni's set of equations needed to determine
stockout effects, however, is highly impractical from a managerial
perspective as he was more concerned with supplying proof of the
theoretical underpinnings of his formulas than with a practitioner's
use.

Schwartz (1966) developed the idea of a perturbed demand curve
to show the effect of loss of goodwill on total stockout costs.
Schwartz identified the stockout penalty as the cost incurred when
demand exceeds supply. He adjusted the demand, after the experience
of a stockout, by a disappointment factor alpha: the ratio of demand
occurring during stockout conditions to total demand. Schwartz
recognized the existence of many statistical problems but contended
that they can be formulated exactly. In a later article (1970), he

zittempted to refine his approach and clarify his perturbed demand concept.

18

The effect of a stockout is not to impose a cost against

the firm at the time of the incident, but rather to modify

the demand pattern in the future from that which otherwise

would have occurred. This is a manifestation of loss of

goodwill, in which the customer alters his future course

of action due to meeting a stockout, rather than causing

the firm some immediate, vaguely defined loss (p. B-509).

It is interesting to note that he deliberately ignored loss of profit
on a sale not made due to the stockout. In any case, he again referred
to the still unresolved statistical problems that continued to plague
his highly mathematical approach rendering his formula virtually
impractical.

Burgin (1970) also had a quantitative approach, correlating the
number of days a stockout existed with the lost sales as a result of
the stockout. He recognized, however, that his approach was very
incomplete:

No account is taken of intangible considerations ("loss of

customer goodwill") or of possible long-term effects

(customer waits this time but in future may go somewhere

else). Similarly no account is taken of interactions with

other items (because one particular item is not available

the customer may not place the rest of his order), or the

possibility of an in-stock being substituted for the item

out of stock (p. 453).

In defending his quantitative relation between time out of stock and
sales lost due to the stockout, Burgin did assume that a monetary
value could be placed on sales lost, without addressing how that is
done. But at least he addressed the issue of length of time out-of-
stock affecting stockouts.

Chang-(1967) developed a model to calculate the cost of stock
depletion for a steel warehouse. He attempted to measure expected

stockout costs by considering them "a function of prior inability to

meet a customer's demands, both for one stockout and a series of

19

future stockouts" (p. 427). Several conditions were established, such
as that data collection needed to be inexpensive and that the
"computational method should be simple enough to be computerized or

to be processed by clerical personnel" (p. 428). Interestingly, he
added another requirement in that the underlying concepts be simple
enough to be readily understood by management.

These considerations were possible given the type of organization
and the sample he worked with: the metal wholesaler had either only
one buyer or a principal buyer per stock item. This allowed him to
limit the possible outcomes of a stockout. Chang then proposed to
attach conditional probabilities to the conditional consequences of
the stockout and, in this manner, to calculate the expected value of
the stockout.

With Niland, Chang (1967) extended this model to include conse-
quences of repeated stockouts, but recognized that

. . . it should be borne in mind that some of the particular

assumptions underlying this method of computing stockout

costs may be quite unrealistic in situations that are

different from the type studied (p. 446).

Walter (1971) used this model to develop his own to determine the
effects of product stockouts in liquor stores in Ohio. He presented
a final consumer perspective and, as a result, had some different
alternative customer reactions than were considered in the Chang model.

Together with Lalonde (1975), the model was extended again to
include subsequent stockouts and their effects (see Figure 1).

The relevance of this study is somewhat mitigated if the conditions
ssurrounding it are taken into account (especially if managerial

implications are considered of value) given the type of product and

20

 

 

 

Ultimate
Response
as a Z
BASIC STOCKOUT MODEL
1
Higher 2.5
Price
2
Same
Price 59.1
es es 3
Lower ‘
Intende-
Purchase Switch Price 2'5
Brand
yes
no no
19.3
Substitut- 5
' Return
Trip 2.5
no
6
Other
Source 14.1
100.0%

Source: Walter and La Londe (1975).

Figure 1. Walter's Stockout Model

21

the controlled conditions surrounding the sample involved in the
study (liquor stores in Ohio are State Operated).

Schary and Christopher (1979) studied reactions to stockouts by
final consumers in a British setting. They broke their model down into
four component modules: I. store and product decisions, II. consumer
behavior, III. response to out-of-stock situations, and IV. retail
merchandising strategy, and concluded that

The only areas of possible measurement are the actual stockout

behavior, and retail merchandising strategy; the rest are

implied. Nevertheless, inferences should be possible based

on the evidence of past and present behavior (p. 61).

Three general conditions were identified affecting the response to a
stockout: brand loyalty, store loyalty and loyalty to neither. The
basis for the distinction was the difference in options customers had
after experiencing a stockout. Whether they went to other stores,
substituted brands or postponed the purchase, brand loyal shoppers
had their image of the store weakened primarily, and possibly of the
product also. Store loyal shoppers experienced a weakening of the
product image first and then maybe of the store. Non-loyal shoppers
posed the least threat, yet, as Schary and Christopher contended, they
could form an important segment in the market to be focused on in the
store management strategies. Schary and Christopher's concern being
with the final consumer is a vital one and, furthermore, their
managerial emphasis in this regard is a critical focal point.

Other, more recent modeling efforts, again, are more oriented
towards higher echelons in the channel. Bennion (1980) dealt with

stockouts as customer service failures with regard to intermediaries

in the channel of distribution as customers. Six case studies

22

allowed him to model the middleman's reactions to a manufacturer
stocking out.

Even though it is important to study these reactions as "the
implications of a stockout are serious to all members of the marketing
channel" (Schary and Christopher, 1979, p. 59), this paper focuses on
(1) the final customer's reactions to stockouts by the retailer regard-
less of what caused these customer service failures, and (2) the
managerial implications for a retailer, as such reactions are important
in determining which products (width) and how many of them (depth)
to carry in the store's assortment.

A final criticism of the above modeling efforts is that they all
assumed that the customers facing stockout situations intended to
purchase the out—of—stock items before entering the store. It is
conceivable, however, that the decision to buy an item is made after
exposure to a related, but at that time unwanted item in the store
(impulse buying) or that the purchase of another item triggers the
want for the out—of-stock item. Zinszer and Lesser (1979, p. 377)
expanded on this, "in a retail store setting, the actual sight of the
product, as well as salesmen involvement, commonly play a role in
consumer's shopping process."

They identified three different types of shopping activities as
inputs in their model: (1) a search for the best purchase to fulfill
a recognized need, (2) purchasing as a result of exposure to the item
(impulse), and (3) acquiring of information to be used for a purchase
decision on an as yet unrecognized need. This allowed them to identify

more customer reactions to stockouts than had been used until that

23

time. The expanded list was divided into long and short run reactions
(see Figure 2).

Furthermore, they identified three types of characteristics that
induce negative consumer reactions to stockouts. First, consumer
characteristics were mentioned: personality, demographics and group
membership. Secondly, store and product characteristics included store
geography, store type and specific product characteristics, such as
prestige and dependability. Shopping processes formed the third
category of relevant characteristics encompassing nearness to purchase,
information processing (e.g., consciousness of stockout) and goals
sought in life.

Zinszer and Lesser's modeling effort was essentially aimed at
explaining stockout responses rather than merely describing them, as
had been done in prior studies. As such, they make a major contribu-

tion from a managerial perspective.

Empirical Measurement Efforts

 

According to Speh and Hutt (1978), up to the time of their
writing, no method was available to estimate the costs associated
with a stockout at any level in the channel of distribution. They
referred to the lack of a concensus on a general method, because
several attempts had been made, and they recognized the difficulty
involved.

In addition to the loss of profit, we may also be concerned

with the loss of goodwill from stockouts. Goodwill is

difficult to measure and often ignored in inventory

decisions, but it can be very important to the overall
profits of the corporation (Coyle and Bardi,1980, p. 93).

24

CUSTOMER REACTION

 

Short-Run Short-Run Long-Run
1. Brand switching o x
2. Product class substitution 0 x
3. Attribute switching of same brand 0 xx
4. Shopping at other stores x x
5. Postponing purchase--return later x x
6. Not noticing stockout--no interest triggered x o
7. Deciding to terminate shopping x x
8. Not buying spurious purchases x o
9. Obtaining a "rain check" x xx
Long-Run
10. Altering choice behavior for later decisions 0 xx
11. Changing opinion of product attributes 0 xx
(cognitive dissonance)

12. Changing distribution of segments x xx

0 = No negative stockout effect on supplier
x Some negative stockout effect on supplier
xx Major negative stockout effect on supplier

Source: Zinszer, Paul H. and Jack A. Lesser, "A Behavioral Model of
Customer Response to Stockout," p. 378.

Figure 2. Supplier Effects of Customer Reactions to Stockouts

25

Magee (1967, pp. 10-20) stated "in a competitive economy where costs
of manufacturing are increasingly rigid, the 'unit cost' of lost
sales is probably growing in most businesses."
In terms of actual measurement, several attempts have been made
to put real numbers on the effects of stockouts. The most quoted seems

to be the study done by Nielsen for Progressive Grocer (1968). An

 

important conclusion reached in this study is that about 20% of the
customers will not substitute a brand, or a size, if the desired item
is out-of-stock, indicating that they go elsewhere or simply postpone
the purchase. Of course, whether a customer switches products depends
on many factors such as product characteristics, but an average of

42% were unwilling to change brands, a percentage that could go as
high as 62% for a product such as toothpaste. Perceived product
differences, even colors, also had an effect on whether the customer
wanted to switch brands: 28% of the shoppers refused to switch brands
if they could not get the color desired.

This study shows postponement of purchase and store switching as
alternative reactions and furthermore that these reactions are
influenced by demographic characteristics: 58% of high income
shoppers would switch, but only 33% of the black respondents would
switch. Blue collar and black shoppers also seemed to be the most
likely to postpone the purchase.

The study brought out the importance of communication with
customers in store management's coping with stockout related problems:
. . . lack of communication is frequently the store's fault.

It is also a reflection of the hopelessness with which some

shoppers view any effort to extract reliable answers from

store personnel. Shoppers have longer memories than
retailers give them credit for. And past failures in their

26

attempts to get accurate information, about why an item is
out-of-stock or when it can be expected are etched deeply
enough in their minds to discourage future pursuits for
answers (Progressive Grocer,1968, p. 8—31).

 

Clearly, there are alternatives open to retailers in mitigating the
severity of negative customer responses to stockouts.

Another measurement effort comes from Shycon and Sprague (1975)
who found that there is a high correlation between out-of-stock
costs, as measured by gross profit lost, and the number of days the

stockout existed. As in the Progressive Grocer study, this study also

 

dealt with retail grocery sales. In the same field, yet more in terms
of the relationship between supermarkets and their warehouses, Ingram,
Brown and Earle (1969) found that retail supermarkets were out of
stock 5.9% of the time and their warehouses 7.6%. A major conclusion
was that stockouts are severe, but that there is no indication of

how severe financially.

According to Walter and Grabner (1975) 40% of liquor shoppers
indicated that they would shop elsewhere if their brand and size were
not available. Mason and Wilkinson (1977) identified product unavail—
ability as a major source of consumer dissatisfaction. Their research
was concentrated in food retailing, where they also concluded in a
later study that while 45% of the shoppers said they would switch
stores, only 6% actually did so when they found the product they were
looking for unavailable (Mason and Wilkinson,1977).

Schary and Becker (1978) looked at market share for the product
as a measurement basis for the effect of stockouts. They studied the
distributions of beer in the northwest U.S. and found that certain

brands, due to a strike among distributors, lost market share. More

27

importantly, it was found that after the strike was over market share
did not return to pre—strike levels. A confounding problem in this
study was that after the strike, locally brewed beer brands had their
prices raised slightly and national brands remained unchanged, which
affected the results. Labeled as a quasi-experiment due to the
relatively controlled conditions for the study, this measurement effort
has merit in the sense of its longitudinal nature. The study also
pointed out that "the influence of a stockout is greatest in the
immediate post-impact time periods" (Schary and Becker, 1978, p. 40).
This furthermore implies that prevention of stockouts is an enabling
element in the marketing mix for the product, enabling in the sense
that "all efforts to build brand loyalty among customers and ultimate
consumers must fail if the supply of products to the market becomes
erratic or uncertain" (p. 41). Using Schary and Christopher's reference
(1979) to the retailing mix, product availability would then be an
enabling factor in the creation of store loyalty.

Experimentally, Charlton and Ehrenberg (1976) in their study of
brand choice variables, tested the influence of product availability,
among others, on brand loyalty. Particularly, the purchase of
artificial "brands" of detergent was monitored over a period of 25
weeks. The sample of heavy-user customers was faced with the withdrawal
of one of the available "brands" and was told that the brand was
temporarily out-of-stock. One of the conclusions was that most buyers
had no difficulty substituting for the unavailable brand, the
switching of which was encouraged within the "outlet" by a price

reduction. More importantly it was observed that "subsequent sales

28

of the withdrawn brand were not affected at all" (Charlton and
Ehrenberg, 1976, p. 102).

Charlton and Ehrenberg stated furthermore that experiments of the
kind they ran, experimentation on a longitudinal basis, is the main
way "for learning about consumers' responses to varying marketing
inputs" (p. 102). Miklas (1979) agreed and proposed an ad hoc
consumer panel to monitor customer reactions over time. He suggested
a quota sample of heavy users of a frequently purchased product be
monitored during simulated shopping trips using photographs of product
assortments in the subject's own home. Collected over a period of
20 weeks, Miklas stated that the data thus collected allow for testing
of models and hypotheses relating to individual customers. As an
alternative method, he also suggested the paired-preference test.

By requiring the making of preference choices between all possible
pairs in a single merchandise classification,

. . . the researcher will be able to deduce the order of

the various alternatives available to the consumer and

ultimately the researcher should be able to predict the

proportion of potential buyers who will: switch brands,

shop at another store, etc. (Miklas, 1979, p. 239).

Even though, as Miklas contended, large amounts of relevant data
might be provided on the topic of retail shelf out—of-stocks, which
to him is under-researched, the time and money that needs to be
invested in the project in many cases becomes prohibitive.

Sanger-Harris, Inc. of Dallas, Texas, provides an example of
retailer efforts underway to measure the impact of stockouts (Carrekar,
1983). Sales personnel are required to keep a record of customers

asking for items not stocked or not available at that time. An

estimate is made of the costs involved which might lead to a decision

29

to carry the item not stocked. The method has been recommended and

used many times before (Buyer's Manual,1965) (see Figure 3),

 

the effectiveness could conceivably be hurt in that not every customer
experiencing a stockout will "voice" the problem to store personnel.
As a result, these effects rely on well-trained personnel creating an
atmosphere in which consumers feel they can communicate any problems
they have with the assortment.

In all the efforts referred to above, a real key to the severity
of reactions to stockouts is the willingness of a customer to buy
substitute brands, colors, sizes, etc. Goodwill implications for the
store as measured by store loyalty form a different factor (Stephenson,
1969). This has to do with availability of store alternatives as well,
a competitive factor that is reflected in market share for a particular
store (Schary and Becker51978). Lesser (1981) found that "stockout
dissatisfied shoppers" caused the store severe image problems although
the exact impact differed, based on demographic characteristics.

The significance for the purposes of this paper is that stockouts are
very important for a retail outlet, which is very dependent on a certain
image (Schary and Christopher,1979); also, stockouts cause a lot of

emphasis to be put on other elements of the "retailing mix,‘ such as

costly promotions to rectify the situation. Bowersox et al. (1968)
stated the following in this respect.

The full impact of a lost sale is directly related to the
customer service policies of competitors. A customer who
is denied by one supplier and serviced by a competitor may
become a customer again only through the use of substantial
sales and promotional effort (p. 196).

30

 

 

Lost a Sale!

H Because we were out of:

 

 

 

Rem ember:

tell us.

another sole.

0 A solo lost is money lost in commission.

0 We don't how you're out of something 'til you

oDon'twait...tellusnowbeforoyoulose

 

| In. Dept. sun so.

...;

 

 

 

 

 

661229! The Baltimore Bums has c... Mina. Gs.

 

o If no sales were lost. please'so indicate by

checking here...[j 37" 2

 

Source: The Buyer's Manual (1964).

Figure 3. Example of a Want Slip

 

31

Store Image and Product Unavailability

Introduction

 

As developed earlier, a definition of a stockout should include
situations in which a customer asks for an item that the retailer does
not carry. However, something must give that customer reason to believe
that the store carries the desired item. Without going into specific
reasons behind those expectations, we can safely assume that shopping
stores of that type and others, and word-of—mouth will have an effect
on those expectations. Therefore, the image a customer has of a store,
no matter how it is formed, could be responsible for the trip to the

store to discover the item's unavailability.

Definitions of Store Image

 

Store image in general refers to the way in which consumers
perceive a store (Engel, Kollat and Blackwell, 1974). Many authors
define the concept more specifically. In 1958, Martineau showed that
besides the usual price, quality and service interpretations, also a
"personality" factor played a role in why customers shop at a certain
store. He concluded that "the shopper seeks the store whose image
is most congruent with the image she has of herself" (p. 48). Even
though economic factors will always be important, Martineau stated
that "price announcements" are meaningless if the store image is not
acceptable to the shopper. One of the conclusions these observations
led to was that a store cannot be all things to all people.

Martineau (1958, p. 47) described store image as "the way in

which the store is defined in the shopper's mind, partly by its

32

functional qualities and partly by an aura of psychological attributes."
Therefore, he concluded that not only store image preselects customers,
but also that it is a major determinant in retail buying behavior.
Through many examples, he helped show that, even though it is still a
vague concept, it can be made operational through an apprOpriate
research design. In a subsequent article, Martineau attempted to
provide more insight into the concept by relating store image to

social class. He found a positive correlation between these two
concepts (p. 49).

Arons (1961, p. 2), saw image as a "complex of meanings and
relationships serving to characterize the store for people." (As such,
he not only recognized Martineau's attributes ("meanings"), but he
added a dimension that dealt with elements that somehow tie the
attributes together ("relationship"). He implied that these relation-
ships are necessary for shoppers to be able to manage that complexity.

Kunkel and Berry (1968) summarized the definitional development
up to 1968 by stating that retail store image is the total conceptualized
or expected reinforcement that a person associated with shopping at a
particular store. However, they added that even though the literature
on retail image has increased notably in the ten years prior to their
writing the rate of knowledge has lagged.

Lindquist (1974), while discussing various definitions, concluded
the following:

One may generalize . . . that the entity, 'retail store image'

does exist and that its descriptors are to be found in varying

degrees among the attributes [found]. Of particular interest

is the finding that of the nine summary factors listed, three

were apparently dominant, and of the three, Merchandise

(Selection, Quality, Pricing and Styling/Fashion) appears to
be the key image factor (p. 37).

33

Through his work, Lindquist indicated that there was no agreement on a
universal definition on the concept of store image. Berry (1969, p. 3)
had already stated that "characteristically, 'image' had been treated
in the literature as an intangible 'something', a vague, untouchable,
forbidding, virtually unmeasurable phenomenon." Pessemier (1980)
seemed to underscore this confusion. But the common denominator appears
to be a basic disagreement on the determinants of store image. Pessemier
concluded that current image research focuses on not only understanding
shoppers, but also the stores in which they shop. This would lend
credibility to Kunkel and Berry's (1968, p. 21) conclusion that "retail
store image is an alluring, yet uncrystallized concept" even today.

Martineau (1968) stated that the shopper seeks the store whose
image is most congruent with the image she has of herself. Subsequent
studies showed evidence of this, culminating in Bellenger (1976)
finding support for the basic hypothesis that the correlation between
self and store image is related to store loyalty.

The importance of store image has been contested occasionally,
starting as early as Alderson and Hollander who adopted a more economic
view of the consumer. Alderson saw the consumer as being a problem
solver with a "goodly" measure of common sense with respect to economic
matters. Hollander (1958) concluded that

. . . if shopping is simply operational behavior through which

fairly rational individuals seek to gather bundles of desired

goods without excessive expenditure of money, time or effect,

then our beloved concept of 'personality' is less important

than such mundane aspects of retailing as merchandising,

pricing, and customer service (p. 176).

Dalrymple (1969) resolved these extremes by stating the following:

If consumers make complex, multivariate value judgments
which result in some total impression being formed, it does

34

not mean that the considerations which mold such impressions

are necessarily noneconomic or emotional in nature.

Rationality and imagery are not incompatible concepts

Doyle and Fenwick (1974) provided a straightforward definition,
that store image is the consumer's evaluation of all salient aspects
of the store as individually perceived and weighted.

In any case, store image plays a very important role in retail

buying whether the basis for the image is rational or emotional.

Retail Store Image Determinants

 

Few authors agreed with Fisk's (1962) initial belief that store
location is perhaps the most powerful dimension of image. Martineau
(1958) thought that elements of such image were primarily layout/
architecture, symbols/color schemes, advertising, and sales personnel.
The latter especially is brought out as a key element through various
examples. He does not touch on product availability, merchandise
suitability and assortment, etc., as ingredients which subsequent
authors found to be very important.

Dalrymple (1969), while using essentially the same factors in
describing store image, employees, fixtures and decoration, price and
advertising, cautioned that store image represents a composite formed
from a great number of pieces of information. Subsequent articles
continued to stress this compositional nature (e.g., Bearden, 1977).
Engel, Kollat and Blackwell (1974) discussed general determinants of
store choice and recognized that these vary a lot with the type of
product bought, type of store in which the product is generally

available and the customer characteristics. However, this variation

35

is in terms of their relative importance in a given situation rather
than in their absolute value as store choice determinants. In general,
they are (1) location, (2) depth and breadth of assortment, (3) prices,
(4) advertising and word-of-mouth communication, (5) sales promotion,
(6) store personnel, (7) services, (8) physical attributes and (9) store
clientele. Engel, Kollat and Blackwell (1974, p. 453) concluded that
the way the customer perceives these determinants make up the store's
image, further, "while definitions differ somewhat, the essential

point is that the store, as perceived by the consumer, may differ from

' Evidence of

what the store 'actually is' in an 'objective sense'.'
the difficulty in pinpointing determinants continues to be found in
the literature (e.g., Arnold, Ma and Tigert, 1978; Alpert, 1980).

Lindquist provided an extensive review of the literature on retail

store image attributes (see Figure 4).

Store Image Measurement Methods

 

Engel, Kollat and Blackwell (1974) discussed the semantic
differential as the most popular method to measure store image.
As a caveat, however, they stated that the bipolar adjectives must
be carefully chosen to include actual determinants. Kelly and
Stephenson (1967) discussed this method in detail. Some major
determinants of store image they cited, after applying the semantic
differential, were physical characteristics of the store, products
offered, convenience of reaching the store from the customer's location,
prices, store personnel. These were further broken down, but one of

the conclusions of their research was that the semantic-differential

Merchandise

 

Quality
Selection/Assortment
Styling, Fashion
Guarantee

Pricing

Service

Service, General
Salesclerk Service
Self—Service

Ease of Return
Credit

Delivery

Phone Orders

Clientele
Social Class Appeal
Self-Image Congruency

Store Personnel

Physical Facilities

 

Physical Facilities
Store Layout
Shopping Ease
Architecture

36

Convenience

 

Convenience
Locational Convenience
Parking

Promotion

Sales Promotion
Advertising/Display
Advertising
Trading Stamps
Symbols and Colors

Store Atmosphere

 

Atmosphere/Congeniality

Institutional

 

Conservative/Modern
Reputation
Reliability

Post—Transaction

 

Satisfaction

Source: Lindquist, Jay D., "The Meaning of Image," pp. 33-35.

Figure 4. Image Attributes Popular in the Literature

37

"can be used to develop information on virtually any patronage
determinant a decision maker finds interesting" (p. 47).

Major criticisms have been labeled against the semantic differential
as well. Kunkel and Berry (1968) stated that by forcing the respondents
to evaluate characteristics that do not necessarily play a role in that
particular respondent's image of the store being studied, the actual
results measure an "image" that is apt to show a higher correlation
with the instrument than with reality. He explained that

. . . the semantic—differential test forces responses for

all image components included in the questionnaire, and

hence cannot serve to isolate critical image components

(Kunkel and Berry, 1968, p. 25).

According to Marks (1976), retail image studies typically employ
the semantic differential with customers being asked to rate many
individual characteristics of a store. The number of characteristics
depends upon the creativity of the author, ranging from as few as six
(Fisk, 1961) to as many as 42 (May, 1971). Berry (1969) found 12
determinants of store image and concluded that his measurement showed
a greater precision than Fisk's. Thus, he essentially inferred that
the more determinants the better the image measurement.

Marcus (1972) pointed at the elusive nature of the image concept
after studying the variation in image between stores of the same
retail chain. The fact that such variation is possible was further
studied by Hirschman, Greenberg and Robertson (1978). They essentially
found that both within and across markets the principal components
from ten store image attributes resulted in disappointingly low levels

of congruence. In other words, retail store image is among other

things also trading area specific. However, it is reliably possible

38

to state that store image attributes relevant in one market are also
relevant in another market. Thus, if a retail store is higher ranked
on four very salient attributes in one area, it will also have a

desirable market position in other areas.

Retail Store Image vs. Customer Satisfaction/Dissatisfaction

May (1974) observed the following in one of her studies on retail
store image:

Image research cannot stand on its own. It must be supple-

mented by other customer research--customer profiles,

shopping habit studies, trading area studies, and so forth--

but more importantly, it must be supplemented by the

merchandising and operating expertise of the members of the

retail management. The integration of image research into

other types of consumer information, however, is vital to

retailing today (p. 20).
Evidence of the relevance of this observation is continuously uncovered.

Venner (1979) estimated that for every $100 a consumer spends in a
typical retail store, another $75 to $90 would have been spent if the
customer's needs could have been better satisfied. He added that "at
least half of this loss has been attributed to out-of-stock conditions"
(p. 2). This customer satisfaction is an important element in store
image (e.g., Stephenson, 1969; Lesser, 1981) and profitable retailing
in general (Herndon, 1972; Lindquist, 1974; Schary and Christopher,
1979). Establishing customer service departments has a favorite
means of enhancing customer satisfaction as a key to retail profit-
ability (Fornell, 1976). According to Fornell, customer service

activities such as complaint resolution, are very important with regard

to customer satisfaction. This particular research culminated over a

39

long period in which it was believed that the level of satisfaction was
directly related to the level of retailer effort to reduce post-purchase
phenomena such as cognitive dissonance. Lately, however, studies have
pointed out

. . . that satisfaction results from a subjective comparison

of the expected and received product attribute levels . . .

but that the exact nature of the satisfaction process is

unknown (Oliver, 1981, p. 26).

Hirschman (1970) developed a theory stating that individuals react
to discrepancies between desired and actual states of affairs by the
market mechanisms of "exiting" and "voice". The exiting consumer's
reactions include switching brands or shifting patronage. In contrast,
"voice" refers to a verbal protest directed at the seller, and, if
there are no satisfactory results, through third parties. Consumer
reactions such as those modeled in Walter and La Londe (1975) (Figure
1) are classified as "exiting" behavior.

According to Oliver (1981), there is no agreement on the psycho-
logical meaning of the satisfaction concept. The amount of research
effort spent on dealing with this concept and the implications of
stockouts for that satisfaction as described earlier warrants a closer
look at satisfaction/dissatisfaction research. Oliver (1981) continued
to explain as follows:

Satisfaction may best be understood as an evaluation of the

surprise inherent in a product acquisition and/or consumption

experience. In essence, it is the summary psychological

state resulting when the emotion surrounding disconfirmed

expectations is coupled with the consumer's prior feelings

about the consumption experience. Moreover, the surprise

or excitement of this evaluation is thought to be of finite

duration, so that satisfaction soon decays into (but never-

theless greatly affects) one's overall attitude toward

purchasing products, particularly with regard to specific
retail environments (p. 27).

40

It can be concluded from the above literature that customer
satisfaction is related to past experiences and future expectations
and intentions. Furthermore, as the second part of Oliver's observa-
tion suggests with regard to "decaying satisfcation", importance is
attached to retailer efforts to mitigate negative experiences such as
stockouts. Therefore, it is important to learn what consumers expect
retailers to do in the case of product unavailability, and what will
bring them back after they have decided to leave the store dissatisfied.

The relevance of the literature on customer satisfaction/
dissatisfaction that applies to this research concerns the concept of
expectations which customers have before encountering the stockout,
rather than with post-purchase conditions which is generally associated
with the construct of satisfaction (e.g., Oliver, 1981; Andreasen,
1977). Miller (1977, p. 72) stated "customer satisfaction [really]
results from the interaction of levels of (a) expectations about anti-
cipated performance and (b) evaluations of perceived performance."
Particularly, it is the "expected" type of expectation, as labeled
by Miller (1977), based on past average performance. Thus, it reflects
what the customer feels performance probably will be. In other words,
even if the retailer normally does not carry an item, merely by the
consumer expecting and wanting it, there is still a stockout and the
consequences can be accordingly.

With regard to this type of expectation, Oliver (1981) used the
concept of disconfirmation: the degree to which the product or
service performance deviates from the pre—purchase expectation level.

This deviation could be positive if performance was above expectations,

41

negative if below expectations or zero if expectations equal
performance. Oliver (1981) goes on to say that

. . . because of the complexity of the retail store milieu,

the potential for expectancy disconfirmation is greatly

enhanced. Parking areas may be filled, stockouts may occur,

clerks may be discourteous, or, on the pleasant side, an

anticipated bargain may be encountered (p. 34).

The concept of disconfirmation is therefore extended to store
performance as well. It can be inferred then that satisfaction is
also a function of subjective comparison of the expected and received
store attribute levels. This indicates the relevance of retail store
image literature in the context of this paper. It is agreed with
Oliver (1981) that

. . . the first step in the application of satisfaction

processes is an understanding of expectation formation.

It is generally agreed that expectations are consumer-

defined probabilities of the occurrence of positive or

negative events if the consumer engages in some behavior.

This definition applies equally to product purchase,

store patronage, and complaining behavior. In all

cases the consumer enters a situation with various expec-

tations ranging on a probability continuum from 'certain

not to occur' to 'certain to occur' (p. 33).

Oliver and Linda (1981) found that simply asking respondents to
predict the degree of satisfaction anticipated on a dissatisfied-
satisfied scale can be used to measure such expectations. This would
avoid having to measure both evaluation and beliefs, but it means
sacrificing diagnostic information evaluation and belief measurement
could provide. In terms of measuring scales with regard to determining
expectations, Oliver (1980) found that the Likert and semantic-
differential scales had the highest reliability.

In summary, customer expectations as to an item's availability

prior to entering a store appear to form an important factor in

42

stockout behavior. Therefore, not having an item on hand due to
logistical or clerical errors, or for strategic reasons all, at least

theoretically, affect stockout behavior.

Fashion Merchandising

Introduction

 

Definitions of stockouts and the discussion of implications thereof

have always been very situation specific. For example, the Progressive

 

Grocer study (1969) related primarily to grocery products; Walter (1971)
referred to liquor store items; Schary and Becker (1978) were interested
in beer distribution; while Bennion (1980) and Chang (1967) studied
higher echelons of the channel of distribution. However, an industry
where psychology plays a very major role in the buying process, as will
be shown later such as the apparel merchandising field, has not been
exposed to any of the kind of studies as mentioned above. The peddler,
regarded as one of the pioneers in the development of retailing,
recognized early on that you cannot do business from an empty wagon,
thereby emphasizing the lost sale consequences, yet unmeasured, of

a stockout (Troxell and Stone, 1981). Most of his customers relied

very much on his traveling around for information on fashion, access

to goods, etc., and given the fairly limited number of peddlers relative
to the territory, there was not much competition as we know now.

This essentially eliminated the threat of losing customers to
competitors, yet without that threat costs were already regarded as

high enough to pay attention to properly stocking the wagon.

43

To put the research setting into perspective, a general background
on the fashion merchandising industry is provided. The overall
discussion is divided into a review of definitions frequently used in
this field, a discussion of channels of distribution used in the
industry, and an exploration of the activity of merchandising in

fashion stores.

Definitions

 

Fashion invariably means different things to different people and
many words have been used to describe it to the point of becoming
synonymous (Nystrom, 1928; Troxell and Stone, 1981). Fashion is defined
as a style that is accepted and used by the majority of a group at any
one time. As a further classification, high fashion refers to apparel
shopped for by the group of elite customers, the fashion leaders,
usually the innovators in adoption of change in fashion. Mass fashion
implies styles adopted by the majority of customers, yet fashion
conscious, usually at lower prices. The style is "the characteristic
or distinctive appearance of agarment, the combination of features
that make it different from other garments" (Troxel and Stone, 1981,

p. 3). One important aspect with regard to styles is that they follow
a cyclical path, thus bringing them in and out of fashion (Fringe,
1982; King, 1963). Laver (1969) described the following cycles as
the relationship between taste and fashion to illustrate the fickleness

of the consumer and the social implications of fashion:

indecent -- 10 years before its time
shameless —— 5 years before its time
outre -- 1 year before its time
smart -- in its time

dowdy -- 1 year after its time

44

hideous -- 10 years after its time

ridiculous —- 20 years after its time (p. 7).

Troxell and Stone (1981, p. 5) recognized that the time it takes
for an individual fashion to complete its course depends on its style
as they support the idea of cycles in fashion, "a new style is often
considered daring and dubious in taste. It is then gradually accepted,
then widely accepted, and finally gradually discarded."

One important common denominator from the preceding discussion is
the aspect of time. Apparently, there are two implications. One, a
retailer has to make an assessment as to the length of time a certain
style will stay in vogue and therefore the extent to which he wants to
be involved in carrying it. Thus, the length of time of popularity of
a style should influence the retailer's perception of the importance of
stockouts. Along the same lines, timing also affects a customer's
perception as expectations are involved regarding the retailer carrying
the item, but being out of stock at the time it is desired. Another
generalization from these definitions relates to the type of customer.
Popularity has been identified as a criterion in the above definitions
and that phenomenon is dependent on individual and/or group tastes,
which implies the critical influence of heterogeneity of customer

demand in merchandise assortment planning.

Channels of Distribution in Fashion Merchandising

In fashion merchandising a channel of distribution most clearly
follows a pattern of producer-retailer—consumer (Greenwood and Murphy,

1978) (see Figure 5).

 

Fashion-oriented
services

 

 

 

 

 

 

 

Source:

45

 

 

CREATORS

 

 

 

 

PRIMARY SUPPLIERS

 

 

Textile Industry:
Fiber Producer
Fabric Producer

 

 

 

 

PRIMARY MANUFACTURER

 

 

Apparel Industry:
Apparel Manufacturer
Contractor
Jobber

 

I
|
l
l

l
|
l
I
l
l
l
l
l
l
l
l

 

 

 

 

PRIMARY DISTRIBUTORS

 

SALES
REPRESENTATIVES

 

 

 

 

Retail Outlets

 

 

 

 

CONSUMER

 

 

Industrial Consumer
Public Consumer

 

 

and Marketing, 1978, p. 57.

 

Figure 5.

---- = Sales Efforts

= Flow of Goods

Greenwood, Kathryn L. and Mary F. Murphy, Fashion Innovation

 

Distribution Channels in Fashion Merchandising

46

Greenwood and Murphy (1978) stated that

. . . fashion-marketing is unique in several aspects.

. . . the flow of goods begins with the supplier, move
directly to the manufacturer, then to the retailer and
finally to the consumer. Fashion goods are seasonal, and
consumer acceptance cannot be predicted accurately enough
for merchandise to be processed by a wholesaler or stored
at a distribution center over a period of time (p. 178).

Typical channel participants are:

With

a. The manufacturer, whose activities could involve
purchasing fabrics, designing styles and patterns,
showing styles to potential retail buyers and order
taking, cutting pieces according to pattern layouts,
and sewing and assembling.

b. The jobber, who could be involved in designing styles,
making arrangements for outside contracting in cutting
and sewing, and storing and shipping of finished
garments.

c. The contractor, who could either cut the garment pieces
according to manufacturer specifications, and/or sew
and assemble the finished garments according to such
specifications.

regard to the role of retailers, Frings (1982) noted that

. . . exclusivity does not seem to be as important to
retailing as it once was. In the United States the
consumer is more interested in availability. Stores
across the country try to provide their customers with
a wide selection of popular national brands. As stores
stock more and more national brands, exclusivity tends
to decrease (p. 218).

Despite this recognition of the broadening of choices for the consumer

(increased width of the assortment), there is continued persistence

to refer only to stock shortages (lack of depth of assortment) in

stockout related matters, even in very recent textbooks in the field

such as Frings' work. These shortages are then defined as lower

physical inventory versus book inventory and are generally blamed on

theft, damage or clerical error. Further discussion of the impact is

47

limited to stating that it could be severe (James, Walker and Etzel,
1972; Wingate, Schaller and Miller, 1972). Continued to be ignored
are the expectations retailer actions create among shoppers as

described in the above quote by Frings.

Merchandise Assortment Planning

 

It appears from the above discussion that availability at the
right time is extremely crucial, particularly for the fashion retailer.
Having too much inventory at the time interest in a fashion diminishes,
results in markdowns and sometimes throwaways when that style has
become "dowdy". Not having it on hand could immediately result in
lost sales. Even though they are costly, as addressed before, it is
the possibility of other consequences affecting inventory management
in fashion retail stores that is of primary interest in this study.

An underlying implication is that studying customer perceptions
and responses to stockout situations is critical in reducing some of
the many uncertainties in fashion merchandise assortment planning.
The above points are further illustrated by the principles of fashion
as identified by Troxell and Stone (1981).

1. Consumers establish fashions by their acceptance or
rejection of the styles offered. Designers try to
anticipate what a customer might like through trial
and error. Retailers choose among those, sometimes
hundreds of 'trials', styles which they think will
appeal to their customers. The ultimate customer
decides on what becomes fashion through what they buy.

2. Fashions are not based on price. Different versions of a
certain style may eventually be offered at many different

price levels, yet the style itself will be essentially
the same.

48

3. Fashions are evolutionary in nature; they are rarely
revolutionary. An important key to fashion design is
to keep in mind what is currently in vogue. As Troxell
and Stone stated, consumers today buy apparel and
accessories to supplement and update the wardrobe they
already own, some of which was purchased last year,
some the year before, some the year before that, and
so on (pp. 4—5).

4. No amount of sales promotion can change the direction
in which fashions are moving. Troxell and Stone used
the example of retailers' and manufacturers' efforts in
the late 1970's and early 1980's to get young people to
wear hats. As these failed, they also drew the
conclusion that timing is very important for retailers;
once sales start slumping all efforts should be geared
to getting rid of the leftover stock.

5. All fashions end in excess. Once the extreme in

styling has been reached [diameter-, width-, lengthwise],
a fashion is nearing its end. The attraction of the
fashion wanes and people begin to seek a different look--
a new fashion (p. 15).

These "principles" imply that a retailer has very little, if any,
influence on what is or what becomes fashion. They also imply that
merchandise assortment planning is a risky business for retailers.

A retailer with some influence on aspects of fashion, at least as a
source of information, is considered a fashion leader. This illustrates
the importance of customer expectations and necessitates a discussion

of the type of retailer involved in fashion merchandising.

Categorizing retailers is a difficult process, but the concensus
in the literature is that the basis ought to be leadership position.
Troxell and Stone (1981) summarized that retailers who are carrying
new, usually expensive styles, are fashion leaders. Characteristically,
they seem to carry few lines and limited amount of depth within those.
The biggest group is comprised of fashion followers which carry the
products that are in the middle stages of their life cycles. Uusally

the fashions are widely accepted and more moderate in price. Mass

49

merchants are the ones who can be considered the laggards in carrying
widely accepted fashions, generally at lower prices.

The leadership position of the retailer affects among other things
the assortment carried in terms of width and depth. The assortment
is identified by Troxell and Stone (1981) as one of the reasons why
consumers might select a certain store over another. Other reasons
are fashion reputation, price ranges, services offered, size and
layout of the store, etc., yet no relative importance standing is
alluded to. However, it is very important to identify the effects
inadequate stocking policies have on such patronage.

Wingate (1959, p. 6) stated that the goal of all assortment
planning is to carry "stocks that provide the customer with the
combination of [selection] factors that to [that customer] are most
significant."

It is interesting to note that Troxell and Stone (1981), while
discussing this objective, are more concerned with overstocks and
having room in the buying plan for "hot" items and special event buys,
without addressing the issue of understocking. This seems fairly
typical for the literature in this area, yet, as stated above, severe
implications following a stockout have been recognized (e.g., Wingate,
1959).

A potentially complicating factor that remains to be addressed,
is that "producers of budget and moderate priced fashions are becoming
reluctant to accept reorders for any but the most classic of their
styles" (Troxell and Stone, 1981, p. 375). This places even more
emphasis of the adequacy of assortment. In addition the importance

of reputation (image) is enhanced in determining where customers

50

will look for new fashions as customers seem to be ”making it plain
that they want to see new styles each time they shop a fashion
department" (Troxell and Stone, 1981, p. 375).

Naturally, the fashion merchandising field has its theories for
adoption of fashions, too. The original downward-flow theory has been
joined by the horizontal—flow and the upward-flow theories (King, 1963).
Each has different implications for fashion merchandising, but an
important element involving all of the theories is the role played by
the customer. Since, as identified above, the customer determines
what is fashionable, it is necessary to look at different groups of
customers as distinguished by the degree of fashion leadership,
consistent with the classification of retailers. Consequently, we
have fashion leaders and fashion followers. To King (1964, p. 124),

a fashion leader is "a person who is quicker than his or her associates
to try out a new style." In some instances he even recognized a
fashion influential as being someone whose advice is sought by
associates. What determines a follower or a leader is of course
situation specific, and many distinguishing characteristics have been
identified. With Bell (1947, p. 48) though, it has to be noted that

a fashion leader is not the creator of fashion, "the leader of fashion
does not come into existence until the fashion is itself created."

The importance of this aspect of adoption, is that retailers need
to be conscious of this process as it may determine what will be
demanded in the (near) future by the majority of the consumers. Thus,
recognizing innovators and their purchases could give the retailer
some time in the proper planning of his merchandise assortment. But,

most of all, it is clear that a fashion retailer should create an

51

atmosphere in which a shopper will ask about the item she cannot find
at that time. Identifying those customers displaying either "voice"
or "exit" behavior, in Hirschman's terminology, becomes very relevant.

A last issue to be addressed is that consumer demand for apparel
products has been called relatively inelastic. As Rachman (1975,

p. 143) puts it, "lower prices do not cause large increases in sales.
Nor does an increase in consumer demand." One reason is the lack of
established brands, or the minor importance of brands. Recently,
however, as witnessed by the upsurge in demand for designer jeans,
for example, branding has become more a factor (Frings, 1982).

Responses to such developments would indicate that status is very
important and that price takes more of a backseat. Elasticity as
discussed by Rachman (1975) relates to the apparel industry in a macro
sense. On a micro level, elasticity shows great fluctuations, both by
outlet and by apparel type (women's, men's, etc.) (Rachman, 1975).
Everyone needs clothing, but there are many alternatives as to the
style or color bOught and the store where bought. As a matter of fact,
store choice seems to be a critical one, which puts the status impact
of stockouts into the foreground. It also points at stockout behavior
differing by what in particular was unavailable: style, color, brand,
Etc.

Particularly the first principle of fashion, or the consumer
deciding what becomes fashion, underscores Magee's point referred to
earlier. Not only in business in general is the "unit cost" of lost
sales growing, but through its trial and error practices, unit cost is
increasing even more in the fashion industry. This phenomenon further

justifies a specific focus on the fashion relating business,

52

especially since Stern and El-Ansary (1977) have noted that one of
the five basic steps in retailing strategy design involves
. . . developing the retailing mix that represents a plan
for the allocation of available resources among alternative
uses in a coordinated manner to maximize the total impact
generated to influence the customers in the defined market

target [and furthermore that] . . . the main mix element is
merchandising (p. 60).

Conclusion

The illustration used by Troxell and Stone concerning the peddler,
points out the major shortcomings of discussions on stockouts in
fashion merchandising, that not having enough on his wagon implied
not enough depth of his assortment. Furthermore, as his customers
came to regard him and their major source of information on fashions,
the width of his assortment was not as critical for his business.

In subsequent developments, such as increased competition, width has
become more of a factor. Evidence is found in the specializations of
fashion retailing emphasizing various combinations of high or low
fashion and/or wide or narrow assortments.

The third element of assortment, consistency, deserves attention
as well. Consumers have a wide choice of stores to patronize. As
identified above, many customers have a tendency to shop more than one
apparel store, forming opinions of them as they shop. These impres-
sions, even of those not visited, are affected by retailer advertising,
product assortment decisions, word-of—mouth, etc. Continuing to
include a store on the "shopping rounds", is influenced by these
"images". Based on the image research reported, several components

have been identified, not the least important of which is merchandise

53

assortment. While realizing the relevance of width or depth,
consistency, or the degree to which the merchandise is related, is
a critical factor in the forming of those images. Yet, until now,
the fashion merchandising literature has not paid attention to the
element of consistency.

According to Progressive Grocer (1968, p. 8-19), stockouts are on

 

the rise because of four reasons: (1) squeeze of profits, requiring
cost control; (2) more inventory control, as "there is little room for
error"; (3) proliferation of new items; and (4) tight labor market.
Given the above discussion of fashion, the third reason as identified
above is especially applicable in the fashion merchandising field.
Furthermore, a (potential) squeeze on profits is a fact of life for all
of business and will need to, among other things, result in more

inventory contrOl (Lambert, 1976; Ballou, 1973; Wall Street Journal,

 

August, 1980).

CHAPTER III

METHODOLOGY

Introduction

The review of the literature in Chapter II provided a basic
overview of what is known in the area of stockouts and their effects
on the consumer. The review can be summarized with Lusch (1982) who
had one of the most general coverages, identifying three effects for
a retailer who is out-of—stock: favorable, unfavorable, and
questionable. Favorable effects occur when a customer switches
brands, styles, etc., but buys within that store. It is only favorable
in the short run as, due to a recurring of the situation, customers
will increasingly wonder if it is worth the trip to that store.

An unfavorable effect exists if the customer buys elsewhere at
that time, and, especially, if she decides to stop patronizing the
original store for future purchases. The third set of effects is
called questionable, involving a postponement of the purchase. In
the short run, it turns out favorable if the customer comes back to
buy that item, but unfavorable if she does not. The important con-
clusion for this research is that frequency of stockout situations
leads, in the long run, to diminished patronage.

As to actual numerical analysis of stockout implications in

terms of dollar cost (e.g., Progressive Grocer, 1968) or alternative

 

reactions in probabilities (e.g., Walter and La Londe, 1975), the
conclusion is that it depends on the situation, the product,

demographics, etc.

54

55

Lessig (1973) pointed out that store loyalty is related to store
image, confirming many previous studies which had assumed this relation—
ship. In many of those studies, as reviewed in the previous chapter,
image determinants were searched for with the perspective in mind of
enhancing this image. Merchandise selection/assortment was one of the
most common determinants (e.g., Lindquist, 1975). Stockouts, as a
factor involved in this ingredient, should therefore also be related
to the image determination process. The above can be summarized in the
model presented in Figure 6. The model portrays consumers responding
differently to stockout situations. It also shows that these reactions
are influenced by a group of factors related to store image. Evidence
of this comes from many sources in the literature (e.g., Martineau,
1958; Myers, 1960; Rich and Portis, 1964; Berry, 1969; Lessig, 1973).
Based on this literature, as the model indicates, prior experience
with factors such as merchandise selection, prices, etc., affect
whether the out—of—stock item will be bought at a later date, substi-
tuted in the same store, purchased elsewhere only at that occasion or
continued to be bought in a competitor's store.

Other situational variables affect reactions to stockouts as well.
For example, the reason a shopper had to enter a store will affect the
way in which she responds to a desired item being unavailable.
According to Bellenger, Robertson and Greenberg (1977):

The store patronized is a result of both the relative

importance of various motives and the shopper's assess-

ment of alternative stores with respect to the various

factors used in making the selection (p. 30).

In other words, the intention to buy a specific item for a specific

purpose will result in a customer reacting in a different manner upon

56

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57

finding the item out of stock than the buyer who sees shopping as a
social event at the time. The latter, the recreational shopper, in
Bellenger and Korgaonkar's (1980) terminology, might merely postpone
the purchase, whereas the first could stop patronizing the store.

With regard to the other elements of the model, the literature,
as discussed in Chapter II, is replete with accounts of the relation-
ship between situational variables and image components (e.g.,

Martineau, 1958; Progressive Grocer, 1968).

 

The alternative reactions a customer displays, following an
out—of-stock experience, have either one, or both, primary consequences
for a retailer: there could be a monetary repercussion, as well as an
effect on the customer's perception of the store. The former can be
of a short or a long term nature depending on whether the customer
buys the desired item elsewhere only at that time or switches patronage
permanently. The extent to which the image of the store is affected
by the stockout experience influences the long versus short run
monetary loss to the store (Lusch, 1982).

In any case, it is obvious that some monetary effects result from
a stockout situation. The effect might be positive if the customer
switches to a higher margin item within the store, or might be
negative if she decides to buy the item elsewhere as the margin on
the out-of-stock item is foregone. The actual degree of monetary
effect, however, is not the focus of this study.

The dynamic nature of the image development process has been
documented frequently in the literature. For example, Kunkel and
Berry (1968) concluded that retail store image is the total

conceptualized or expected reinforcement that a person associates

58

with shopping at a particular store. Thus, image is constantly affected

by positive and negative experiences.

Research Purpose

The model in Figure 6 leaves several questions which are not or not
sufficiently dealt with in the literature. Therefore, the purpose of
this research is to specifically investigate four questions:

1. How do customers respond to product unavailability in a
fashion retail store?

2. What factors affect customer responses to product
unavailability in a fashion retail store?

3. What is the influence of product unavailability on
the customer's image of fashion retail stores?

4. What is the influence of store image on the customer's
responses to stockouts in fashion retail stores?

In terms of the model, the first area of investigation involves
the determination of how customers respond when an item is not avail-
able at the time it is desired. The distinguishing characteristic here,
and for all four questions, is that the concern is with fashion
merchandising, an area heretofore not studied in a similar manner.

The second question deals with the way in which situational variables,
such as demographics, product involved, etc., affect customer response
to out-of-stock conditions. The third and fourth questions deal with
product unavailability and its relation to the image of the store:
whether product unavailability affects store image and whether prior
store image affects the manner in which a customer responds to product

unavailability.

59

Hypotheses

Buying an alternative to the out-of—stock item within the store,
as deemed favorable by Lusch (1982), is one possible reaction by the
shopper. It is riskier for the retailer if the shopper is willing to
wait ("questionable"), but for a customer to shop elsewhere is the
most negative of the three categories of reactions ("unfavorable").
The importance of these risks led to the following hypothesis:

H1: Customer responses to stockouts in fashion merchandising

are primarily characterized by exit rather than switching

behavior or by purchase postponement.
Exit behavior in this context refers to a customer leaving the store
without putchasing anything or even consciously postponing the purchase
of the out-of-stock item. From the fashion merchandising literature
there is an a priori expectation that the customer is inclined to shop
elsewhere when she is faced with an out-of-stock situation (e.g.,
Troxell and Stone, 1981; Wingate and Friedlander, 1978; King, 1963).

The conclusion reached by Bellenger et al. (1977) with regard to
the importance of shopping motives in the development of store image
and store loyalty, gave rise to the following hypothesis:

H2: Customer reactions to stockouts are affected by the
intentions behind the attempted purchase.

Ideally, this hypothesis is accepted so as to give a retailer an idea
on what influences stockout reactions. It would allow his/her, in a
sales seminar to stress empathy, to make an effort to find out what
a customer is particularly interested in, to determine if the customer
wants to be left alone while shopping, etc.

Knowing a little more about what influences customer reactions

to stockout helps reduce the uncertainty in the retailers assortment

60

planning as retailers are constantly forced to adapt to varying demands
of prospective customers (e.g., Prasad, 1975). Much of this adaptation
is affected by the customer's demographic characteristics. In the
literature there are many examples of studies dealing with such
descriptors starting with Martineau (1958). Empirical studies, such

as the one Nielsen performed for the Progressive Grocer (1969) continue

 

to outline the importance of demographics. This lead to the hypothesis
that:
H3: Demographic characteristics of shoppers, such as age,
income, level of education, number of children, affect
customers' responses to stockouts.
Similarly, many other studies (e.g., Schiffman, Dash and Dillon,
1977; Bearden, 1977) investigated the effects of other variables,
such as locational convenience, on store patronage. Thus, it can also

be hypothesized that:

H4: Situational variables, such as distance traveled, affect
customers' responses to out-of-stock situations.

Whatever the result of testing the above two hypotheses, the key for
the retailer is to reduce the uncertainty surrounding the occurrence
of stockouts, a phenomenon that has always been treated as a
necessary evil.

The a priori relevance of the variables referred to in hypotheses
three and four is depicted in Figure 7. With respect to the question
on the number of children under 12 still at home, the cut-off age of
12 was chosen because, until that time, the decision maker on what is
fashion, though being influenced, and the financier of the desired

purchase is still one and the same person, yet not the child. Beyond

61

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62

that age, it is presumed that there is growing financial "independence"
allowing the child to express its own fashion tastes more significantly.
Image implications of stockouts have been discussed in several studies
(e.g., Lesser, 1981; Zinszer and Lesser, 1980). As fashion shopping
is considered riskier in "psychological" terms than, for example,
grocery shopping (Tigert and Arnold, 1981), we can conclude that store
images are very important in fashion shopping. Hisrich, Dornoff and
Kernan (1972, p. 459) showed that "the higher the risk, the more
important the store choice is as a surrogate for not knowing much
about the product."

The contention in this study is that a rare experience with a
stockout has relatively little influence on the image of the store,
given that high-fashion retailers present the strongest overall image
(Rich and Portis, 1964). Thus, it becomes importance, particularly
given the relation between store loyalty and consumer store images
(e.g., Lessig, 1973), to test the following hypotheses:

H5: When a customer is faced with an out-of—stock situation,

there will be a negative effect on the customer's
perception of the store.

H6: Customer responses to stockouts are affected by the image
of the store which the customer held prior to the stockout
experience.

Preferably, hypothesis five is rejected; however, even if it is not
rejected, as is expected, it will provide a better perspective of
the risk involved in merchandise assortment decisions and the
associated training and instructions for the store's buyers. Also,

a better perspective will force a reevaluation of the focus on

overstocking issues as proposed by Ammer (1973).

63

The acceptance of hypothesis six will guide a retailer's marketing
efforts towards a strengthening of the store's image. With a strong
positive store image, it could act as a buffer, taking some pressure
off the difficult assortment decisions. Also, from a competitive
standpoint, image sharpening, repositioning, etc. (e.g., Ring, 1979)
become very important issues.

The basis for the above contention on the (lack of) impact of
stockouts on the image of fashion stores, lies in the existence of the
many alternatives for the retailer to mitigate the effect of the

negative stockout reaction (e.g., Progressive Grocer, 1969). With

 

statements like "we could only buy so many of this popular model",

"the manufacturer does not make them any more", "new fashions are
coming in", the consumer may be more willing to accept a stockout
without becoming annoyed. However, for a retailer to be able to use
these mitigating statements, a customer has to check with store
personnel when they cannot find what they are looking for. Hirschman's
(1970) distinction between "exit" and "voice" behavior needs to be
explored, leading to the following hypothesis:

H7: In fashion shopping, customer responses to stockouts are
characterized by "exit" rather than by "voice" behavior.

Ideally this hypothesis is rejected as retailers need to have
customers who cannot find a desired item identify themselves.
Therefore, the result of this hypothesis test should lead to an
enhancement of the atmosphere in the store to elicit "voice"

behavior.

64

Measurement

The measuring instrument used in obtaining answers to test the
research hypotheses was a questionnaire. One thousand questionnaires
were mailed to a systematic random sample of credit card customers of
Streets', Inc., a chain of high fashion outlets of women's and
children's clothing in Oklahoma City, Oklahoma. A total of 250 usable
responses was desired, given the requirements of some of the statistical
techniques to be used in analyzing the data.

Many factors particular to the sampling selection process can
influence the measurement results. According to Schiffman, Dash and
Dillon (1977) these factors are more likely to confound matters than
the research instrument:

it is more likely that any unintentional variation

in findings [in prior image studies] are influenced by

the definition of the sample (p. 4).

In this particular study it is not the objective to measure image
in an absolute sense. Rather, the intention is to measure relative
changes among components of the image construct. These components
have been identified in the literature and include location, advertising,
interior design, other types of customers, merchandise aspects, sales
staff related factors, store services, etc. (see Lundquist, 1974-1975).
As Hansen and Deutscher (1977—1978, p. 61) observed, "the manager
wants to know: (a) how to interpret the results . . . and (b) what
strategic changes he should make based upon the results."

The respondents were informed of the purpose of the study--to
allow the store to provide customers a more complete assortment.

However, they were not told how names were drawn so as to protect

65

the privacy implication of credit card information. Also, the
researcher, and not the store, was identified as the primary source
of the study. A copy of the cover letter for the questionnaire can
be found in Appendix B.

With regard to the specific store chain, Streets' is a retailer
of women's fashion apparel in the central Oklahoma area. The chain
consists of ten outlets in the higher income shopping locations,
each with an area of approximately 10,000-15,000 square feet. Credit
card customers of this retailer are women who can be expected to be
fashion conscious meeting the classification criteria by Troxell and
Stone (1981). Demographic data on the stores' trading areas are
provided in Appendix A.

The central element of the methodology was an experimental design
involving two scenarios. Several reasons exist for the approach. The
key area of focus in this part of the research was to measure how the
customer's prior impression of the "personality" of the store influences
the response to the out-of—stock situation. In order to accurately
measure this prior image, it is not valid to ask the customer's
opinion about an existing store and then ask her how she reacted at
the thmashe could not find what she was looking for in that store.

In that case, the out-of-stock experience has already become part of
the store image she reported on earlier.

To request that the consumer identify whether--to what extent——
the stockout experience has influenced her opinion of the store,
invokes too much confounding by variables such as intermediate

positive or negative experiences, discussions with friends, store

66

management's efforts to mitigate the seriousness of the customer's
reactions, etc.

Because of the above measurement problems, a more reliable alter-
native to determine image prior to the experience was used to put the
customer in a new situation. Being "new" in the area, she would receive
information about the shopping alternative through advertising by the
store, as well as word-of-mouth about the store, its location, clientele,
sales people, etc. Asking for her opinion of the described store also
allowed for better control over how much time has elapsed between the
forming of the store opinion and the "actual" stockout experience.
Using this approach avoids the problem that a time factor might affect
the response of the customer to the situation.

Other projective techniques used to measure someone's feelings
and beliefs, such as Thematic Apperception Tests, Sentence Completion,
etc., were eliminated as alternative measurement techniques due to the
length of time the respondent is exposed to the picture, sentence, etc.
Each of these techniques requires an immediate response (Kinnear and
Taylor, 1979), which is impossible to control in a mail questionnaire.

The scenarios were used in the following way. Half of the
respondents was exposed to a basic store description (Scenario A) in
which they were told about various elements, such as demographics of
the store's trading area, size of the store, interior design, etc.

The description of the store matched as closely as possible the actual
environment surrounding a high fashion store. However, a hypothetical
name was used to avoid obvious identification with a store the

respondent might be familiar with.

67

The other half of the respondents was exposed to another basic
store description (Scenario B). This time the environment sketched
corresponded to a store that projected a distinctly different image,
which also provided an opportunity to test the validity of the
scenarios. Pretesting verified the dissimilarity in store images
projected.

After being exposed to their respective scenarios, one-third of
each group (A I vs. B I) received no further information, but was asked
for an opinion of the store described to them, as well as to the likeli-
hood of their shopping there. The second subgroup, of equal size
(A II vs. B II), was exposed to a situation in which they had a positive
experience in that they found what they were looking for. Then they,
too, were asked their opinion of the store and desire to shop there.
The last subgroup (A III vs. B III) was asked the same two questions
about the store, but this time following a stockout experience.
Respondents were randomly assigned to the respective scenarios. A
copy of the particular scenarios can be found in Appendix C.

According to Kinnear and Taylor (1979) a Posttest-Only Control
Group Experimental Design is created as depicted in Figure 8. In this
type of true experimental design, with randomized assignment of
respondents to the different scenarios and different groups within
each scenario, "the extraneous variables have been controlled and
we have a nonconfounded measure of the treatment effect" (Kinnear and

Taylor, 1979, p. 343).

68

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69
Methods of Analysis

Following the format as described above, makes several analyses
possible. By ensuring that the scenarios are distinctly different,
any differences in responses to the stockout situation between scenarios
is attributed to the differing prior image. Within each scenario,
having three groups of respondents undergo three different treatments
allows for a check on the validity of the scenario as a methodological
tool. Thus, when statistically significant differences occur between
customer responses as well as between customer perceptions of the stores
as described to them, they can be attributed to the various treatments,
one of which is the stockout experience.

In this experimental design, two treatments were used (positive
and negative experiences) as well as a control "treatment" (no specific
experience). Effects within each of the two scenarios were searched
for, as well as effects between them. In this manner, analysis of
variance was a reliable method of analysis with alternative reactions
as dependent variables, including the desire to shop. Consequently,
hypotheses four and five were tested using the above approach.

Determining actual customer reactions to a stockout situation is
an ex post facto measurement and the results, as stated above,
constituted dependent variables in the analyses to be performend.

With the intentions behind the attempted purchase, demographic
characteristics of shoppers and other situational variables as
independent, input variables, ANOVA was, again, a simple and reliable

method of analysis used to test hypotheses two, three, and six.

70

Customers displaying a tendency for "voice" behavior are the ones
retailers can easily identify and deal with accordingly. "Exit"
behavior is displayed by people who do not ask a sales person when they
cannot find an item and are, therefore, more difficult to identify.
Given the responses to question 11, a comparison of proportions of

each behavior type is the appropriate test for hypothesis seven.

Questionnaire Development

In developing the questionnaire, two pretests were conducted.

The first pretest involved a group of 90 students and determined
whether any logical problems existed with the measuring instrument
itself. Based on the responses, the questionnaire was updated and
subsequently administered to ten women who were considered similar to
the projected sample subjects. The questionnaire was amended as a
result of these responses and a copy of the final result is provided
in Appendix D.

The first two questions, on perception of the store and likelihood
of shopping there, were designed to measure reactions to the hypothe-
tical store as described. In selecting store image components, it
should be stressed that the intent in this research was not its
identification in an absolute sense. Rather the purpose was to identify
certain key ingredients that received a high degree of concensus in
the literature, to create a composite that, when used to measure store
image before and after, allowed relevant conclusions to be drawn as
to the effect(s) the change agent had on image of the store in which
the change agent operated. Given criticism regarding selection of

bi-polar attributes (e.g, Engel, Kollat and Blackwell, 1974) and

71

with respect to the method itself (Kunkel and Berry, 1968), this
appears to be a relevant assumption.

There is an agreement that store image is a composite of dimensions
that consumers perceive as the store (e.g., Dalrymple, 1969; Berry,
1969; Marks, 1976; Bellenger, 1976). The assumption can be made then,
too, that given the same geographical area (see Hirschman et al., 1978)
one only needs a certain composite stressing an availability factor
and a few generally acceptable ingredients to measure effects on image.
In other words, using the same composite before and after an incident
believed to affect image, reliably measures effects of that incident
on image regardless of the initial composite being the most accurate
measure of the absolute image.

In the construction of the scenarios, generally recognized image
components such as locational convenience, advertising, store atmo-
sphere (e.g., Prasad, 1972) were used to describe the two different
stores. Other components, fashionability, price level, width of
assortment, helpfulness of sales people, were used in the measurement
of differences between the images projected in the scenarios as
perceived by the respondents in the study. "Will (not) have what I
want" was a measure of expectation and therefore was considered to be
related to the consistency dimension of an assortment. Store policies
on refunds and returns were identified by, among others, Tigert and
Arnold (1981) as store service elements and formed the last two on
the seven attribute image scale.

The question on "likelihood of shopping there" was inserted to
obtain a composite measure of image which was considered important in

view of Bearden's (1977, p. 15) insistence that "store image is a

72

comprehensive concept that reflects overall consumer attitudes toward
individual stores." The impact of store image as a composite was then
looked at versus image as a set of individual store attributes as most
studies reported (see e.g., Alpert, 1980; Arnold, Ma and Tigert, 1978).
The respondents who constituted groups A I and B I answered the
first two questions only. Respondents in groups A II and B II were
asked their perception of the store and the likelihood to return there.
In addition to these same questions, groups A III and B III were asked
to respond to a question on how they would respond in the out—of-stock
situation. Alternative reactions to the latter question emerged from
the pretesting phase. For actions regarding the clothing item, a skirt,
there are three alternatives: the customer could buy it, not buy it or
ask for it to be held for her. Given these three, there are two
possibilities with regards to a matching blouse. The blouse could be
either ordered or not ordered and looked for elsewhere. This resulted

in the six possible combinations depicted in Figure 9.

Skirt

 

Buy Do Not Buy rHold

 

Order

 

Blouse
Do Not Order

 

 

Figure 9. Alternative Reactions to the Stockout in the
Scenarios

73

The pretest indicated that if there was an interest in the skirt/
blouse combination, there would at least be a desire to ask for the
skirt to be held, rendering the "do not buy/do not order" cell
irrelevant. Instead, an alternative emerged in that a decision to
"hold/buy" the skirt is affected by whether the blouse is already on
order.

Following the questions on the hypothetical situation, all respon-
dents were exposed to a set of questions in reference to an actual
stockout experience they had at Streets'. However, it was important
to clear the mind of the respondent at this point before asking her to
respond, so as not to confuse the scenario with the actual situation.
At the same time, an appreciation was expressed to increase the chance
that the respondent would complete a comparatively lengthy questionnaire.
Furthermore, learning which of the ten possible outlets the respondent
referred to, allowed a better interpretation of the results given the
differences in physical location, demographic make-up of the trading
area, accessability, etc. According to Marcus (1972, p. 42), such
variables do confound image measurement, "variations in images of three
branches of May Co. department stores . . . stemmed from age of the
stores, differences in environment, and variation in company policy
among stores."

Question six, measuring the perception of the Streets' store the
respondent shops at, was kept consistent with previous store perception
questions as to the image scale used. Question seven, besides for
purposes of ensuring the cooperation of Streets' management, and in

combination with question six, was primarily included to assure a

74

disconnection in the respondent's mind between the previous and the
following set of questions.

Questions eight through 18 were specifically designed to get
the respondent's total reaction to the actual stockout experience.
Included in this set were inquiries into the purpose behind the
shopping trip, the role played by the sales person and the customer's
perception of what should be done to correct the particular situation.
Particularly, the questions on what actions would bring a very annoyed
customer back and what actions a retailer could take in this matter,
were included to comply with the managerial orientation of this
research. Demographic and situational variables were asked in

questions 19 through 26.

CHAPTER IV

DATA ANALYSIS AND RESULTS

Introduction

The demographic characteristics of the sample are discussed first
and compared to the demographics of the areas from which the sample
was drawn. Subsequently, reliabilities are reported on for the
constructs that were used, for example, image. Measurement results
are then discussed along with conclusions regarding the hypotheses and

factors which affected this research effort.

Sample Characteristics

The sample of 1006 customers responded with 264 usable returns,
a response rate slightly over 26%. Demographic characteristics of
this sample can be found in Appendix E.

A comparison of demographics as previously known about the areas
in which the stores are located (Appendix A), and those obtained
through the questionnaire (see Appendix E), shows that there were
substantial differences as addressed below. These differences were
expected as the sample was drawn from a population of active charge
card holders from a store chain that is known for merchandise in higher
price ranges. The fact that charge card privileges were awarded,
further explains why the sample was not representative of the store
area's general population (Bonk, 1975; Hirschman, 1979).

Other reasons for differences exist. An important reason was that
the sample was not drawn to be representative of the trading areas.

Even though respondents were randomly selected, the population they

75

76

were drawn from-—active charge card holders--cannot be considered
representative of the total clientele of the individual stores,
especially, since each store's trading area was not proportionally
represented in the drawing process for the sample. Based on the
question of which Streets' store was the shopper's favorite, only one
respondent in the sample preferred the Sooner Fashion Mall in Norman,
a suburb of Oklahoma City, and only four considered the Rockwell Plaza
store their favorite. Consequently, these two stores were left out of
the general comparison on demographics.

Differences between sample demographics and previously known
demographics, particularly with regard to age, existed primarily
because the data from the Continuing Consumer Audit (CCA) were based
on the age of the head of the household which may or may not be the
same as that of the respondent to the questionnaire. Differences in
the measurement categories pertaining to education, presence of young
children and income, were also responsible for deviations. The latter,
for example, was measured by CCA in category sizes of $10,000, $5,000,
$5,000, $10,000, respectively, in addition to a category for those
earnings over $30,000. This latter category proved to be the one with
the highest frequency among respondents in the sample, which featured
categories of $10,000 (see Appendix E).

Even though questions related to the demographics 0f the sample
were not designed according to the limited data that was available on
the stores' trading areas, some particular differences can be pointed
out. In the sample, most respondents were older (> 45 years), had a
higher income, had no small children at home, had higher education

levels and were either employed or already retired as can be deducted

77

from the higher age representation in the sample. Also, most of the
respondents were married and were long—time Oklahoma City residents.
Due to the existence of ten stores in the "prime" locations, distance
from a Streets' store in time was rarely more than 15 minutes (see
Appendix E).

No significant differences were found between demographics of the

respondents to the individual scenarios (Table 1).
Scenario Reliability

"Because measurement error is an important issue in the use of any
measurement method, investigation of reliability should be made when new
measures are developed" (Nunnally, 1967, p. 210). To determine the
internal consistency, Cronbach's coefficient alpha was calculated not
only per scenario--A I, A II,.A III,B I, B II, B III--but also per set
of "positive" (A II + B II), "negative" (A III + B III), and "no
experience" (A I + B I) scenarios. Furthermore, alpha was calculated
for the two basic scenarios, A and B. The results are presented in
Table 2. Alpha was chosen here as it "provides a good estimate of
reliability since the major source of measurement error is because
of the sampling content" (Nunnally, 1967, p. 211).

Clearly, scenario B showed a higher alpha than scenario A, but with
the lowest individual scenario showing an alpha of .67, we can say that
all of the scenarios were reliable instruments.

For the scenario as a whole, an alpha of .85 was calculated
(Table 3). By contrast, alpha was also calculated for the same scale,
which was used to measure the image of the actual store. The resulting

alpha was much lower: .69. Interestingly, the analysis showed that

78

 

 

Table 1. A. Comparison of Demographic Characteristics by Scenario
Using ANOVA
Sum of Mean F Sign.
Source of Variation D.F. Squares Squares Prob of F

Age
Type of Experience 2 5.94 2.97 .84 .44
Store Type 1 3.68 3.68 1.04 .31
2-Way Interaction 2 .81 .41 .11 .89
Explained Variance 5 10.23 2.06 .58 .72
Residual 258 916.41 3.55
Total 263 926.64 3.52
Employment
Type of Experience 2 3.19 1.60 .89 .41
Store Type 1 1.50 1.50 .83 .36
2-Way Interaction 2 3.93 1.97 1.09 .34
Explained Variance 5 8.52 1.71 .95 .45
Residual 258 465.01 1.80
Total 263 473.53 1.80
Education
Type of Experience 2 .78 .39 .22 .80
Store Type 1 .05 .05 .03 .87
2-Way Interaction 2 17.92 8.96 5.13 .01
Explained Variance 5 18.75 3.75 2.15 .06
Residual 2 8 450.53 1.75
Total 263 469.28 1.78
Distance from Store
Type of Experience 2 4.05 2.03 1.00 .36
Store Type 1 1.86 1.86 1.03 .33
2-Way Interaction 2 1.27 .64 .32 .72
Explained Variance 5 7.18 1.43 .73 .60
Residual 258 507.50 1.97
Total 263 514.68 1.96

79

Table 1. A. Continued

 

 

Sum of Mean F Sign.
Source of Variation D.F. Squares Squares Prob of F

e. Length of Time in OKC
Type of Experience 2 11.72 5.86 1.87 .14
Store Type 1 1.10 1.10 2.56 .49
2-Way Interaction 2 2.38 1.19 .52 .60
Explained Variance 5 15.20 3.05 1.33 .25
Residual 258 590.06 2.29
Total 263 605.26 2.30

f. Marital Status
Type of Experience 2 1.20 .60 .68 .51
Store Type 1 .15 .15 .17 .68
2-Way Interaction 2 1.83 .92 1.04 .36
Explained Variance 5 3.18 .63 72 61
Residual 2 7 226.80 .88
Total 262 229.98 .88

g. Children < 12 at Home
Type of Experience 2 .01 .01 .01 .99
Store Type 1 .06 .06 .09 .76
2—Way Interaction 2 1.35 .67 1.01 .36
Explained Variance 5 1.42 .28 43 83
Residual 2 7 171.01 .67
Total 262 172.43 .66

h. Income
Type of Experience 2 5.29 2.64 .40 .50
Store Type 1 4.75 4.75 1.25 .27
2-Way Interaction 2 6.38 3.19 .84 .43
Explained Variance 5 16.32 3.27 .86 .51
Residual 2 7 977.60 3.80

Total 262 993.92 3.79

Table 1. B.

80

Crosstabulation of Education with Scenario Type

 

Scenario‘Type

 

 

 

Education Level A I A II A III Total
*

High School or Less 13 7 -12 79
(11.4) (12.1) (11.8) ( 32.6%)

Some College 11 18 13 94
(13.6) (14.4) (14.0) ( 38.8%)

College Degree 6 5 4 33
( 4.8) ( 5.0) ( 4.9) ( 13.6%)

Graduate Training 5 7 7 36
( 5.2) ( 5.5) ( 5.4) ( 14.9)

Total 35 37 36 242
(14.5%) (15.3%) (14.9%) (100.0%)
B I B II B III Total

High School or Less 9 21 17 79
(14.0) (14.0) (15.7) ( 32.6%)

Some College 20 17 15 94
(16.7) (16.7) (18.6) ( 38.8%)

College Degree 7 3 8 33
( 5.9) ( 5.9) ( 6.5) ( 13.6%)

Graduate Training 7 2 8 36
( 6.4) ( 6.4) ( 7.1) ( 14.9%)

Total 43 43 48 242
(17.8%) (17.8%) (19.8%) (100.0%)

Chi—Square = 17.11 Degrees of Freedom = 15

Significance = .31 Cells with Exp. Freq. < 5 = 8.3%

 

*
Absolute frequency
(expected frequency).

81

Table 2. Reliability Coefficients for Individual Scenarios

 

 

Coefficient
Scenario Alpha N
A I .78 41
A II .70 39
A III .67 43
B I .80 44
B II .90 46
B III .88 51
Average Random Error .205 264
A I + B I .81 85
A II + B II .88 85
A III + B III .86 94
Average Random Error .15 264
A .73 123
B .87 141
Average Random Error .199 264

 

82

the price component included in the "image" construct turned out to be
the greatest impediment to a higher alpha level for any of the "images"
measured while using the identical scale. For example, without "price"
the alpha coefficient for the image measurement scale for the actual

store would have been higher: .73 (Table 3).

Table 3. Image Measurement Scale Reliability Coefficient and the Effect
of the Price Component

 

Alpha if Item

 

Deleted N Alpha
A. Hypothetical Store
Fashionability .82 264 .85
Price Level .87 !
Assortment Width .83
Sales People's Courtesy .82
Availability Expectation .82
Refund Policy .82
Return Policy .82
B. Overall Streets' Image
Fashionability .62 264 .69
Price Level .73 !
Assortment Width .59
Sales People's Courtesy .66
Availability Expectation .61
Refund Policy .66
Return Policy .68
C. Downtown Store
Fashionability .62 28 .68
Price Level . .70 1
Assortment Width .58
Sales People's Courtesy .58
Availability Expectation .58
Refund Policy .67

Return Policy .72

Table 3. Continued

83

 

Alpha if Item

 

Deleted N Alpha
D. Mayfair
Fashionability .72 14 .78
Price Level .83 1
Assortment Width .77
Sales People's Courtesy .70
Availability Expectation .73
Refund Policy .73
Return Policy .73
E. Penn Square
Fashionability .32 13 .50
Price Level .79 !
Assortment Width .22
Sales People's Courtesy .41
Availability Expectation .46
Refund Policy .29
Return Policy .33
F. Reding
Fashionability .64 81 .70
Price Level .77 1
Assortment Width .57
Sales People's Courtesy .66
Availability Expectation .66
Refund Policy .65
Return Policy .68
G. Windsor Hills
Fashionability .61 19 .63
Price Level .69 !
Assortment Width .54
Sales People's Courtesy .55
Availability Expectation .58
Refund Policy .57
Return Policy .61

 

84

Calculating the reliability coefficient for the image measurement
scale for each individual store further reinforced this finding with
regard to the impact of price on image measurement (Table 3).

Factor analyzing the image determinants used further illustrated
the "independence" of price level perception in the measurement of
image. Other than price, a factor relating to the merchandise
selection and one pertaining to store service elements stood out as

being very important (Table 4).

*
Table 4. Factor Analysis of Image Measurement Scale Components
(for the Actual Store)

 

 

Component Factor 1 Factor 2
Fashionability .84 .12
Assortment Width .72 .40
"Always has what I need" .65 .43
Price Level .56 -.48
Refund Policy .12 .70
Return Policy .12 .65
Sales People Courtesy .32 .51

Communality Factor Eigenvalue Pct of Var

 

Assortment Width .71 1 2.65 44.2%
Fashionability Level .73 2 1.05 17.5%

 

*
Varimax rotation.

As a further assurance of reliability, the split-half method was
also applied. With this method scale components were divided in half

and scores on the two half-scales were correlated. Since the scale in

85

this research had seven components, the two part scales had four and
three components respectively.

The primary reason for including this method was that different
time periods may have elapsed in the forming of the store image by the
respondent. This could be true in the case of the store in the
scenario, but particularly for the store where the actual experience
took place. According to Nunnally (1967, p. 214), the split-half method
takes this potentially important factor into consideration. Results

of this method's application can be found in Table 5.

Table 5. Split-Half Reliability Coefficients

 

 

ALPHA 1 ALPHA 2 Correlation
4 items 3 items Alpha 1 and 2 N
A. Hypothetical Store .73 .81 .70 264
Actual Store .56 .56 .47 264
B. A I .41 .75 .61 41
A II .54 .70 .54 39
A III .44 .64 .47 43
B I .64 .75 .62 44
B II .79 .89 .79 46
B III .75 .83 .83 51
C. A I + B I .65 .80 .62 85
A II + B II .79 .83 .73 85
A III + B III .73 .79 .86 94
D. A .44 .74 .55 123
B .73 .83 .76 141

 

Again, as was the case when coefficient alpha was used, the

scenarios showed a higher reliability when measuring image of the

hypothetical store than the measurement of the actual Streets' store

image (Table 5A). In any case, however, the basis for a more reliable

data analysis was formed given the emphasis on and results of the above

tests.

Measurement:

Dependent Variables

In scenarios A III and B III, alternative responses to a stockout

experience in the hypothetical situation were measured.

Analysis showed (Table 6) that most people would be apt to purchase

neither the skirt nor the blouse, or buy only the skirt and then leave

the store. The next most likely reaction was to buy the skirt if the

blouse is on order. "Asking for the skirt to be held while an alter—

native to the blouse is being searched for elsewhere" was the next

likely reaction, closely followed by "buying the skirt and asking for

the blouse to be ordered."

The least likely reaction by far was that

of asking for the skirt to be held while a blouse is put on order.

Table 6. Likelihood of Alternative Responses to the Hypothetical

Stockout Experience

 

 

Std. Mentioned as a
Alternative Mean Dev. Likely Action
Buy skirt, then leave 2.38 1.69 46.8%
Forget both 2.47 1.52 45.2
Buy skirt, if on order 2.72 1.87 39.7
Hold skirt, search elsewhere 2.85 1.81 34.6
Buy skirt, order blouse 2.97 1.83 31.3
Hold skirt, order blouse 3.17 1.82 28.4

 

87

For purposes of analysis, alternative stockout reactions to an
actual experience were combined into a category of "buying something
else within" (switching behavior). Another category was made of
respondents who left and bought what they were looking for elsewhere
(exit behavior). A third category consisted of respondents who were
willing to wait (postponement). In testing hypotheses two, three, and
four, these categories formed the dependent variable. With the above
mentioned three categories for responses to question 11, cross-
tabulations were performed on the demographic data, due to the

categorical nature of that data.

Hypothesis Testing

Hypothesis One

 

Of all the respondents, 65.4% left the store upon not being able
to find what they were looking for. Respondents willing to switch
wiflmhlthersame store and those willing to postpone the purchase made
up 21 and 13.6%, respectively. A chi—square test of uniformity showed
in a statistically very significant manner that exiting behavior
dominated the alternative reactions to an actual stockout situation
(Table 7). This finding tends to be confirmed by looking at Table 6.
Those reactions involving leaving the store upon not finding the desired
item in stock are the first ("buy skirt and leave"), second ("forget
both and leave") and fourth ("hold skirt and search elsewhere") most
likely to be displayed. As a result, hypothesis one, as stated, was

accepted.

88

Table 7. Alternative Reactions to an Actual Stockout

 

 

Absolute Relative Expected

Reaction Frequency Frequency Frequency
Switching within the same store 51 21.0% 81
Leaving when item not in stock 159 65.4 81
Postponing the purchase 33 13.6 81
Total 243 100.0% 243

*
Chi—Square statistic = 1474 , 2 degrees of freedom

 

*
This is significant at the p < .0001 level.

Hypothesis Two

 

Intentions behind the attempted purchase, as measured through
the question "for what reason did you initially go to the store,"
appeared to have a statistically significant relationship with customer
stockout responses (p < .05). Customers shopping for a particular
item showed a higher frequency of buying something else within the
same store than was expected. When looking for several items, a
customer was much more likely to shop elsewhere when a stockout was
experienced. Further, if a customer was just browsing, whether alone
or with a companion, she was much less willing to wait than was
expected. Yet she was also more willing to buy something else in the
store (Table 8).

Another way of looking at these relationships is that of all the
respondents who bought something else inside, those looking for
several items constituted a substantially lower number than was
expected. In conclusion, at the .05 level of significance, hypothesis

two was accepted.

89

Table 8. Crosstabulation of Stockout Responses with Purchase

 

 

 

Intentions
Stockout Responses
Purchase Intentions Switching Exiting Postponing Total
*
To buy a specific item 15 68 11 94
(19.1) (63.1) (11.8) ( 40.7%)
To buy several items 19 33 4 56
(16.0) (37.6) ( 7.0) ( 24.2%)
Just to browse 13 54 14 81
(16.5) (54.4) (10.2) ( 35.1%)
Total 47 155 29 231
(20.3%) (67.1%) (12.6%) (100.0%)
Chi—Square = 10.45 Degrees of Freedom = 4
**
Significance = .03 Cells with Exp. Freq. < 5 = none

 

*
Actual frequency
(expected frequency).

**
Significant at p < .05.

Hypothesis Three

 

As Table 9 shows, demographics were very ineffective in explaining
how a customer responds to a stockout. At p < .05, only age and the
presence of young children showed any statistically significant
relationship. With regard to age, the customer buying something else
within was primarily in the "over 45" category. Apparently, older
people were much less likely to go elsewhere, also a greater number

in this category was willing to wait.

90

The 25-34 and 35—44 groups were more willing to shop elsewhere
upon not being able to find what they were looking for, whereas the
under-25 group was more willing to wait than expected.

Presence of children under 12 had a significant bearing on the
shoppers reaction to a stockout (p < .01). When no children were
present a significant number of customers were more likely to buy
something else within the store or were willing to wait. In conclusion,
25-44 year-old shoppers were more likely to buy elsewhere and so were
shoppers without young children. However, these were the only demo-
graphics of those used that showed a statistically significant effect

on stockout behavior.

Hypothesis Four

 

The brand, style, color, size, or even the price of the product
involved showed no significant relationships with stockout reactions
(Table 10). The same result applied to distance (as measured in time)
from the store. However, the frequency of having a stockout experience
showed a very significant relationship (p < .0005, see Table 10). The
people who "hardly ever" experienced a stockout were much more likely
to shop for something else within the same store or were willing to
wait, and those who experienced it "occasionally" were likely to buy
elsewhere. The degree to which people with many experiences
("frequently") of this nature were likely to buy elsewhere was much
greater than for those who had it happen occasionally. As a result,
it was found that the more frequently a shopper experienced a stockout,

the more likely she was to buy the item elsewhere (Table 10).

91

 

 

 

Table 9. Crosstabulation Analyses Between Stockout Reactions and
Demographic Characteristics
Reactions
Switching Exiting Postponing Total
a. Age Groups
Under 25 2 8 5 15
( 3.1) ( 9.9) ( 2.0) ( 6.8%)
25—34 7 40 5 52
(10.6) (34.4) ( 7.1) ( 23.5%)
35-44 8 42 . 4 54
(11.0) (35.7) ( 7.3) ( 24.4%)
45-54 9 21 6 36
( 7.3) (23.8) ( 4.9) ( 16.3%)
55 and Over 19 35 10 64
(13.0) (42.3) ( 8.7) ( 29.0%)
Total 45 146 30 221
(20.4%) (66.1%) (13.6%) (100%)
Chi-Square = 16.39 Degrees of Freedom = 8
**
Significance = .04 Cells with Exp. Freq. < 5 = 20.0%
b. Employment Status
Unemployed 19 43 10 72
(14.7) (47.5) ( 9.8) ( 32.7%)
Employed 26 102 20 148
(30.3) (97.5) (20.2) ( 67.3%)
Total 45 145 30 220
(20.5%) (65.9%) (13.6%) (100%)
Chi-Square = 2.47 Degrees of Freedom = 2
Significance = .29 Cells with Exp. Freq. < 5 = none
c. Level of Education
High School or 18 43 11 72
less (14.8) (47.3) ( 9.9) (32.9%)

 

 

 

92

 

 

 

 

 

Table 9. Continued
Reactions
Switching Exiting Postponing Total
College 20 81 17 118
(24.2) (77.6) (16.2) (53.9%)
Grad. School 7 20 2 29
( 6.0) (19.1) ( 4.0) (13.2)
Total 45 144 30 219
(20.5%) (65.8%) (13.7%) (100%)
Chi-Square = 3.37 Degrees of Freedom = 4
Significance = .50 Cells with Exp. Freq. < 5 = 11.1%
Time Lived in OKC
< 10 years 6 25 6 37
( 7.5) (24.0) ( 5.5) (17.1%)
> 10 years 38 116 26 180
(36.5) (117.0) (26.5) (82.9%)
Total 44 141 32 217
(20.3%) (65.0%) (14.7%) (100%)
Chi-Square = .47 Degrees of Freedom 2
Significance = .79 Cells with Exp. Freq. < 5 = none
Marital Status
Single 19 40 13 72
(14.6) (46.8) (10.6) (33.2%)
Married 25 101 19 145
(29.4) (94.2) (21.4) (66.8%)
Total 44 141 32 217
(20.3%) (65.0%) (14.7%) (100%)
Chi-Square = 4.26 Degrees of Freedom = 2
Significance = .12 Cells with Exp. Freq. < 5 = none

93

Table 9. Continued

 

 

 

 

 

Reactions
Switching Exiting Postponing Total
f. Children at Home?
None 35 90 28 153
(31.0) (99.4) (22.6) (70.5%)
Yes 9 51 4 64
(13.0) (41.6) ( 9.4) (29.5%)
Total 44 141 32 217
(20.3%) (65.0%) (14.7%) (100%)
Chi-Square = 9.19 Degrees of Freedom = 2
*
Significance = .0101 Cells with Exp. Freq. < 5 = none
g. Level of Income
30,000 or less 21 63 14 98
(19.1) (64.7) (14.3) (47.6%)
30,001-50,000 15 49 13 77
(15.0) (50.8) (11.2) (37.4%)
> 50,000 4 24 3 31
( 6.0) (20.5) ( 4.5) (15.0%)
Total 40 136 30 206
(19.4%) (66.0%) (14.6%) (100%)
Chi—Square = 2.36 Degrees of Freedom = 4
Significance = .67 Cells with Exp. Freq. < 5 = 11.1%

 

*
Actual frequency
(expected frequency).

**
Significant at p < .05.

Table 10.

94

Selected Situational Variables

Crosstabulation Analysis of Stockout Responses with

 

 

 

 

 

Chi-Square = 20.42

***
Significance = .0004

Degrees of Freedom

4

Reactions
Switching Exiting Postponing Total
a. Time Distance from Store
0-5 min. 8 32 5 45
( 9.1) (29.2) ( 6.6) (20.7%)
6—10 min. 15 38 13 66
(13.4) (42.9) ( 9.7) (30.4%)
11-15 min. 14 37 11 62
(12.6) (40.3) ( 9.1) (28.6%)
16-20 min. 4 27 1 32
( 6.5) (20.8) ( 4.7) (14.7%)
> 20 min. 3 7 2 12
( 2.4) ( 7.8) ( 1.8) ( 5.5%)
Total 44 141 32 217
(20.3%) (65.0%) (14.7%) (100%)
Chi-Square = 9.44 Degrees of Freedom
Significance = .31 Cells with Exp. Freq. < 5 = 20.0%
b. Frequency of the Stockout Event
Hardly Ever 22 28 13 63
(13.1) (41.3) ( 8.6) (26.1%)
Occasionally 21 90 18 129
(26.8) (84.6) (17.7) (53.5%)
Frequently 7 40 2 49
(10.2) (32.1) ( 6.7) (20.3%)
Total 50 158 33 241
(20.7%) (65.6%) (13.7%) (100%)

Cells with Exp. Freq. < 5 = none

Table 10. Continued

95

 

 

 

 

Reactions
Switching Exiting Postponing Total
c. Opinion Change?
Yes 2 22 1 25
( 5.2) (16.4) ( 3.4) (10.3%)
No 48 137 32 217
(44.8) (142.6) (29.6) (89.7%)
Total 50 159 33 242
(20.7%) (65.7%) (13.6%) (100%)

Chi-Square = 6.17

***
Significance = .046

Degrees of Freedom = 2

Cells with Exp. Freq. < 5 = 16.7%

 

*
Actual frequency

(expected frequency).

**
Significant at p < .0005.

***
Significant at p < .05.

The conclusion, being in terms of the single item rather than

"items", was reinforced by the statistically significant relationship

(p < .001) between the feelings the shopper had when she learned that

the item was out of stock.

half of them (46%) were looking for a specific item.

Of those who were annoyed by it, almost

More than half

(52%) of those who were not annoyed were just browsing when they had

their out-of-stock experience (Table 11).

96

Table 11. Crosstabulation Analysis of Purchase Intention and Level
of Annoyment

 

 

Purchase Intention Annoyed Not Annoyed Total
Buy a specific item 63 30 93
(53.9) (39.1) (39.1%)
Buy several items 39 18 57
(33.1) (23.9) (23.9%)
Just browsing 36 52 88
(51.0) (37.0) (37.0%)
Total 138 100 238
(58.0%) (42.0%) (100%)
Chi—Square = 16.71 Degrees of Freedom = 2
*
Significance = .0002 Cells with Exp. Freq. < 5 = none

 

*
Actual frequency
(expected frequency).

Thus, it was concluded with regard to hypothesis four, that
frequency of a stockout experience occurring significantly affected
the stockout response, with the higher frequency being very strongly
related to the customer leaving the store and buying somewhere else.

A summary table, involving the variables referred to in testing

the hypotheses three and four, is provided in Table 12.

Hypothesis Five

 

In this study, the hypothesis was tested with two measures, the
first test involving the hypothetical situation presented in the first
part of the questionnaire. The "likelihood of returning to the store"

was used as the dependent variable. Secondly, by using the direct

97

question of "did your opinion of Streets' change due to this experience",
hypothesis five was tested using the actual stockout to which the

customer was asked to refer.

Table 12. Summary Table of Crosstabulations of Stockout Reactions
with Various Demographic and Situational Variables

 

 

Actions by Shoppers 2 Significance % of Cells with
With: X Level Exp. Freq. < 5
*

Age 16.39 .03 20%
Employment Status 2.47 .29 none
Education Level 3.37 .50 11.1%
Years in the City .47 .79 none
Marital Status 4.26 .12 * none
Children < 12 9.20 .0101 none
Income 2.36 .67 11.1%
Time to Get to Store 9.44 .31 * 20%
Frequency of Happening 20.42 .0004* none
Reason for Shopping 10.45 .0335 none

 

*
Actual frequency
(expected frequency).

Using both these measures, hypothesis five was rejected. There
were no statistically significant differences between the people who
had the "negative" shopping experience and those who had the "positive"
one or the ones who had no experience at all with regard to their
likelihood of return (Table 13).

Asking respondents a direct question on their opinion change showed
the following breakdown (Table 14). Twenty-six shoppers (10.2%) said
that their opinion had changed, whereas 221 (85.0%) said the stockout

experience had not affected their opinion. The rest either did not

98

respond (did not report any stockout experiences) or said that the one
experience had not affected their opinion at that time, but it would

change if it were to happen again.

Table 13. Oneway Analysis of Variance: Type of Shopping Experience
and Likelihood of Return Visit

 

 

 

Sum of Mean
Source D.F. Squares Squares F Ratio F Prob.
Between type of experience 2 4.67 2.33 1.63 .20
Within type of experience 261 373.48 1.43
Total 263 378.15

 

Table 14. Opinion Change Due to a Stockout Experience

 

 

Opinion Change? Frequency Percent

Yes 26 10.2%
No 221 87.0
No, but it will next time 7 2.8
Total 254 100.0%

 

It was also found that to a significant extent (p < .0001) an
opinion change was more likely to happen when there was a higher
frequency of stockout situations in the experience of the shopper.
However, opinion change was not significantly related (p < .05) to the
reason why the customer originally went shopping (Table 15). It was

worth noting that a significantly greater percentage of respondents,

Table 15.

99

Situational Variables

Crosstabulation Analysis of Opinion Change with Selected

 

Opinion Change?

 

 

 

 

 

Yes No Total
a. Frequency of Stockout Event
Hardly Ever 2* 66 68
( 7.0) (61.0) (26.9%)
Occasionally 7 127 134
(13.8) (120.2) (53.0%)
Frequently 17 34 51
( 5.2) (45.8) (20.2%)
Total 26 227 253
(10.3%) (89.7%) (100%)
Chi-Square = 37.08 D.F. = 2
**
Significance = .0000 Cells with Exp. Freq. < 5 = none
b. Level of Annoyment
Annoyed 24 119 143
(13.8) (129.2) (57.7%)
Not Annoyed 0 105 105
(10.2) (94.8) (42.3%)
Total 24 224 248
( 9.7%) (90.3%) (10075)
Chi-Square = 17.64 D.F. = 1
**
Significance = .0000 Cells with Exp. Freq. < 5 = none
c. _§pecifics of Item Not Found
Brand 2 10 12
( 1.2) (10.8) ( 4.9%)
Size 4 94 98
( 9.5) (88.5) (39.7%)
Style 16 68 84
( 8.2) (75.8) (34.0%)

100

Table 15. Continued

 

Opinion Change?

 

 

 

Yes No Total
Color 0 25 25

( 2.4) (22.6) (10.1%)
Particular Item 2 26 28

( 2.7) (25.3) (11.3%)
Total 24 223 247

( 9.7%) (90.3%) (100%)
Chi-Square = 15.45 D.F. = 4

*** *****
Significance = .004 Cells with Exp. Freq. < 5 = 30.0%
d. Purchase Intentions

Specific Item 13 86 99

(10.2) (88.8) (39.1%)
Several Items 6 53 59

( 6.1) (52.9) (23.3%)
Browsing 7 88 95

( 9.8) (85.2) (37.5%)
Total 26 227 253

(10.3%) (89.7%) (100%)
Chi-Square = 1.75 D.F. = 2
Significance = .42 Cells with Exp. Freq. < 5 = none

e. Talk with Sales Person About It?

 

Yes 18 95 113
(11.8) (101.2) (45.6%)
No 8 127 135
(14.2) (120.8) (54.4%)
Total 26 222 248
(10.5%) (89.5%) (100%)
Chi-Square = 5.54 D.F. = 1
****

Significance = .02 Cells with Exp. Freq. < 5 = none

101

Table 15. Continued

 

*
Actual frequency
(expected frequency).

** '
At p < .0001.

***
At p < .005.

****
At p < .05.

*****
As this number is higher than the generally accepted criterion

of 20% (Upton, 1978), greater caution is required in interpreting these
results.

who expressed themselves to a salesperson about the event, said that
their opinion of the store was affected (Table 15e).

Interestingly, these was a statistically significant relationship
(p < .05) between what was out of stock and the change of opinion.
Color showed a very low bearing on likelihood of opinion change, but
brand and style were very significant (Table 15c).

A direct reference to consistency of assortment was the question
asked, as part of the image dimension on "will/will not have what I
want." In the context of the scenario, there was a significant
relationship (p < .005) between the level of expectations of finding
what the shopper was looking for and the two scenarios (Table 16).
Also the store in scenario A created much higher levels of expectation
than the scenario B store. Furthermore, it was found that a significant
correlation (p < .001) existed between the likelihood of returning

to the store and the level of expectations (r = .59, see Table 17a).

102

Table 16. Level of Expectations and Scenario Type

 

 

Sum of Mean
Source D.F. Squares Squares F Ratio F Prob.
*
Between Scenarios A and B 1 18.19 18.19 13.25 .0003
Within Scenarios 262 359.80 1.37
Total 263 377.99

 

*
Significant at p < .0005.

Table 17. Crosstabulation Analysis of Levels of Assortment Expectation
with Likelihood of Patronage and Leaving Store Without
Purchase

 

Level of
Expectation 0-25% 26-50% 51-75% 76-100% Total

 

a. Likelihood of Patronage

 

Very High 2 4 5 19 30
( 7.2) ( 9.4) ( 6.6) ( 6.9) .(12.1%)
High 7 9 20 26 62
(14.8) (19.3) (13.6) (14.3) (25.1%)
Medium 13 35 21 11 80
(19.1) (24.9) (17.5) (18.5) (32.4%)
Low 19 25 8 1 53
(12.7) (16.5) (11.6) (12.2) (21.5%)
Very Low 18 4 0 O 22
( 5.3) ( 6.9) ( 4.8) (5.1) ( 8.9%)
Total 59 77 54 57 247
(23.9%) (31.2%) (21.9%) (23.1%) (100%)
Chi-Square = 121.15 D.F. = 12
**
Significance = .0000 Cells with Exp. Freq. < 5 = 5.0%

**
Pearson's R = -.59 Significance = .0000

103

Table 17. Continued

 

Level of
Expectation High Medium Low Total

 

b. Likelihood of "Forget Both" Response

 

High 7 4 10 21
( 9.5) ( 4.3) ( 7.3) (25.0%)
Medium 12 9 17 38
(17.2) ( 7.7) (13.1) (45.2%)
Low 19 4 2 25
(11.3) ( 5.1) ( 8.6) (29.8%)
Total 38 17 29 84
(45.2%) (20.2%) (34.5%) (100%)
Chi-Square = 15.2 D.F. = 4
**
Significance = .004 Cells with Exp. Freq. < 5 = 11.1%

 

*
Absolute frequency
(expected frequency).

**
At p < .0001.

***
At p < .005.

It was also found that the higher the expectations, the more a
respondent was likely to not buy the already found skirt upon not being
able to find the desired blouse, thus indicating a very strong reaction
(Table 17b).

When looking at the actual situation the same pattern developed.
It was desirable to study the actual situation in which a shopper had
experienced a stockout for several reasons. Actual store image has not

only had more time to form, but is also based on a broader customer

104

knowledge as to the actual merchandise carried and the relative interest
in different apparel such as outerwear, underwear, sleepwear, etc.

Expectation levels related very significantly to the actual
response by the customer (Table 18a). The higher the expectations
were of finding what the shopper wanted, the more likely he/she was
to look for an alternative within the same store, or at least postpone
the purchase. A significantly lower than expected number of shoppers
decided to go elsewhere under these conditions. Furthermore, expecta-
tion levels were highly related to the degree of annoyance felt by
the customer (Table 18b). The more she expected to find what she
wanted, the more annoyed she felt upon finding the desired item out
of stock. Of all those customers annoyed by the stockout, 57% had
high expectations of finding what they were looking for. Only 22%
of those annoyed did not have very high expectations.

As was found earlier, the level of annoyance in a stockout situa—
tion affected the way a customer responded to it. Also, being annoyed
was not further influenced by expectations prior to the experience.
However, of those not annoyed, the shopper with the higher expectations

was more likely to leave and buy elsewhere (Table 19).

Hypothesis Six

 

The testing of this hypothesis was more complex. Analysis of
variance of the two relevant individual scenarios (A III and B III)
showed that there was no statistically significant (p < .05)
difference between the two scenarios as to what the respondents

do when faced with a stockout (Table 20).

105

 

 

 

Table 18. Crosstabulation Analysis of Level of Expectations with
Stockout Responses and Level of Annoyment
Level of Switching
Expectation Within Exiting Postponing Total
a. Stockout Responses
*
Very High 13 5 3 21
( 4.4) (13.7) ( 2.9) ( 8.8%)
High 16 41 14 71
(14.9) (46.3) ( 9.8) (29.7%)
Medium 17 80 13 110
(23.0) (71.8) (15.2) (46.0%)
Low 4 30 3 37
( 7.7) (24.2) ( 5.1) (15.5)
Total 50 156 33 239
(20.9%) (65.3%) (13.8%) (100%)
Chi-Square = 31.81 D.F. = 6

**
Significance = .0000

Level of Annoyment

 

Very High

High

Medium

Low

Very Low

Total

Cells with Exp. Freq. < 5 = 16.7%

Annoyed

 

12
(13.8)

35
(43.1)

68
(67.3)

28
(20.1)
( 1.7)

146
(57.5%)

Not Annoyed

 

12
(10.2)

40
(31.9)

49
(49.7)

7
(14.9)

( 1.3)

108
(42.5%)

_l<2£_a_1__

24
( 9.4%)

75
(29.5%)

117
(46.1%)

35
(13.8%)

3
( 1.2%)

254
(100%)

106

Table 18. Continued

 

Chi-Square = 13.64 D.F. = 4

***
Significance = .009 Cells with Exp. Freq. < 5 = 20.0%

 

*
Absolute frequency
(expected frequency).

**
p < .0001.

*** .
p < .01.

Table 19. Three-Way Crosstabulation of Level of Expectations and
Purchase Intentions by Level of Annoyment

 

Stockout Response
Level of Switching
Expectation Within Exiting Postponing Total

 

a. For Respondents Who Were Annoyed

 

High 9* 27 8 44
( 7.5) (31.1) ( 5.3) (31.4%)
Medium 11 48 6 65
(11.1) (46.0) ( 7.9) (46.4%)
Low 4 24 3 31
( 5.3) (21.9) ( 3.8) (22.1%)
Total 24 99 17 140
(17.1%) (70.7%) (12.1%) (100%)
Chi-Square = 3.37 D.F. = 4

Significance = .50 Cells with Exp. Freq. < 5 = 11.1%

107

Table 19. Continued

 

Stockout Response
Level of Switching

Expectation Within Exiting Postponing Total

 

b. For Respondents Who Were Not Annoyed

High 19 19 9 47
(12.0) (27.3) ( 7.7) (48.0%)
Low 6 38 7 45
(13.0) (29.7) ( 8.3) (45.9%)
Total 25 57 16 98
(25.5%) (58.2%) (16.3%) (100%)
Chi-Square = 13.12 D.F. = 2
**
Significance = .0049 Cells with Exp. Freq. < 5 = none

 

*
Absolute frequency
(expected frequency).

**
p < .005.

Table 20.

108

Relationship Between Scenario Type and Stockout Response

 

 

Sum of Mean F F
Source D.F. Squares Squares Ratio Prob.
a. Leave without Buying Skirt or Blouse
Between scenarios A and B 1 6.79 6.79 3.02 .09
Within scenarios 22_ 206.67 2.25
Total 93 213.46
b. Hold Skirt, Look Elsewhere for Blouse
Between scenarios A and B 1 .73 .73 .22 .64
Within scenarios _92 299.41 3.25
Total 93 300.14
c. Buy Skirt, Then Leave Store
Between scenarios A and B 1 1.35 1.35 .48 .49
Within scenarios 22_ 257.29 2.80
Total 93 258.64
d. Buy Skirt, Order Blouse
Between scenarios A and B 1 .09 .09 .03 .87
Within scenarios .92 304.90 3.31
Total 93 304.99
e. If Blouse on Order, Buy Skirt
Between scenarios A and B 1 .17 .17 .05 .83
Within scenarios 92 317.71 3.45

 

 

 

 

 

Total 93 317.88

 

109

Analysis of variance also indicated very clearly that the main
effect of stores, or store A versus store B, significantly affected the
perception of the stores and thus confirmed the pretest results
(Table 21).

At least at the same significance level (p < .01), and even at
p < .05, the variance in store image due to the experience within the
store (positive, negative, or no experience) was not statistically
significant (Table 21).

Another indicator of the difference between scenarios in terms
of the prior image effect on stockout response came from the answers
to question two, or the likelihood with which customers were to return
to the hypothetical store.

It was learned as shown in Figure 10, that the store described
in scenario A bad a higher image level than the store in scenario B.
Results showed (Table 22) that respondents who had a positive shopping
experience under conditions of scenario A, were more likely (p < .05)
to return than the ones who had no particular experience at all given
that scenario. This difference was not significant at that level for
scenario B. For example, the difference in likelihood of returning

for respondents exposed to scenario A I (- )--having no particular

XA I

experience--and A II (R )--positive experience--is -2.37. This

A II
was barely significant at the p < .05 level.

Interestingly, the respondents, with a positive experience under
scenario A (A II respondents), showed the most significant difference
in likelihood of returning when compared to the respondents exposed

to the negative experience under scenario B III (see Table 22).

Furthermore, when comparingtfimalikelihood of returning for respondents

Table 21.

110

Relationship Between Scenarios A and B, Type of Experience,
and Store Perceptions

 

 

 

 

 

 

 

 

Sum of Mean F F
Source of Variance D.F. Squares Squares Ratio Prob.
a. Fashionability Level
Between types of experience 1 .02 .02 .02 .90 *
Between scenarios A and B 1 101.69 101.69 93.46 .000
Within individual scenarios 261 283.99 1.09
Total 263 385.70
b. Price Level
Between types of experience 1 1.87 1.87 1.32 .25 *
Between scenarios A and B 1 79.96 79.96 56.51 .000
Within individual scenarios 261 369.32 1.42
Total 263 451.15
c. Assortment Width
Between types of experience 1 2.26 2.26 1.42 .23 **
Between scenarios A and B 1 15.94 15.94 10.02 .002
Within individual scenarios 261 415.43 1.59
Total 263 433.63
d. Courtesy of Sales People
Between types of experience 1 2.60 2.60 1.48 .23 *
Between scenarios A and B 1 57.23 57.23 32.46 .000
Within individual scenarios 261 460.15 1.76
Total 263 519.98
e. Assortment Expectations
Between types of experience 1 1.19 1.19 .86 .35 *
Between scenarios A and B 1 18.01 18.01 13.10 .000
Within individual scenarios 261 358.79 1.38
Total 263 377.99
f. Refund Policy
Between types of experience 1 1.99 1.99 1.00 .32 *
Between scenarios A and B 1 8.88 8.88 4.45 .036
Within individual scenarios 261 520.67 2.00
Total 263 531.54

**

111

Table 21. Continued

 

 

 

 

Sum of Mean F F
Source of Variance D.F. Squares Squares Ratio Prob.
g. Return Poliey
Between types of experience 1 .34 .34 .20 .66 **
Between scenarios A and B 1 18.86 18.86 10.85 .001
Within individual scenarios 261 453.80 1.74
Total 263 473.00
*
At p < .001.
**
At p < .005.
***
At p < .05.

exposed to a positive experience and for those with no particular
experience at all, given the higher image store, the ones who found
what they were looking for showed a higher propensity to return.

The above finding, with regard to the influence of prior image once

a shopper experiences a stockout, was confirmed by noticing (Table 22)
that there was no significant differences as to the likelihood of
returning to the store in the case of shoppers who had the negative

A III ’ "3 III)'

The differences in likelihood with which respondents returned to

experience under both scenarios (K

the hypothetical store did not significantly depend on the type of
experience the customer had in that store as shown in Table 23.

For example, the mean likelihood of returning to a store in which the
respondent had no experience at all (iNO) differed from the mean
likelihood of returning for a respondent who had a positive experience.
However, at the .05 level (2-tail) it was not a statistically

significant difference.

112

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Table 22.

113

Store and Likelihood of Patronage

Paired T-tests Between the Specific Type of Hypothetical

 

 

Paired Difference T-value Significance
RA 1 - 2A II -2.37 .02*
EA I __'A III -1.26 .21
EA I - in I -.32 .75
”A I — in 11 -.29 .77
RA I - "3 III .43 .67
EA II - RA III 1.29 .20
EA II - in I 2.12 .04
RA 11 - EB II 2.18 .03
i - ' 3.oo .ooa**

A II X3 III

'A 111 - KB I .96 .34
EA 111 - RB II 1.01 .31
RA III )-(3 III 1'85 '07
in I - EB II .04 .97
in I - KB 111 .80 .43
i3 II 7 "3 III '77 '44

 

*
At the p < .05 level (2-tail).

**
At the p < .001 level (2-tail).

114

Table 23. Paired T-tests Between Likelihood of Returning Under
Different Conditions in the Store

 

Paired Difference T-value Significance

 

"no - ipos -l.58 .12
ITINO - film; -.25 .80

xPOS - XNEG 1.42 .16

XA - XB 2.04 .04

 

Given the above findings, insufficient evidence was found to accept

hypothesis six.

Hypothesis Seven

 

The a priori assumption was that the percentage of "exiters" was
equal to the percentage of "voicers" for two reasons. First, there
was no indication found in the literature to lead to a different
assumption. Second, from a statistical perspective, the case of 50/50
provides for the greatest allowance for sampling related variance
(standard error) making it more difficult to make type II errors
(e.g., Bacon, 1974). Here, type II is considered to be the more serious
error. It is, as outlined above, desired to have the customer express
to store personnel that she cannot find what she is looking for.
Erroneously rejecting the hypothesis that most people "exit" rather
than "voice", results in a reduction of the attention paid to creating

an atmosphere in which a customer feels comfortable expressing herself

115

before leaving, and thus the retailer loses valuable input in the
merchandise planning function.

A simple test of proportions tested hypothesis seven (Table 24).
Using an alpha of .05 and a one-tail test-~due to the risk mentioned
in the previous paragraph--this hypothesis was rejected. Unfortunately
for the retailer, however, at least half of the respondents still

displayed this "exit" behavior.

Table 24. Test of Proportions Involving "Exit" versus "Voice"

 

 

Behavior
Type of Absolute Expected Standard Critical
Behavior Frequency Proportions Proportions Deviation Value
Voice 113 .4556 .5000
Exit 135 .5444 .5000 '03'8 “5522
Total 248 1.0000 1.0000

 

Other Important Findings

As shown in Table 25, when the respondent was asked to report on
what would influence her responses to a stockout, the sales person
factor was mentioned the most as being important (71%).

Closely following in importance were how badly they wanted the
item (66%) and the time available for shopping (62%). Also rated as
rather important was the reason for shopping at the time (53%). The
importance of other possible factors dropped rapidly: feelings at
the time (39%), number of occurrences (29%), and being alone or with

others (17%).

116

Table 25. Factors Influential in Determining
Stockout Reactions as Reported on
by Respondents

 

%

 

Considering
it

Factors Mentioned Important
Helpfulness of the sales people 71%
How much the item is desired 66
The time available for shopping 62
The reason for shopping 53
"How I feel at the time" 39
Number of times it has happened 29
Whether alone or with others 17

 

When asked about which factors could bring the annoyed shopper
back, the location of the store stood out as being the most important
reason for returning. Very few were adament about not returning for

any reason (Table 26).

Table 26. Factors Considered Important for an Annoyed
Shopper to Return

 

%

 

Considering
it
Reason for Returning Important
Convenience of location 80.5
Special sales 72.6
Image of the store 70.0
Possession of a store credit card 59.0
Desire to shop around anyway 44.0
A friend's/relative's suggestion 28.5
A manager's personal touch 27.0
Shopping with a friend/relative 20.0

Nothing could bring her back 6.0

 

117

After factor analyzing these "reasons" it became clear that
essentially two main elements were at work (Table 27). Store related
elements of location and "image" formed very significant factors.
Elements related to the individual's psychological and social needs,
such as desire to shop around, friend's suggestion, etc., formed
important factors also, yet they do not appear to be as much under the

direct control of the retailer as the store related factor.

*
Table 27. Factor Analysis of Important Reasons to Return to a Store
After a Stockout Experience There

 

 

 

Reason for Returning Factor 1 Factor 2
Shopping with a friend/relative .77 .24
A manager's personal touch .75 .16
Nothing could bring her back .73 .11
Desire to shop around anyway .64 .30
A friend's/relative's suggestion .61 .43
Convenience of location .12 .84
Image of the store .17 .80
Special sale .36 .53
Possession of a store credit card .48 .53

Eigen- Pct.
Communality, Factor Value of Var.

Special sale .42 1 4.13 45.9%
A friend's/relative's suggestion .55 2 1.02 11.3%

 

*
Varimax rotation.

The respondent was also asked what action they preferred the
retailer to take in out-of—stock instances. The preferences ratings
on alternatives for retailers in shown in the following breakdown in

Table 28.

118

Table 28. Respondent Perceived Alternative Retailer Actions

 

 

Very Much
Alternative Preferred Preferred
Check other Streets' stores 61.2% 30.8%
Call when item is in 43.6 37.2
Check any other location 40.9 39.1
Tell how long it will take 35.0 56.9
Give an acceptable reason 27.8 41.8
Show an acceptable alternative 17.2 41.8

 

Since these alternatives depend on contact with store personnel
there was a high degree of consistency with the above findings. However,
it also put more weight on the results of the testing of hypothesis

seven, which is discussed further in Chapter V.

CHAPTER V

SUMMARY AND CONCLUSIONS

Introduction

In this chapter the research purposes are again addressed,
followed by a summary of the research itself. Conclusions are then

discussed along with implications for future research.

Research Summary

Traditionally, stockouts have been negatively looked upon by
business. According to the literature, the definitions identifying
a stockout all relate to not having normally available stock at the
time a customer wants it. Whether the cause for the stockout was a
mistake in buying plans, errors in stocking, a customer not returning
merchandise to the proper location after examining the item, or theft,
depth of assortment was the critical variable. The question raised by
authors such as Ammer (1974) concerned justifying the amount of
attention being paid to overstocking as a safeguard against under-
stocking. However, if an important factor in assortment planning
is a proper balance between understocking and overstocking, we know
surprisingly little about both sides of the scale, but particularly
the understocking side.

In addition to the above observation, it was noticed that the
definition used in the literature for a stockout only applied to a
logistical perspective. Questions can be asked: What is a situation

called when a shopper asks for an item that is not carried at all?

119

120

Why has the shopper made the effort in some way to find out if the
item is available? Recognizing the importance of this situation, a
strategic view on what the effect is of not carrying what the customer
expects you to carry should definitely be taken into account as well in
assortment planning. Whether the customer expectations are a result
of direct retail management actions, competitor actions or purely
related to consumer ignorance, is not relevant at this point. The

key is that the customer has a negative shopping experience at that
location. As a result, in this research a stockout is defined as a
situation which occurs when a customer is unable to buy a wanted item
due to the unavailability thereof (strategically or logistically)

in that particular outlet.

Strategically speaking, it can be said that it is not profitable
for the retailer to cater to the occasional shopper wanting a certain
item or the retailer may deem that a certain item may not suit his
intended target market. However, it is difficult to make that decision
if we do not know enough about how much it costs to be forced to say
"no" to an inquiring shopper, even if we assume we know exactly how
expensive it is to carry a not so popular item. This research is part

of an effort to shed more light on the merchandise assortment decision

and some of the factors that affect it and are affected by it.
Research Design

As reported in Chapter II, many attempts have been made to answer
the question on how much understocking costs. A major conclusion is

that we cannot tell for certain. But what we can do, is learn more

121

about factors that influence those costs. This research investigated

four major issues:

1.

2.

3.

4.

how customersrespondthproduct unavailability in a fashion
retail store;

what factors affect customer responses to product unavail—
ability in a fashion retail store;

the influence of product unavailability on customer store
image in fashion merchandising;

the influence of store image on customer responses to stockouts
in fashion retail stores.

Through the cooperation of a high fashion women's apparel store chain

in Oklahoma City, a sample of their customers was taken from the active

charge card file. A total of 1006 customers was mailed a questionnaire

without any other incentive than the promise that store management

would be provided with inputs to upgrade the service and image of the

store. Twenty-six percent of the sample returned usable responses

which were analyzed to specifically test seven hypotheses:

H 1:

H 4:

H 5:

Customer responses to stockouts in fashion merchandising
are primarily characterized by "exit" rather than switching
behavior or by purchase postponement.

Customer reactions to stockouts are affected by the
intentions behind the attempted purchase.

Demographic characteristics of shoppers, such as age,
income, level of education, number of children, affect
customers' responses to stockouts.

Situational variables, such as distance traveled, affect
customers' responses to out-of-stock situations.

When a customer is faced with an out-of-stock situation,
there will be a negative effect on the customer's perception
of the store.

Customer responses to stockouts are affected by the image
of the store which the customer held prior to the stockout
experience.

122

H 7: In fashion shopping customer responses to stockouts are
characterized by "exit" rather than by "voice" behavior.

Experimental Design

 

The scenario approach was deemed necessary as it is difficult to
get an idea of what the customer thinks of a store before she has an
out-of-stock experience there. Two stores were projected with
distinctly different images. Pretesting assured the distinction, but
it was unequivocally substantiated by the actual research. In the
description of the stores, certain image elements such as location and
advertising were used to assure differences between the two. For
measurement purposes in the actual questionnaire, other popular
dimensions (see Lundquist, 1974) such as merchandise selection, sales
people, store services, etc., were used. Within a given store, randomly
selected respondents were exposed to one of three possible situations:
a positive one in which the particular shopper found the right size
of a desired item, a negative one in which she did not find the right
size, and as a control group, a situation with no particular experience.

Analysis of variance showed that prior image did not necessarily
affect how a customer responded and, especially, that the actual
experience per se did not significantly relate to what she decided to
do about it. The fact that less than 10% changed their opinion due
to the negative experience, may or may not cause retail store manage-
ment any concern, but that percentage appears low, confirming Rich and
Portis' conclusion that fashion store images are among the strongest

(1964).

123

Important observations were made regarding the price level
perception as part of the store image measurement. In many cases,
price stood out as an image attribute that depressed the overall
reliability of the measurement scale used. These observations indicate
that pricing was very much a separate factor in store perception.
Factor analysis, as also reported in Chapter IV, reinforced this
conclusion.

Given the substance and the variation of the impact, it can be
concluded that price levels confuse customers in their perceptions
of a store. In the case of the actual store, where the impact of price
level perception on image scale reliability was even more negative,
the confusion can be attributed to a deviation in store policy on only
carrying higher priced merchandise. After checking with store manage-
ment, there had indeed been some instances where close-out merchandise

was carried at relatively "bargain" prices.

Conclusions

Hypothesis One

 

With regard to hypothesis one, crosstabulation analysis as
reported in Chapter IV showed that most fashion apparel shoppers
tended to walk out before they switched to another item within the
same store and were even less willing to wait. Referring to the
actual stockout experience by the respondent, the question was asked,
"What did you do when you could not find what you were looking for?"
In interpreting answers to this question, buying another version

("switching") of whatever the shopper was looking for--brand, size,

style, color—-is not necessarily a negative reaction for the retailer
(e.g., Lusch, 1982). The literature has not reported any conclusive
research findings on whether buying alternatives, as mentioned above,
result in more or less money being spent by the shopper. However, when
consumers decide to buy something else, we may safely assume that the
monetary losses for the retailer are not as severe as when consumers
leave and buy somewhere else. For the same reasons, buying something
entirely different is still buying within the same store and cannot be
considered a very negative result for the store either.

In the case of the hypothetical experience the same type of
interpretation can be made. The alternative of "forgetting both" is
considered the worst from a retailer's point of View. The less negative
alternative is that a customer asks for the skirt to be held, while she
looks for a matching blouse somewhere else. This is based on the
premise that she had somewhat of a commitment to return, although
this commitment may not be very strong. Holding the skirt and ordering
the blouse is considered to be a sign of willingness to wait, which
merely postpones the cash-flow until the order comes in. This, of
course, is assuming that reorders are possible, which is generally
not the case (Greenwood and Murphy, 1978).

Buying the skirt, conditional upon the blouse being on order,
moves up some cash-flow and therefore is considered less unfavorable
a reaction than the preceeding ones. Given the slight chance that
backordering is possible in the industry (Greenwood and Murphy, 1978),
this alternative ranks at about the same level as "buying the skirt

and leaving" as a reaction. If the consumer is willing to buy the

125

skirt and to order the blouse, the retailer is presumed to suffer
the least from the out-of-stock experience given the possible reaction
by the consumer.
In any case, results showed distinctly that "exiting" was a
frequently displayed behavior by a customer who would not buy the
item(s) for which he/she was looking. Clearly, this behavior results
in the immediate loss of the sale and thus the margin that could have
been earned on the item. Further repercussions for the retailer depended

on other factors that were investigated and are discussed below.

Hypothesis Two

 

Regarding hypothesis two, the reason why the shopper originally
went to the store-~to buy one or several items, or to browse--had a
very significant effect on what the customer did in case of an out-of-
stock situation.

Clearly, there is an element of importance to a shopper involved
in deciding what to do when the out—of-stock situation is encountered.
Customers looking for only one item are apparently spending more time
looking for an item in one store. There search/choice criteria for
that item may be clearer and they feel that there is a chance to find
at least a close alternative. Those who are looking for several items
may not have that time or are simply not even expecting to find all
that they are looking for in one store: they might as well not spend
much time on one item as they could expect to run into something
similar in another store they were going to visit anyway. The shopper
who is just browsing causes the retailer the least amount of concern

in this case, as respondents were more likely to buy something else

126

"within" or were willing to wait for the item in question. If several
items are sought then the customer might as well go elsewhere as she
probably does not expect to be successful in finding all of the desired
items in one specialty store.

Given the cross-sectional nature of this research, it was difficult
to identify over time the effects on customers' store perception in
these situations. With the importance of frequency of occurrence in
determining what to do, the longitudinal perspective is relevant.

In conclusion, at the .05 level of significance hypothesis two was
not rejected. This finding is in agreement with the literature,

particularly Bellenger and Kargaonkar (1978).

Hypothesis Three

 

Analysis, using various methods such as cross-classification and
analysis of variance, showed that only age and the presence in the
family of children under 12 had a significant effect on the way shoppers
responded to stockouts. The demographic variables that were included
in the questionnaire were picked as they were the most frequently
mentioned in the literature, starting with Martineau (1958), as
possibly being influential in image related situations.

Interestingly, the "under 25" group was more willing to wait than
was expected. It can be explained by the apparent importance of status
to this group in buying from a high fasion store. This importance
could be enhanced by the older reference groups (relatives and/or
employers) who, according to the demographics analysis, made up the

largest percentage of patrons of the store chain involved.

127

The 25-34 and 35-44 groups were more willing to shop elsewhere upon
not being able to find what they were looking for. More than likely
a respondent in these groups can be classified as a recreational shopper
(Bellenger and Kargaonkar, 1978): whether she is with the stroller or
with a friend/relative, this shopper conforms more to the "shopping
around" type. Customers, buying for their children, were more than
likely also looking for themselves. In this manner, they fit the group
classified earlier as "shoppers for several items". Thus the results
confirm those found earlier for that group: shoppers with children
under 12 were much more likely than expected to buy elsewhere. The

conclusion also supports the recreational shopper theory.

Hypothesis Four

 

Situational factors were also tested as possibly affecting
stockout responses. The number of times a shopper had experienced
an out-of-stock proved very important. Another factor was the extent
to which the shopper was annoyed by the occurrence. These results

confirmed what was intuitively expected.

Hypothesis Five

 

A given stockout experience, however, did not significantly affect
the response to the situation. Two indicators were available to test
this hypothesis. One measurement involved a direct question on the
basis of an actual experience by the respondent. The second one was
made possible by the experimental design element of the questionnaire
which was necessitated by the need to test the effect of prior image on

stockout response as referred to again in the previous section. The

128

scenario approach yielded answers to a question on the likelihood of
returning to a hypothetical store in which a shopper had a certain
experience. That this likelihood was not significantly affected by the
type of experience--positive, negative or none in particular-—also led
to the conclusion that hypothesis five should be rejected, again with

the caveat that a cross-sectional view was taken.

Hypothesis Six

 

With the general finding being that prior image did not affect the
manner in which a customer responded to an out-of-stock situation, the
following point needs to be made.

In the testing of this hypothesis, it was found that only in
certain cases somewhat of a prior image effect on stockout response
could be detected. One of the cases involved a difference in likeli-
hood of returning to the store between respondents who had a positive
experience under scenario A and those who had no particularly described
experience in that store under the same scenario. This difference
indicates the important influences that finding a desired item has on
a customer's image of the store.

The other case entailed the "positive" experience under scenario
A versus the "negative" one under scenario B. This differences in
likelihood to return to the store as a result of the type of experience
in it, can be explained given the difference in image found between
the overall scenarios A and B (Figure 10). With the above difference
then being a difference between extremes, a conclusion of prior image
having a significant effect on the out-of—stock response, as measured

in this way, has to be treated very cautiously.

129

Apparently positive experiences are effective in enhancing store
image than negative experiences in detracting from store image (also
see the conclusions on hypothesis five). It becomes almost a
rationalization to shop there ("I was successful there before, so why
not"), whereas going back to the store in which a stockout was
experienced, can be rationalized in many ways, too (e.g., "Oh, why
not, who knows they may have something; besides, it's on the way").

In any case, this research lends credibility to what has been
found in the literature, that images of fashion stores are the strongest
of all store images (e.g., Rich and Portis, 1964). Also, it is again
concluded that fashion store images, if not the strongest, are at
least rather robust with respect to stockout occurrences (hypothesis

five).

Hypothesis Seven

 

The issue of the number of customers walking out without communi-
cating in some way with store personnel that they had an out-of-stock
experience, became apparent. If store management is to improve its
merchandise selection and its chances in mitigating the impact of
inadequacies in it, it would certainly help if customers express
themselves. Whether the customer is annoyed or not by the experience,
valuable input on customer expectations, motives and wants can be
obtained if an atmosphere can be created in which she feels comfortable
providing that feedback. As it turned out, a substantial number of
shoppers did walk out, for various reasons, without checking with

store personnel.

130

If a customer leaves the store without interacting with a sales
person, the customer's action not only conceals the inadequate
restocking and organizing of the shelves and racks, but also eliminates
valuable input in assortment planning decisions. In other words, if
"exit" behavior is displayed, monitoring of customer preferences, an
important retailing function (e.g., Bowersox, 1978), is severely lacking.
Over and over, merchandise and sales person related factors turned
up being very important, leading to the conclusion that assortment
decisions have to be approached very carefully, but if mistakes are
made, the sales person still has a lot of influence on how the negative

experience affects the shopper and her perception of the store.

Implications

According to one of the original objectives, the attempt was made
to provide greater insight in the merchandise assortment decision.
After thoroughly verifying the reliability of the measures used,

several important implications are evident.

Stockout Definition

 

The research showed clearly that the traditional way of defining
a stockout is inadequate. From a retailer point of view, the literal
interpretation of a stockout implies an inventory management problem.
However, another form of stockout is encountered after a retailer either
drops a product from the assortment or decides not to carry one to
begin with for strategic reasons. In this situation, it will very
likely be necessary to contend with shoppers who still ask for the

unavailable item. To the customer it is still an out-of-stock

131

experience which, as the research findings showed, was also important
when compared to how she reacts under traditional stockout conditions.
As a result, we can now speak of a logistical (inventory management)
stockout and a strategic stockout.

Consequently, for the retailer in the integrated merchandising
decisions, depth of assortment (logistical view) is not the only
important dimension of assortment. Width, or breadth, particularly in
terms of different fashion items, has to be considered as well. In
doing so, decisions on width either enhance or detract from the
consistency of assortment, or the relationship among product lines
carried. Thus, the consistency dimension has to be considered as
well in the assortment decision. Consistency leads to expectations
formed by the customer: a hardware store is not expected to carry
living room furniture, but it might be that a shopper expects it to
carry some lawn furniture. The greater the variety of items that
store has carried, in the customer's own past experience or according
to word-of-mouth, the greater the chance, in the consumer's mind,
of the lawn furniture being carried.

In particular, one research conclusion drawn was that depth of
assortment (color and size availability) was not considered as brand
availability which is an element of width. However, a much greater
influence on stockout responses was found in the (lack of) availability
of styles which points in the direction of consistency of assortment.

In essence, the decision on which items to carry and which to
drop affects the consistency of the whole assortment and, thus, it
could affect the expectations of the shopper. The importance of at

least studying those factors in terms of their effects on consequences

132

of stockouts was brought out by this research. Level of expectations
showed a strong relationship with (1) customer actions taken in the
case of a stockout, (2) the extent of her being annoyed, as well as
(3) the likelihood of her returning to the store, with all the influence
she may have on friends and relatives. Even though several factors,
in the time between the visit during which the out-of-stock was
experienced and a possible next visit, could mitigate the seriousness
of the reactions to the retailer, this shopper's influence on other
shoppers has to be considered, too. Factor analysis showed that store
related variables such as location, could be among those mitigating
factors. However, psychological and social issues formed an important
factor also. Shopping with a companion, or at least discussions with
friends or relatives on the patronage topic seemed to be strong issues
in bringing these shoppers back, but when asked what a retailer could
do to improve the chance of returning, the respondent placed greater

importance on the sales personnel influence.

Buyer Evaluation

Traditionally, the buyer's task has been to purchase within
guidelines as primarily dictated by the selling potential of the
merchandise. As forecasting is a difficult task, the performance
of a buyer has to be evaluated carefully. From a personal standpoint,
this buyer, if he/she is going to make an error, will be least subject
to negative evaluations by management if he/she errs toward the
understock rather than the overstock side of the assortment balance.

The inability to measure the costs of stocking out, relative to the

133

ability to determine costs of overstocking, is greatly responsible
for this behavior.

Furthermore, it is conceivable that a buyer is regarded as
successful if more often than not the quantity of merchandise bought
is sold without markdowns being necessary just to move the goods.
However, this same buyer's performance should, given the results of
this research, be subjected to closer scrutiny if too often his/her
merchandise is cleared without such markdowns. Particularly with
merchandise that is determined to be closely related to the store's
main mission and very sensitive from an image building point of view,
a closer look should be taken. A more realistic formula could be
found to more critically evaluate a buyer's performance. Perhaps, a
priority scale could be developed for merchandise categories, based on
store management's assortment policies, with a ratio assigned to each
category as to the frequency allowed of overstock versus no overstock

(where no overstock might indicate the possibility of stockouts).

Sales Personnel

 

Given that many people walk out without talking to sales people
regarding an item not found, it is imperative that an atmosphere is
created in the store to entice the consumer to communicate. The
research points out that sales personnel are very influential in
affecting customer reactions to possible assortment imbalances. As a
result, training of these employees can be modified to include ways
to determine as soon as possible the type of customer entering the

store. Future research could involve a discriminant analysis to

134

analyze if "exit" customers differ from "voice" customers and in
which characteristics.

With regard to atmosphere creation, the reasons why customers do
not communicate with sales personnel regarding items not found could
be explored. In this research a preliminary impression was obtained
when one out of four respondents reported that they "usually do not
ask such things" and many of the others indicated some dissatisfaction
with the type of response to their inquiries. Surely, a major, sincere
and concerted effort on the part of sales personnel in dealing with
these situations would be a good start in the creation of the appropriate
atmosphere. As seen above, the input that sales people can provide
to a buyer as to the items understocked, is very important. Yet, when
errors are made, at least the sales person can be effective in
mitigating negative consequences of a stockout. Additionally, greater
opportunities for customer feedback provide valuable input in the

merchandise assortment decision in general.

Implications for Store Image

 

As fashion store images proved to be very strong and, therefore,
can act as buffers to a deterioration of image resulting from
negative shopping experiences, the emphasis in the literature on
projecting the proper store image (see for example, Pessemier, 1980;
King and Ring, 1980; Ring, 1979) becomes not only justifiable, but
also very relevant. With the emphasis on retail store positioning
through a clear image projection justified through this research,
the importance of customer expectations as to the store's merchandise

assortment and selection is underlined again.

135

Channel Role of the Retailer

 

In vendor relations it seems plausible that the more sophisticated
retailer receives greater attention from the vendor. This could involve
accuracy of order filling, pressure on order deadlines, as well as
credit related matters. Showing greater and more accurate awareness
of the impact of understocking whether caused by buyer or vendor error,
certainly contributes to the impression of sophistication.

In addition, a retailer's response to inaccurately shipped orders,
whether the result of vendor or carrier error, will likely be more
"thought out". Deducting a percentage from the invoice, returning
the shipment, or any other alternative, can be more realistically

evaluated with an increased knowledge of the consequences of stockouts.

Limitations

Certain limitations have to be recognized for a realistic inter—
pretation of the research results. As outlined before, the sample was
not designed to be representative of the total population limiting the
ability to make inferences beyond the population from which respondents
were sampled. Yet, the implications as described above, do not suffer
considerably in relevance.

Another constraint concerns the research methods used. Scenarios
have been criticized before, yet the measures of reliability that were
used supported the original reasons why this method was employed.

Issues related to the entire area of image measurement are certainly
relevant here as well, even though the extent of the link to that area

has been limited to the measurement of relevant changes in store

136

perceptions. However, the most relevant limitation of all seems to be
the cross-sectional nature of this research. Miklas (1979) already
suggested that a longitudinal approach to image measurement is definitely
more relevant. Therefore, in this context, the absence of measurement
over time of stockout responses and effects applies here, too. As a

result, the following are suggestions for future research.
Suggestions for Future Research

In general it can be said that improvements on the limitations
as mentioned are already suggestions for future measurement efforts
in the area of stockouts, such as the need for a logitudinal approach
to the measurement. However, there are some particular areas which
require more research effort.

From a shopper's standpoint, the effect a shopper's mood has on
a stockout response has not been conclusively shown. Yet it seems
plausible that it plays a role not only in the response itself, but
in the length of time she will remember the incident and thus the time
she has to influence others. Also, her general perspective on the
shopping activity can be considered important. A shopper who considers
it a fun activity will not be as affected by an out-of—stock experience
as a shopper who despises shopping. Should these indeed turn out to
be important in the way a shopper responds to the stockout, even
more importance is placed on the sales person's abilities to recognize
these states of mind and to deal with them effectively. Along the
same lines, the actual product category in question could be very

relevant, too. The purchase of outer-, under—, or sleepwear also

137

affects the importance to the buyer as that influences her ability to
wait or desire to shop elsewhere. These are other critical factors
to realize in the merchandise assortment decision.

It is also interesting to learn the view of the retailer on the
phenomenon of stockout, particularly in relation to the narrow and
expanded version of the definition of such events. To learn these
views also serves as an input in a broader study on the role of
stockouts in channel relations. It could be hypothesized that when
stockouts are frequently the result of inventory management errors,
there will be an effect on the relationship with the supplier in terms
of level of cooperation in advertising, meeting shipping/ordering
deadlines, etc. On the other hand, if stockouts are due to strategic
stockouts, suppliers may be more forced to rely on pull advertising
to gain the retailer's willingness to provide exposure to the product.
Furthermore, should stockouts be more often the result of supplier
errors, the repercussions for those suppliers are readily apparent.

In total, however, it is certainly necessary to study the
phenomenon of stockouts. By better understanding them we can not only
deal with them better, but we can also begin to realize that they
cannot and should not be treated as evils that cannot be completely
avoided. There is a strategic role available for them in merchandise
assortment planning and the relevant channel of distribution relations,
not only in fashion retailing, but in any other fields where assortment

decisions need to be made.

APPENDICES

APPENDIX A

DEMOGRAPHICS OF STREETS' STORE LOCATIONS

138

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APPENDIX B

COVER LETTER

APPENDIX B

COVER LETTER

Actual name and
addresses will be
typed individually
using word processing.

Dear "Ms. Customer":

You will probably respond to this mailing by saying: "Another one of
those lists of questions they want me to answer." And you are right,
we would like your input. As a matter of fact, your input is
extremely vital in allowing Streets' to offer you, a valued customer,
the best assortment of fashion goods possible.

In order to improve the store's merchandise offering, we drew a sample
of our customers and your name came up along with 199 others. This,
however, is the only time we will know about you as your response will
be kept completely confidential. We must ask you therefore not to
write your name or any identifying information on the questionnaire
that is not asked for directly. After filling out the questionnaire
completely, just put it in the self-addressed stamped envelope and
drop it in the nearest mailbox.

We sincerely appreciate the time and effort you spent to assist us.
We will do our best to use the results to your benefit by making
Streets' a better place to shop. If you have any questions or other
input to give, please do so by writing or calling me.

Thank you very much!

Sincerely,

G. P. van Nederpelt

Assistant Professor of Marketing
Oklahoma State University
Stillwater, OK 74078

140

APPENDIX C

SCENARIOS A AND B

APPENDIX C

SCENARIOS (A)

A I

Fashion Unlimited is a retail apparel outlet. It attracts younger
women in particular. Atmosphere in the store is created by plush
carpeting, piped-in music, etc. Several young and well-dressed sales
people are usually immediately available. Merchandise is neatly
displayed on mannequins, chrome racks and mirrored walls. The store
has approximately 15,000 square feet and is located in a large shopping
mall. The mall is located in a higher income part of town. The store
is the only outlet under the Fashion Unlimited name in the central
Oklahoma area. Occasionally, there is a commercial on prime time
television, advertising the store and its merchandise.

AII (=AI+)

While shopping at Fashion Unlimited, you have decided to buy an item
you like: a beautiful skirt. Now you are looking for something to
go with it and in so doing you find a blouse that matches nicely.
Fortunately, you find the blouse in your size.

A III (= A I +0

While shopping at Fashion Unlimited, you have decided to buy an item
you like: a beautiful skirt. Now you are looking for something to go
with it and in so doing you find a blouse that would match nicely.
However, after looking for awhile you cannot find your size.

SCENARIOS (B)

B I

Fashion Unlimited is a retail apparel store, where generally women
with children seem to shop. Even though there are tile floors, they
seem to be comfortable places at which to shop. Sales people can
usually be found hanging around the check-out counter. There are
few displays with merchandise hung on long racks and folded on tables.
Each of the several stores with the same name in the area, has about
10,000 square feet of selling space. Some of the stores are located
in closed-in malls, whereas others are in open malls and some are
standing by themselves. The stores can be found in all different
areas of the city. Advertising is done in the localtmmspaper and at
least every Wednesday there is a full page ad.

141

142

B II (= B I +)

While shopping at Fashion Unlimited, you have decided to buy an item
you like: a beautiful skirt. Now you are looking for something to
go with it and in so doing you find a blouse that matches nicely.
Fortunately, you find the blouse in your size.

B III (= B I +)

While shopping at Fashion Unlimited, you have decided to buy an item
you like: a beautiful skirt. Now you are looking for something to
go with it and in so doing you find a blouse that would match nicely.
However, after looking for awhile you cannot find your size.

APPENDIX D

COPY OF THE QUESTIONNAIRE

AUIPETUDIXII)

COPY OF THE QUESTIONNAIRE

The first set of questions pertains to a hypothetical store. The purpose of asking you to answer
these questions is for us to learn more about shepping for fashion goods in general. 50 for the
next set of questions. it is important that you imagine yourself to be in the following situation:

2.

Fashion Unlimited is a retail apparel outlet. It attracts younger women in particular. At-
mosphere in the store is created by plush carpeting, piped-in music, etc. several young
and well-dressed sales people are usually immediately available. Merchandise is neatly
displayed on mnnequins, chrome racks and mirrored walls. The store has approrinutely
15,000 square feet and is located in a large shopping mall. The mall is located in a high-
er income part of town. The store is the only outlet under the Fashion Unlimited name in
the central Oklahoma area. Occasionally, there is a commercial on prime time television,
advertising the store and its merchandise.

The following question is designed to measure your opinion of the store. An example has been
provided to show how the rating is done. By placing an 'X' in one of the spaces for each
scale you can show the direction (favorable-unfavorable) and the intensity of your feelings
toward the retail store. For example, suppose you feel that the store is neither “good“ nor
”bad“. i.e. "neutral”, you would indicate this by placing an "X“ in the middle space:
The retail store is:

good / / / x / / / bad
If you feel that the retail store is extremely I'good", you would mark the scale:

good / X / / / / / bad

However, should you feel that the store is extremely 'bad', you would mark the scale:

good / / / / / X / bad

Please, mark each of the following scales describing your Opinion of Fashion Unlimited:

 

 

 

 

 

 

 

high fashion / / / / / / low fashion _ (7-13)
low priced / / / / / / high priced
wide assortment / / / j / / narrow assortment
discourteous sales people / / / / / / courteous sales peeple
will have what I want / / / / / [_will not have what I want
bad refund policy / / / / / / good refund policy
good merchandise / / / / / / bad merchandise
return policy return policy

Please, indicate in percentages how likely you are to shop at a store like this:

less than 25% (14)
26 - 50%
51 - 75$
76 - 100$

 

143

144

For the next set of questions it is important that you think of your favorite Streets' store. At
this time the accuracy of your answers becomes even more important so that store management can

become more responsive to your fashion needs. We appreciate your efforts so far and hope you will
continue to give us valuable assistance for just a little bit longer.

What is the location of this store in Oklahoma City:

(5-6)

 

3. The following question is designed to measure your opinion of Streets': (7-13)

high fashion la.

low priced /

wide assortment
discourteous sales people

always has what I need

\\\\k

bad refund policy

Kx ‘\ ‘\ ‘x 5‘ bx ‘\
\. \. \. \t \. \. \~

\\\\\
\L\\\\\

good merchandise
return policy

4. For what reason did you first shop at Streets':

friends recommended the store

the ads made me curious

was in the mall anyway when I saw the store
other, please describe

/

/
A/
/
/
/
/

low fashion

high priced

narrow assortment
courteous sales people
never has what I need
good refund policy
had merchandise

return policy

(14)

 

Please, think back to the last time that you were not able to find what you were looking for in

this store.

5. What ingparticular was it that you could not find? (Choose one)

my brand

my size

my style

my color

other, please specify

(15)

 

6. How did you feel then?

very annoyed
somewhat annoyed
only mildly annoyed
not at all annoyed

(16)

7. For what reason

3. Did you speak to

145

did you initially go to the store?

to look specifically for the item that turned out to be unavailable

to look for several items

just to look around

to window shop with a friend/relative
other (please describe)

 

a sales person about the problem?

yes (if. yes. please go to question 10)
no

9. What was your most important reason for not speaking to a sales person?

(Choose only one

)

I usually do not ask such things

they would only give me some poor excuse
there was no one available

I did not have time to ask

it was not important enough to me to ask
other. please describe

 

10. What did you actually do when you learned that what you wanted was unavailable?

(Choose only one

)

bought another brand of what I was looking for
bought another size of what I was looking for
bought another style of what I was looking for
bought another color of what I was looking for
bought something entirely different
left and bought what I was looking for somewhere else,
but I still shop at Streets'
left without buying anything and I doubt if I'll shop there again
other (please describe)

 

11. How many times has it happened to you that you could not find what you were looking

for in Streets':

12. Did your opinion

never

rarely
occasionally
frequently

very frequently

of Streets' change because of that experience of not finding

what you were looking for:

 

yes
no
no, but it will if it happens again

—3-

(17)

(18)

(19)

(21)

146

13. Peeple react differently when things like this happen to them. Before you decided
what to do in this situation, please indicate how important each of the following
was to you: (23-30)

very not not at all
important important neutral important important

 

 

 

 

 

 

 

 

 

 

the reason why I went shopping / / / / / /
the helpfulness of the sales people / / / / / /
the number of times that this situation
has occurred before / / / / / /
the way I felt at the time / / / / / /
whether I was alone or with others / / / / / /
how badly I wanted what I was looking for / / / / / /
how much time I had to shop / / / / / /
other, please describe f

14. Suppose you leave the above store without buying. You are very annoyed, because you

have had several similar experiences in this store. How important would each of the
following be in bringing you back to shop there again: (31-40)
very not not at all

important important neutral important important

 

 

 

 

 

 

 

 

a special sale / / / / / /
a friend's/relative's suggestion / / / / / /
the convenient location / ‘pg/ / / / /
the reputation/image of the store / / / / / /
your desire to shop around anyway / / / / / /
possession of a credit card issued by
that store / / / / /
the manager contacting you personally / / 4/ / / /
shopping with a friend/relative / / / / / /
I would be so annoyed that I would not
go back / / / / / /

 

other

 

147

15. The following have been identified as possible actions a retailer could take in cases such
as these. Please indicate your preference as to each one of the actions the store could
take in this case:

other. please describe

16. Your age is:

very much

(41-47)

not at all

preferred preferred neutral preferred preferred

 

 

 

 

 

 

 

17. Are you currently employed?

give me a reason that makes sense to me / / / / / /
call me when the item is in / / / / / /
tell me how long it will be before
another item is in / / 4/ / / /
show me an acceptable alternative / / / / / /
tell me where I might be able to find
what I want / / / / / /
check with another Streets' store / / / / / /
To allow us to process the information, please answer the following questions. Your answers
will only be used for statistical purposes and complete anonymity is assured.
(48)
under 18
18 r 24
25 - 34
35 - 44
45 - 54
55 - 65
over 65
(49)
no
part-time
full time
temporarily off work
do not need to work
education is: (50)

18. Your level of

did not finish high school

finished high school

went to college. have not graduated
received an undergraduate degree

received graduate training
other, please describe

 

19. In order to shop at the Streets' store where this experience

does it usually

148

take you to get there?

0 - 5 minutes

6 - 10 minutes

11 - 15 minutes

16 - 20 minutes

21 - 25 minutes

26 - 30 minutes
more than 30 minutes

20. How long have you lived in the Oklahoma City area?

less than 1 year

1 - 3 years

3 - 5 years

5 - 10 years

more than 10 years

21. What is your marital status?

single
married
divorced
widowed

22. How many children under twelve live at home?

none

one

2 - 3

more than 3

23. Your combined family income per year is approximately:

less than 10,000
10,001 - 20,000
20,001 - 30,000
30,001 - 40,000
40,001 - 50,000
50,001 - 75,000
more than 75,000

T. YO

-6-

happened how long

0 1

(S1)

(52)

($3)

(54)

(SS)

APPENDIX E

DEMOGRAPHICS OF THE SAMPLE

149

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“3. 1:1,; I."