<^i *i\*4 Division of Agricultural Sciences 
 
 fvu 
 
 ' V V UNIVERSITY OF CALIFORNIA 
 %,\^ ^ 
 
 GROWTH CHARACTERISTICS OF 30 MAJOR 
 RETAIL FOOD CHAINS «- 1953-1963 
 
 K. D« Duff . . . D. B* DeLoach 
 
 
 CALIFORNIA AGRICULTURAL Ml II FN N 829 
 
 EXPERIMENT STATION BULUIIN 8 a 
 
CONTENTS 
 
 Page 
 
 THE FINDINGS 3 
 
 GROWTH CHARACTERISTICS OF 30 MAJOR RETAIL FOOD 
 
 CHAINS, 1953-1963 5 
 
 Purpose of the study 5 
 
 Procedure 5 
 
 CHARACTERISTICS OF THE MARKET 6 
 
 Demographic changes 6 
 
 Disposable income 8 
 
 CHARACTERISTICS OF THE RETAIL FOOD INDUSTRY 10 
 
 THE RETAIL FOOD CHAINS 15 
 
 Growth characteristics of chains 17 
 
 Effects of Growth 24 
 
 Financial interrelationships 26 
 
 INDUSTRY PERFORMANCE AND PUBLIC POLICY 29 
 
 Methods used 29 
 
 Growth patterns 29 
 
 Effect of population changes on number and location of grocery stores 34 
 
 Conduct and performance of chains 35 
 
 GOVERNMENT REGULATION 40 
 
 Legal restraints 40 
 
 Public opinion 40 
 
 Current investigatory philosophy 41 
 
 APPENDIX A 43 
 
 APPENDIX B 48 
 
 APPENDIX C 54 
 
 APPENDIX D 58 
 
 Application of Markov technique to structure data 58 
 
 Limitation to the Markov analysis 60 
 
 APPENDIX E 64 
 
 LITERATURE CITED 65 
 
 JANUARY, 1967 
 
 THE AUTHORS: 
 
 K. D. Duft is Research Assistant in the Experiment Station, Davis. D. B. DeLoach is 
 Professor of Agricultural Economics and Agricultural Economist in the Experiment 
 Station and on the Giannini Foundation, Davis. 
 
THE FINDINGS 
 
 This bulletin reports the study of the 
 operating performance of 30 major gro- 
 cery chains over the 10-year period 1953— 
 1963, their pattern of growth, and the 
 factors behind their growth. It provides 
 an economic analysis of the concentration 
 of market power in the retail grocery busi- 
 ness. 
 
 Today, more than enough retail food 
 stores are available to supply the require- 
 ments of the local population in many 
 parts of the United States. The retailers, 
 competing for sales, cater to customer pref- 
 erences for products and services, as much 
 as this is economically feasible. 
 
 Population shifts, among age groups as 
 well as geographically, affect managerial 
 planning for food distribution. For in- 
 stance, figure 1 shows a projected increase 
 by 43 per cent in the 20-to-29-year age 
 group by 1972, thus constituting a large in- 
 crease in new family units. Similarly, the 
 westward migration of our population 
 forecasts a higher level of demand for food 
 products, marketing services, and facilities 
 in the West. Because market growth offers 
 opportunities for food retailers, new mer- 
 chandising technologies find fertile 
 ground. The firms that survive must pro- 
 vide modern facilities, services, and prod- 
 ucts at competitive prices. 
 
 Corporate chains, operating only 10 per 
 cent of the grocery stores in the United 
 States, sold more than 41 per cent of the 
 total grocery store volume in 1964. Affili- 
 ated buying groups handled 50 per cent, 
 and unaffiliated stores 9 per cent. 
 
 About 68 per cent of the total grocery 
 sales volume moved through supermarkets 
 — stores with an annual sales volume of 
 $500,000 or more. The relative volume of 
 all small stores (up to $150,000 annual 
 sales) continued to decline after 1958. This 
 reflects a further shift of patronage to mass 
 merchandising establishments. But the 
 number of relatively small chain store 
 firms increased, which indicates that es- 
 tablished firms do not erect entry barriers, 
 especially since most of these newer chains 
 are found in large metropolitan areas 
 where they are competing with the larger 
 
 previously established chains. The new 
 chains, however, may find it difficult to 
 obtain capital for entry and to survive 
 in a competitive market. 
 
 Both from the standpoint of relative 
 sales volume and actual store numbers, the 
 two largest firms — The Great Atlantic and 
 Pacific Tea Company and Safeway Stores, 
 Incorporated — were relatively less impor- 
 tant in 1964 than at any time during the 
 last 20 years. The relative share of annual 
 sales of the 20 major chains was about the 
 same in 1929 and 1962. The most signifi- 
 cant sales growth took place among the 
 medium-size chains. 
 
 Several financial items were analyzed. 
 Among the significant results are these: 
 
 • The portion of total assets considered 
 fixed increased slightly, possibly cir- 
 cumscribing some of the flexibility 
 needed in a progressive industry. 
 
 • The smaller chains seem to be using 
 more short-term credit than the larger 
 chains, particularly for open account 
 purchases. 
 
 • The net worth position of the larger 
 concerns improved slightly compared 
 to that of the smaller chains. This 
 seems to reflect their retention of cor- 
 porate earning instead of outside 
 financing. 
 
 • Before 1958, small chains had the 
 largest net profits per sales dollar. 
 Since 1958, this pattern has been re- 
 versed. 
 
 • Net sales were more responsive to 
 changes in store numbers in the large- 
 chain group than in the smaller-chain 
 groups. 
 
 • On an average, the addition of one 
 store tended to increase a chain's total 
 annual net profit by $10,000. The 
 small-chain group showed the lowest 
 level of response in this respect. 
 
 An effort was made to account for the 
 growing importance of retail chains in 
 food distribution. The most obvious con- 
 clusion from the analysis is that, given the 
 state of our technology, the "push for big- 
 ness" that characterizes most businesses, 
 including agriculture, shows that size, sales, 
 
 [3] 
 
and buying volume are basic to minimiz- 
 ing unit costs and increasing total net 
 profits. Nonetheless, retail chain managers 
 are always seeking the optimum size for 
 their individual stores and the optimum 
 number of stores within their given firm. 
 Through the analysis, the following gen- 
 eral tendencies show up: 
 
 • Group I (large-size chains) has the 
 highest net return on net dollar sales 
 on the average, while many of the 
 large firms seem to be losing their 
 grip on total industry sales. 
 
 • Group II (medium-size chains) seems 
 to be most dynamic in increasing the 
 scope of its operations. The data in- 
 dicated great variations among the 
 operating trends of the 10 individual 
 chains in this group. 
 
 • Group III (small-size chains) seems to 
 be rapidly expanding its relative 
 share of the market, while as a group 
 it received the lowest relative net 
 profit as percentage of net dollar sales. 
 
 None of the chains seems to be satisfied 
 that its present size, both in terms of sales 
 and stores, provides the solution for op- 
 timizing profit. Therefore, experimenta- 
 tion goes on. The authors' attempts to 
 project the outcome of this experimenta- 
 tion led to the conclusion that a further 
 growth in the average size of chains is 
 likely. This does not mean, however, that 
 the large chains will grow still larger, 
 compared to the others, but that the small- 
 
 and medium-sized groups will increase in 
 size. 
 
 Most investigations of the food industry 
 have been made in answer to expressed 
 dissatisfactions about some element of in- 
 dustry performance, usually about alleged 
 inequities over prices paid or received at 
 various levels of food production, manu- 
 facturing, or distribution. Most investiga- 
 tions have assumed that the alleged in- 
 equities are associated wth the market con- 
 duct of large-chain firms that use their 
 economic power to influence, unduly, the 
 terms of trade at all levels of marketing. 
 
 It is the judgment of the authors that 
 technology has fostered and encouraged 
 bigness in almost all of our basic industries, 
 including agriculture. Large-scale, multi- 
 store retail food firms seem to be the only 
 satisfactory arrangement to provide the 
 investment capital required to support the 
 modern technologies used by such firms. 
 The only alternative source of capital of 
 such magnitude would be a federal 
 agency. This alternative has far-reaching 
 implications. 
 
 The authors consider the growth of 
 large food chains as a function of the com- 
 petitive struggle for customers. Through- 
 out the evolutionary period of mass mer- 
 chandising, consumers have had alterna- 
 tives available to them. If and when con- 
 sumers find a more satisfactory solution to 
 their food supply problems, retailing 
 methods will be adjusted further. This is 
 a basic attribute of the competitive process. 
 
 r 4 j 
 
GROWTH CHARACTERISTICS OF 30 MAJOR 
 RETAIL FOOD CHAINS— 1953-1963 1 
 
 v^ongress authorized the creation of the 
 National Commission on Food Marketing 
 on July 1, 1964, to conduct a broad eco- 
 nomic inquiry of our food processing and 
 distribution system and to report its find- 
 ings by June 30, 1965. Ensuing delays in 
 organizing the Commission and its staff 
 made it necessary to extend the reporting 
 date to June 30, 1966. Many leaders in the 
 food industry were apprehensive about the 
 type of inquiry that would be undertaken 
 and believed that the short time allocated 
 to the Commission for a comprehensive 
 study would make a thorough appraisal 
 of the economic problems confronting the 
 industry impossible (Ginsburg, 1966). 
 Many officials of retail food chains — cen- 
 trally owned and controlled retail grocery 
 firms with two or more store outlets — 
 were uneasy about the direction the in- 
 quiry would take. Their past experience 
 led them to believe that many economists, 
 legislators, and farm leaders had already 
 publicly taken a position on three of the 
 main issues submitted to the Commission 
 for study: 
 
 • That there is an undue concentration 
 of market power in a few retail food 
 chains. 
 
 • That the chains use their market 
 power to depress farm prices and keep 
 prices to consumers higher than they 
 would be under more competitive 
 conditions. 
 
 • That additional government restraints 
 or remedial legislation are needed to 
 correct the imbalance among the vari- 
 ous groups engaged in producing, 
 processing, distributing, and using 
 food (Adamy, 1966). 
 
 Purpose of the study 
 
 The authors of this report, along with 
 many other economists, are unwilling to 
 accept the foregoing claims without fur- 
 ther examination (Tongue, 1965). In par- 
 ticular we wanted to probe the implied 
 
 Submitted for publication August 4, 1966. 
 
 charge that retail food chains strive to in- 
 crease their size (power) primarily to mani- 
 pulate their buying and selling prices. An 
 alternative explanation for growing power 
 of chains seems to be their advantage in 
 obtaining the investment capital required 
 to establish and operate modern retail 
 outlets, including their ability to compete 
 in pricing and promoting their mechan- 
 dise, and their greater flexibility in adapt- 
 ing to the demographic changes in the 
 United States. 
 
 To learn more about the reason for the 
 growth in size and market power of retail 
 food chains, an analysis of the growth 
 characteristics of 30 major national and 
 regional retail grocery chains was under- 
 taken. This bulletin reports one phase of 
 the study, supplementing U.S. Federal 
 Trade Commission (1960) and Hiemstra 
 and DeLoach (1962). 
 
 Procedure 
 
 The procedure for the analysis was dic- 
 tated partly by the nature of the obtain- 
 able data. Fairly complete records are 
 available for 30 grocery chains for the 
 period 1953-1963, inclusive. In addition, 
 the 1954 and 1959 censuses provide bench- 
 marks against which the trade data can be 
 compared. 
 
 To analyze the growth characteristics of 
 the 30 chains included in this study, we 
 sketched the environmental conditions 
 which give rise to the demand for the 
 number, kinds, and qualities of retail serv- 
 ices offered consumers. To show the im- 
 portance of recent changes in the structure 
 of the retail grocery business, comparative 
 sales data for both the independent (one- 
 store firms) and chains are introduced. In 
 our analysis of the 30 chains, we classify 
 each chain, according to its annual sales 
 volume, into one of three groups of 10 
 stores each: Group I contains the large 
 chains with $400 million or more annual 
 sales, Group II includes the medium chains 
 with $100 to $400 million annual sales, 
 and Group III has the small chains with 
 
 [5] 
 
less than $100 million annual sales. The 
 groupings are used to show comparative 
 changes among groups I, II, and III and 
 among the chains within each of the 
 groups. 
 
 Changes in several important operat- 
 ing policies and practices are brought out 
 by a comparative analysis of the financial 
 records of the 30 chains. The performance 
 results of each chain within and between 
 the size groups are shown through a com- 
 parison of net returns on investment and/ 
 
 or dollar sales. Finally, an attempt is made 
 to appraise the impact on public policy of 
 the growing economic power of retail food 
 chains and to learn whether that policy 
 has been or is an effective force in modify- 
 ing the growth characteristics of chains. 
 
 The data and other information pre- 
 sented in this report were obtained from 
 the published material listed in Literature 
 Cited, unpublished material referred to in 
 footnotes, and from interviews with indus- 
 try and government officials. 
 
 CHARACTERISTICS OF THE MARKET 
 
 Retail food firms must continually adjust 
 their business policies and practices to the 
 changing environment in which they oper- 
 ate. This environment is affected greatly 
 by changes in population composition and 
 geographic movement, and consumers' dis- 
 posable income which can be allocated to 
 the purchase of various products and serv- 
 ices. 
 
 Demographic changes 
 
 The Bureau of the Census estimates that 
 the population of the United States will 
 approximate 226 million by 1975. This is 
 about 17 per cent above 1964 and 33 per 
 cent above 1954. The structure of the pop- 
 ulation also is undergoing considerable 
 change, especially among the age groups 
 
 AGE 
 Under 10 
 
 10-19 
 
 +28% 
 
 ^30° 
 
 ill! Il/ll I TTTTT 
 
 20-29 
 
 30-39 
 
 40-59 
 
 60 and 
 
 «.E 
 
 -10% 
 
 -23°, 
 
 Total Population 
 
 20% 
 
 TT/l II I! II JJJ. 
 
 +86% 
 
 ^3% 
 
 +26% 
 
 uMZMZM™ 
 
 ii/n/nua 
 
 +76% 
 
 i ////// m 
 
 +40% 
 
 ffl 1940-1962 
 
 □ 1962-1972 
 
 Fig. 1. Changing U.S. age compositions. 
 Source: This Week Magazine, 1963. 
 
 [6] 
 
cS 
 
(figure 1). The projected growth of the 
 20- to 29-age group is particularly impres- 
 sive because it reflects the probable growth 
 of 43 per cent in the number of family 
 units for the period 1962-1972. The ed- 
 itors of the Progressive Grocer (1965) ex- 
 pressed their attitude toward the popula- 
 tion changes with this comment: 
 
 Youngsters married for the first time 
 form a market which offers special oppor- 
 tunities to retailers and manufacturers. 
 Their marriages create new households 
 that never bought (food) independently 
 before. They are establishing brand and 
 store preferences and buying habits. Be- 
 ing inexperienced in shopping, they are 
 more attracted to those store operators 
 who understand their needs and cater to 
 them. The prize, obviously, is not only 
 their present business, but their future 
 business as well. 
 
 In addition to the changes in popula- 
 tion numbers and composition, the food 
 industry is paying close attention to re- 
 gional population shifts that can and do 
 affect their sales and facility requirements 
 in various parts of the country. In recent 
 years there has been a strong movement 
 to the southwestern states and a more 
 moderate growth in most other areas. For 
 example, the combined population of Ari- 
 zona and California rose about 6.7 million 
 between 1954 and 1964, or 48.1 per cent. 
 In the Southeast, Florida's population in- 
 creased by 2.3 million, or 67.5 per cent, 
 during the 10-year period. This meant that 
 the food industry had to provide facilities 
 to distribute food to an additional nine 
 million people in these three states alone 
 (appendix table A-l and figure 2). 
 
 Before 1950, population tended to move 
 from rural to urban areas. Although this 
 urbanization process is still in progress, it 
 has now been overshadowed by a second- 
 ary movement of our city population into 
 surrounding suburbs. Accompanying this 
 movement has been the construction of a 
 multitude of "shopping centers," almost 
 all of which include a grocery store, vari- 
 ous other merchandising outlets, banks, 
 etc., all oriented toward serving the entire 
 range of consumer wants. 
 
 To offset the suburbanization trend, 
 widespread city housing redevelopment 
 
 projects have beeen completed, more are 
 underway, and new ones are planned. 
 This kind of redevelopment of cities has 
 had, and probably will continue to have, 
 an important effect on the types of food 
 distribution facilities required to serve the 
 inhabitants. In fact, some industry leaders 
 believe such redevelopments may be the 
 basis for a revival of neighborhood stores 
 designed especially to supply a large group 
 of consumers who will buy on a "hand-to- 
 mouth" basis. 
 
 The probable impact of population 
 growth and geographic distribution on the 
 number and distribution of grocery stores 
 will be discussed under "Growth Patterns," 
 on pages 29 to 34. 
 
 Disposable income 
 
 The net disposable income of consumers 
 is a meaningful statistic to the retail gro- 
 cer (appendix table A-l and figure 3). 
 This income affects both the volume of 
 sales of the food industry and the kinds of 
 products customers are most likely to buy. 
 Although the food and nonfood purchases 
 in grocery stores are an outgrowth of a 
 number of conditions faced by customers, 
 including better dietary information and 
 alternative products, much of the increase 
 in consumption of meats, dairy products, 
 fruits, and vegetables became possible as 
 income rose sufficiently to enable cus- 
 tomers to shift to these relatively higher 
 priced products (table 1). Also, customers, 
 as their incomes rise, are purchasing more 
 luxury and specialty foods, for example 
 high-markup foreign food specialties. 
 
 Despite the fact that more money is be- 
 ing spent for food today than ever before, 
 the percentage of consumers' disposable 
 income used to buy food has declined from 
 25.6 per cent in 1947-1949 to 18.6 per cent 
 in 1965 (U. S. Department of Agriculture 
 1965c and d). 
 
 Much of the disposable income used 
 for food, household supplies, drugs, cos- 
 metics, and many other consumer goods 
 is spent in combination- and specialty-type 
 grocery stores. Because our primary pur- 
 pose is to examine the food retail distribu- 
 tion system, the next few sections will be 
 directed toward this goal. 
 
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Table 1 
 
 APPROXIMATE CONSUMPTION OF FOOD PER CAPITA 
 
 BY MAJOR FOOD CATEGORIES 
 
 
 1910 
 
 1932 
 
 1955 
 
 1963* 
 
 1910-1963 
 
 Food category 
 
 Pounds 
 
 Percent- 
 age of 
 total 
 
 Pounds 
 
 Percent- 
 age of 
 total 
 
 Pounds 
 
 Percent- 
 age of 
 total 
 
 Pounds 
 
 Percent- 
 age of 
 total 
 
 Percent- 
 age of 
 change 
 
 Dairy products 
 
 Eggs 
 
 337.0 
 37.1 
 
 170.2 
 41.9 
 
 16.3 
 130.6 
 123.0 
 7.6 
 202.5 
 188.0 
 
 14.5 
 221.1 
 
 295.0 
 
 87.9 
 
 9.6 
 
 .211 
 .023 
 
 .107 
 .026 
 
 .010 
 .082 
 .077 
 .005 
 .127 
 .118 
 .009 
 .139 
 
 .185 
 
 .055 
 
 .006 
 
 360.0 
 38.0 
 
 152.8 
 
 46.8 
 
 16.4 
 132.5 
 115.9 
 
 16.6 
 220.0 
 198.0 
 
 22.0 
 156.3 
 
 223.0 
 
 110.3 
 
 13.8 
 
 .238 
 .025 
 
 .101 
 .031 
 
 .011 
 .088 
 .077 
 .011 
 .146 
 .131 
 .015 
 .103 
 
 .147 
 
 .073 
 
 .009 
 
 398.0 
 
 46.9 
 
 191.8 
 49.2 
 
 16.3 
 143.4 
 
 94.6 
 
 48.8 
 202.7 
 154.6 
 
 48.1 
 113.7 
 
 152.0 
 
 106.3 
 
 15.0 
 
 .269 
 .032 
 
 .130 
 .033 
 
 .011 
 .097 
 .064 
 .033 
 .137 
 .104 
 .033 
 .077 
 
 .103 
 
 .072 
 
 .010 
 
 368.0 
 40.0 
 
 203.3 
 
 49.9 
 
 16.7 
 123.7 
 
 73.7 
 
 50.0 
 197.6 
 145.1 
 
 52.5 
 111.4 
 
 144.0 
 
 110.0 
 
 15.6 
 
 1,420.0 
 
 .259 
 .028 
 
 .143 
 .035 
 
 .012 
 .087 
 .052 
 .035 
 .139 
 .102 
 .037 
 .078 
 
 .101 
 
 .077 
 
 .011 
 
 + 9.19 
 + 7.81 
 
 + 19.44 
 -1- 6.62 
 
 + 2.45 
 
 - 5.28f 
 
 - 40.08 
 
 +557 89 
 
 Meats, fish, and 
 
 poultry 
 
 Fats, oils, and butter 
 Beans, peas, and 
 
 Fruits 
 
 Fresh 
 
 Vegetables 
 
 Fresh 
 
 - 2.41f 
 
 - 22.81 
 +262.06 
 
 
 - 49.61 
 
 Flour and cereal 
 
 - 51.18 
 
 Sugar and sweeten- 
 
 + 25.14 
 
 Coffee, tea, and 
 
 + 62.50 
 
 
 
 Total 
 
 1,592.0 
 
 100 
 
 1,512.0 
 
 100 
 
 1,480.0 
 
 100 
 
 100 
 
 - 10.80 
 
 
 
 * Preliminary. 
 
 t Since this pertains to pounds of fruits and vegetables purchased at the retail store, this datum may be somewhat 
 misleading. The greatly increased consumption of processed fruits and vegetables indicates that less wastage is now 
 purchased with the food product. Therefore, "actual" fruit and vegetable consumption may have increased while 
 pounds of fruits and vegetable products purchased has decreased. Rising incomes during this period provide an 
 additional basis for this explanation. 
 
 Source: U. S. Department of Agriculture, 1965c, pp. 18-19. 
 
 CHARACTERISTICS OF THE RETAIL 
 FOOD INDUSTRY 
 
 According to the 1964 Census, retail food 
 store sales amounted to slightly more than 
 $57 billion in 1963, or about 24 per cent 
 of all retail transactions. The 1963 volume 
 was handled by 319,433 outlets, or about 
 23 per cent of all retail trade outlets. The 
 food stores employed 1,274,395 paid work- 
 ers, or about 15 per cent of those in all 
 kinds of retail outlets (table 2). 
 
 If the 1939 and 1963 annual dollar sales 
 are adjusted to a 1947-1949 price index, 
 food store sales more than doubled dur- 
 ing the 24-year period. However, the in- 
 creased volume was handled by 43 per 
 cent fewer stores. Significantly the domes- 
 tically produced food sold through these 
 stores was produced on 6.9 million farms 
 
 in 1939 and 3.5 million farms in 1963, a 
 decrease of about 50 per cent. 
 
 Because the retail food industry of 1963 
 is a product of a changing technology and 
 changing needs of its customers, a few 
 comments of a historical nature seem ap- 
 propriate to an understanding of the 
 process by which our present-day retail 
 food industry became what it is. 
 
 The present system of food distribution 
 in the United States has been associated 
 with our transition from a predominantly 
 self-sufficient, rural society to a largely in- 
 dustrial-urban society and with advances 
 in food technology that have made it pos- 
 sible to handle food as it is now done. 
 
 In our present industrial-urban society, 
 
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consumers are almost totally dependent on 
 our food distribution system as a means 
 of maintaining their way of life. Con- 
 versely, the present system reflects, in a 
 large measure, the acceptability to con- 
 sumers of the system and their preferences 
 among a large variety of services made 
 available to them by competing retail firms 
 that make up the system. In view of the 
 demographic and technological changes 
 taking place in the United States, it is rea- 
 sonable to expect a further evolution in 
 all sectors of the food industry, particu- 
 larly the retail sector. The speed with 
 which this change occurs will be deter- 
 mined by the technical and economic ca- 
 pacity of the food industry to stimulate 
 and then fulfill their customers' desires 
 for new products and services. 
 
 The evolutionary processes in food re- 
 tailing are well illustrated by events in 
 the United States during the past 200 
 years. The colonial villages relied on 
 bakers, butchers, and tea and spice mer- 
 chants for items produced outside the 
 home. Later, the itinerant merchant or 
 peddler became the principal supplier of 
 the farmers in the sparsely settled coun- 
 try. As the rural population increased and 
 became more concentrated, the general 
 store type of operation became a feasible 
 source of supply. A further concentration 
 of population in towns and cities made 
 possible the specialty food store — bakery, 
 dairy, fruit and vegetable, and meat — a 
 type of operation in which the individual 
 was both the owner and operator. 
 
 Today, one sees all types of retail food 
 stores. Competition for urban customers 
 has encouraged a reversion to the general 
 store concept on a larger and more pre- 
 tentious scale. In an effort to improve 
 shopping arrangements, encourage "one- 
 stop" shopping, and reduce unit selling 
 costs, food retailers began offering a com- 
 plete line of foods, a wide range of higher- 
 margin household products, cosmetics, 
 wearing apparel, drugs, and hardware. 
 The widespread use of private auto- 
 mobiles also has been a very important 
 factor in expanding the area from which 
 large retail stores can draw customers. 
 
 The practice of selling a wide range of 
 food and nonfood merchandise requires 
 more floor space and equipment than is 
 
 needed by the more conventional grocery 
 store. These large combination stores, 
 often departmentalized, are referred to as 
 the "supermarkets" which now account 
 for the largest percentage of all retail food 
 sales. Zimmerman (1955) defines the super- 
 market as "a highly departmentalized re- 
 tail establishment, dealing in foods and 
 other merchandise, either wholly owned 
 or concession operated, with self-service 
 sales, adequate parking space, and doing 
 a minimum of $250,000 (since doubled) in 
 business annually." The modern super- 
 market embodies the accumulation of pre- 
 vious technological innovations in food 
 retailing and supplements them with im- 
 proved techniques developed by other seg- 
 ments of the nation's economy (Mueller 
 and Garorian, 1961). 
 
 Table 3 illustrates the declining im- 
 portance of the more specialized-type out- 
 let and the growing importance of the 
 combination-type store. Total sales more 
 than doubled for the combination stores 
 from 1948 to 1963, while there was little 
 or no sales increase for the specialized 
 units. However, the number of specialty 
 food stores decreased by only 18.2 per 
 cent; the number of combination stores 
 decreased by 34.8 per cent. 
 
 As the combination-type store grew, 
 both in sales and average store size, more 
 small independent operators went out of 
 business (appendix table A-2). These data 
 also show that because of the large de- 
 crease in the number of combination 
 stores, the specialty-store group was a 
 larger proportion of the total food store 
 group in 1964 than in 1955. Nonetheless, 
 total sales volume is of much greater eco- 
 nomic significance than number, and illus- 
 trates better the declining importance of 
 the specialty food store. 
 
 Figure 4 shows the relative growth in 
 chain store outlets compared to that of 
 the independents. While the number of 
 chain stores increased by 1,960 stores be- 
 tween 1955 and 1964, the number of all 
 food stores decreased by 123,640. 
 
 The trend towards larger food stores is 
 shown in appendix table A-3. In 1953 food 
 sales in the small-stores group constituted 
 about 20 per cent of total sales and those 
 in supermarkets were 48.3 per cent. In 
 1961, the last year for which comparable 
 
 [12] 
 
Table 3 
 
 RETAIL ESTABLISHMENTS AND SALES, BY KIND OF STORES, 
 
 SELECTED YEARS 
 
 Kind of store 
 
 Number of establishments 
 
 Sales 
 
 1948 
 
 1954 
 
 1958 
 
 1963 
 
 1948 
 
 1954 
 
 1958 
 
 1963 
 
 
 350,754 
 23,920 
 4,517 
 
 13,482 
 
 27,165 
 19,500 
 
 7,917 
 13.658 
 
 279,440 
 
 22,896 
 
 4,458 
 
 13,136 
 
 20,507 
 19,034 
 8,132 
 13,777 
 
 259,796 
 
 23,844 
 
 4,339 
 
 12,689 
 
 17,593 
 19,235 
 
 NA 
 18,012 
 
 244,838 
 16,457 
 3,630 
 
 8,874 
 
 14,979 
 
 18,631 
 
 NA 
 
 12,024 
 
 thousand dollars 
 
 Grocery and combination 
 
 24,729,717 
 
 1,641,087 
 
 132,331 
 
 394,602 
 
 586,592 
 722,761 
 308,336 
 092,438 
 
 34,420,764 
 
 1,943,969 
 
 184,148 
 
 484,503 
 
 567,955 
 862,290 
 479,787 
 752,439 
 
 43,696,343 
 
 2,327,038 
 
 193,748 
 
 505,355 
 
 527,752 
 
 904,981 
 
 NA 
 
 867,116 
 
 52,565,955 
 
 
 1,529,814 
 
 
 175,666 
 
 Fruit and vegetable 
 
 412,292 
 
 Candy, nut, and confec- 
 
 499,268 
 
 
 1,080,282 
 
 
 NA 
 
 
 815,909 
 
 
 
 Total 
 
 460,913 
 
 381,380 
 
 355,508 
 
 319,433 
 
 29,207,864 
 
 39,695,855 
 
 49,022,333 
 
 57,079,186 
 
 
 
 Source: U. S. Bureau of the Census, 1954, 1958, and 1963. 
 
 1955 1956 1957 1958 1959 1960 1961 1962 1963 1964 
 
 Fig. 4. Composition of total food stores. 
 Source: Appendix table A— 2. 
 
 data are available, the small-store group 
 accounted for about 8 per cent of total 
 sales and supermarkets for 70 per cent. A 
 subsequent (1962) reclassification of stores 
 into small (up to $150,000 in annual sales), 
 superette ($150,000 to $500,000), and 
 supermarkets (more than $500,000) places 
 many of the former superette stores in the 
 small-store class, thereby affecting total 
 sales of all three groups. Despite this 
 change in classification, the supermarkets 
 held roughly 68 per cent of the total an- 
 
 Table 4 
 
 GROWTH IN NUMBER OF 
 
 SUPERMARKETS 
 
 Year 
 
 Number of 
 supermarkets* 
 
 Size definition 
 of supermarket 
 (minimum annual 
 gross sales) 
 
 1952 
 
 1954 
 
 16,500 
 21,440 
 24,700 
 27,100 
 28,800 
 29,900 
 32,000 
 33,300 
 30, 100 
 27,125 
 28,400 
 30,900 
 
 dollars 
 
 375,000 
 375,000 
 375 000 
 
 1955 
 
 1956 
 
 375 000 
 
 1957 
 
 375 000 
 
 1958 
 
 1959 
 
 375,000 
 375,000 
 375 000 
 
 1960 
 
 1961 
 
 375,000 
 500,000 
 500,000 
 500,000 
 
 1962 
 
 1963 
 
 1964 
 
 
 * Progressive Grocer, 1955-1965, and 1963. 
 
 [13] 
 
Table 5 
 
 NONFOOD SALES IN SUPERMARKETS AS A PERCENTAGE OF 
 
 TOTAL SALES, 1958-1963 
 
 Item 
 
 Health and beauty aids 
 
 Housewares 
 
 Magazines and books. . . 
 
 Soft goods 
 
 Toys 
 
 Phonograph records 
 Stationery 
 
 All nonfoods 
 
 Percentage of total sales 
 
 1958 
 
 2.28 
 .74 
 .21 
 .26 
 .10 
 .10 
 
 3.77 
 
 1959 
 
 2.38 
 .81 
 .22 
 .30 
 .11 
 .11 
 .09 
 
 4.02 
 
 1960 
 
 1.47 
 .84 
 .23 
 .33 
 .13 
 .13 
 .10 
 
 4.23 
 
 1961 
 
 2.57 
 .88 
 .26 
 .36 
 .15 
 .13 
 .11 
 
 4.45 
 
 1962 
 
 2.75 
 .93 
 .27 
 .40 
 .15 
 .13 
 .12 
 
 4.75 
 
 1963* 
 
 2.29 
 .83 
 .43 
 .56 
 
 NA 
 
 NA 
 
 t 
 
 NA 
 
 * Food chains only. 
 
 t Included in "Magazines and books." 
 
 Source: Progressive Grocer, 1952-1964. 
 
 nual grocery store sales. This increasing 
 importance of the large supermarket is 
 even more obvious in table 4. 
 
 As mentioned, inherent in the present- 
 day supermarket is a characteristic of the 
 
 old general store — that of selling various 
 nonfood products, which amounted in 
 1962 to 4.75 per cent of sales, with a con- 
 tinuing upward trend indicated (table 5). 
 The most common nonfood products sold 
 
 Table 6 
 
 SALES OF CHAIN AND INDEPENDENT STORES, 
 
 BY SIZE GROUP FOR SELECTED YEARS 
 
 Size of store 
 
 Sales per store 
 
 1953 
 
 1958 
 
 1959 
 
 1960 
 
 1961 
 
 1962 
 
 
 dollars 
 
 Small* 
 
 70,000 
 24,945 
 25,110 
 
 272,674 
 141,210 
 157,224 
 
 976,699 
 779,070 
 
 886,772 
 
 62,500 
 17,949 
 18,040 
 
 297,297 
 191,964 
 198,492 
 
 1,143,791 
 1,054,795 
 1,096,667 
 
 62,500 
 17,448 
 17,541 
 
 306,452 
 211,321 
 216,578 
 
 1,141,975 
 1,031,646 
 1,087,500 
 
 62,500 
 
 25,298 
 25,386 
 
 300,000 
 204,301 
 208,405 
 
 1,150,585 
 1,018,519 
 1,086,336 
 
 NA 
 
 NA 
 
 26,541 
 
 NA 
 
 NA 
 
 217,153 
 
 NA 
 
 NA 
 
 1,269,103 
 
 82,143 
 
 
 58,371 
 
 Total 
 
 58,738 
 
 Superette* 
 
 301,786 
 
 
 274,490 
 
 Total 
 
 Supermarket* 
 
 277,289 
 1,501,701 
 
 
 1,292,683 
 
 Total 
 
 1,401,292 
 
 
 
 
 95,739 
 
 169,474 
 
 179,412 
 
 202,308 
 
 218,850 
 
 238,237 
 
 
 
 * 1962: Small, under $150,000 annual gross sales; Superette, $150-$500,000; Supermarket, $500,000 and more. Prior 
 to 1962: Small, under $75,000; Superette, $75-$375,000; Supermarket, $375,000. 
 Source: Appendix table A-3. 
 
 [14] 
 
Table 7 
 
 UNITED STATES POPULATION, 
 
 GROCERY STORES, AND 
 
 POPULATION PER STORE 
 
 FOR SELECTED YEARS 
 
 Year 
 
 Popula- 
 tion 
 
 Grocery 
 stores 
 
 Popula- 
 tion per 
 store 
 
 Increase 
 from 
 1940 
 
 1940 
 
 million 
 
 132.1 
 139.9 
 151.7 
 175.4 
 177.1 
 180.0 
 183.0 
 185.8 
 
 thousand 
 
 444.9 
 397.0 
 400.7 
 285.0 
 280.5 
 260.1 
 248.8 
 235.9 
 
 297 
 352 
 378 
 615 
 631 
 692 
 736 
 788 
 
 index 
 100 
 
 1945 
 
 119 
 
 1950 
 
 127 
 
 1958 
 
 207 
 
 1959 
 
 212 
 
 I960 
 
 233 
 
 1961 
 
 248 
 
 1962 
 
 265 
 
 
 
 Source: U. S. Bureau of the Census, 1963, and 
 Progressive Grocer, 1952-1964. 
 
 in today's store are classified as "Health 
 and Beauty Aids," including such high- 
 margin items as cosmetics, toiletries, and 
 drugs (Progressive Grocer, 1959). 
 
 As early as 1957, more than half of the 
 existing food stores sold drugs and cos- 
 metics, magazines, housewares, stationery, 
 toys, beer, hardware, store-baked goods, 
 dietetic foods, soft goods, greeting cards, 
 books, and garden supplies. To accommo- 
 date this increase in the items offered, the 
 stores have continually grown larger. The 
 average undeflated dollar sales per store 
 almost doubled in each of the three classi- 
 fications during the past 10 years (table 
 6) 2 , and the average population per store 
 rose from 297 persons in 1940 to 788 per- 
 sons in 1962 (table 7). 
 
 THE RETAIL FOOD CHAINS 
 
 Because of the controversy surrounding 
 the rising economic power of the national 
 food chains and their policies and oper- 
 ating practices (Ginsburg, 1966), this 
 analysis emphasizes the position of the 
 chains in the structure of the industry. 
 
 The term "retail food chain" used in 
 this report refers to a firm operating more 
 than one retail outlet, even though the 
 United States Census classification in- 
 cludes firms with 1 1 or more outlets. The 
 retail firm may or may not be integrated 
 back to its source of supply of merchan- 
 dise. The corporate chain, which is the 
 most common form of ownership, is a 
 
 centrally owned and controlled, multi- 
 unit firm, performing both the buying 
 and selling functions in retailing. Such a 
 firm may be local, regional, or national, 
 depending on its area of operation. 
 Neither independently owned, single- 
 store firms which associate themselves to- 
 gether for cooperative buying, advertis- 
 ing, and public relations, nor wholesaler- 
 sponsored buying groups are considered 
 as chains in our study These groups are 
 referred to as "affiliated" stores. Single- 
 store firms without such a relationship 
 with wholesalers or other retailers are re- 
 ferred to as "unaffiliated" stores. 
 
 Table 8 
 CHAIN EXPANSION PATTERN, BY SIZE GROUPS, 1953-1964 
 
 Number of 
 stores per 
 
 Number of chains 
 in group 
 
 Change in 
 number 
 
 Number of stores 
 operated by groups 
 
 Change in 
 number 
 
 Average number of 
 stores per chain 
 
 chain 
 
 1953 
 
 1964 
 
 1953 to 1964 
 
 1953 
 
 1964 
 
 1953 to 1964 
 
 1953 
 
 1964 
 
 2-3 
 
 2,013 
 
 587 
 171 
 85 
 23 
 
 2,509 
 
 648 
 
 201 
 
 83 
 
 30 
 
 +496 
 + 61 
 + 30 
 - 2 
 
 + 7 
 
 4,654 
 3,040 
 2,620 
 3,449 
 14,115 
 
 5,650 
 3,448 
 2,916 
 4,178 
 17,058 
 
 + 996 
 + 408 
 + 296 
 + 729 
 +2,943 
 
 2.31 
 5.18 
 15.32 
 40.58 
 613.70 
 
 2.25 
 
 4-9 
 
 5 32 
 
 10-25 
 
 14 51 
 
 26-99 
 
 50.34 
 
 100 and more. . . . 
 
 568.60 
 
 Source: Mooney, 1964, p. 38. 
 
 The retail food price level rose about 8 per cent during this period. 
 
 [15] 
 
Table 8 indicates that the 2- and 3-store 
 chains increased in number more than 
 other size groups between 1953-1964. The 
 2- and 3-store firms and the 26- to 99-store 
 firms had the greatest percentage increase 
 in the number of store outlets. However, 
 the chains with more than 100 stores had 
 the greatest increase in actual store out- 
 lets. 
 
 Data from appendix table A-3 and 
 table 9 show that the chains have been 
 steadily improving their position relative 
 to the independents as far as the number 
 of stores operated by the two groups is 
 concerned. Even though chains operate 
 only a small part of all grocery stores, 
 their 8.7 per cent of the total grocery and 
 combination stores now accounts for 41.2 
 per cent of total sales for that group. 
 
 Table 9 
 
 RELATIVE IMPORTANCE OF CHAINS 
 
 VERSUS INDEPENDENT GROCERY 
 
 AND COMBINATION STORES 
 
 Percentage of total grocery and combination stores 
 
 
 1953 
 
 1958 
 
 1959 
 
 1960 
 
 1961 
 
 1962 
 
 Chain 
 
 Independent . . . 
 
 5.6 
 94.4 
 
 6.8 
 93.2 
 
 7.0 
 93.0 
 
 7.9 
 92.1 
 
 NA 
 NA 
 
 8.7 
 91.3 
 
 Percentage of total grocery and combination store sales 
 
 
 1953 
 
 1958 
 
 1959 
 
 1960 
 
 1961 
 
 1962 
 
 
 36.0 
 64.0 
 
 38.7 
 61.3 
 
 38.8 
 61.3 
 
 38.9 
 61.2 
 
 NA 
 
 NA 
 
 41.2 
 
 Independent . . . 
 
 59.8 
 
 Source: Appendix table A-3. 
 
 Table 10 
 
 GROCERY SALES BY MAJOR CHAINS AS A PERCENTAGE OF 
 
 ALL GROCERY STORE SALES FOR SELECTED YEARS 
 
 Year 
 
 A&P 
 
 Safeway 
 
 Kroger 
 
 Amer- 
 ican 
 
 Total 
 
 of 4 
 
 largest 
 
 Second 
 4 chains 
 
 Next 12 
 chains 
 
 Total of 
 top 20 
 chains 
 
 Other 
 chains 
 
 All 
 
 chains 
 
 
 ■per cent 
 
 1929 
 
 14.3 
 13.7 
 13.4 
 14.4 
 12.1 
 
 9.9 
 10.3 
 10.0 
 10.3 
 11.4 
 
 11.5 
 11.7 
 12.0 
 11.2 
 
 11.7 
 
 11.9 
 11.8 
 11.7 
 11.4 
 11.2 
 11.4 
 
 9.4 
 
 8.9 
 8.9 
 8.5 
 
 2.9 
 4.6 
 4.8 
 4.9 
 5.0 
 
 4.4 
 4.1 
 4.6 
 4.6 
 5.0 
 
 5.2 
 
 4.8 
 4.6 
 4.8 
 5.1 
 
 5.2 
 5.2 
 5.2 
 5.1 
 5.0 
 5.0 
 
 4.4 
 4.3 
 4.3 
 4.1 
 
 3.9 
 3.6 
 3.1 
 3.2 
 3.2 
 
 3.2 
 3.3 
 3.2 
 3.1 
 3.4 
 
 3.3 
 3.3 
 3.3 
 3.3 
 3.3 
 
 3.2 
 3.2 
 3.3 
 3.8 
 3.9 
 4.0 
 
 3.5 
 3.3 
 3.1 
 3.2 
 
 2.0 
 
 1.8 
 1.7 
 1.8 
 1.7 
 
 1.6 
 1.7 
 1.6 
 1.7 
 1.7 
 
 1.7 
 1.7 
 1.7 
 1.7 
 1.6 
 
 1.8 
 1.8 
 1.8 
 2.0 
 2.0 
 2.0 
 
 1.6 
 1.7 
 1.7 
 1.7 
 
 23.1 
 23.7 
 23.0 
 24.3 
 22.0 
 
 19.1 
 19.4 
 19.4 
 19.7 
 21.5 
 
 21.7 
 21.5 
 21.7 
 21.0 
 21.7 
 
 22.0 
 22.0 
 22.0 
 22.3 
 22.1 
 22.4 
 
 19.0 
 18.2 
 18.1 
 17.4 
 
 3.6 
 3.6 
 3.2 
 3.4 
 3.4 
 
 3.0 
 3.1 
 3.2 
 3.5 
 3.7 
 
 3.8 
 3.9 
 4.1 
 4.1 
 
 4.2 
 
 4.5 
 4.8 
 5.3 
 5.6 
 5.7 
 6.0 
 
 5.1 
 5.1 
 5.2 
 5.5 
 
 3.0 
 
 2.8 
 2.6 
 
 2.5 
 2.7 
 3.1 
 3.2 
 3.3 
 
 3.3 
 3.7 
 4.1 
 4.1 
 4.5 
 
 4.8 
 5.1 
 5.8 
 6.6 
 6.8 
 7.2 
 
 5.8 
 6.0 
 6.1 
 6.3 
 
 29.2 
 30.5 
 28.0 
 
 24.6 
 25.2 
 25.7 
 26.4 
 28.5 
 
 28.8 
 29.1 
 29.9 
 29.2 
 30.4 
 
 31.3 
 31.9 
 33.1 
 34.5 
 34.6 
 35.6 
 
 29.9 
 29.3 
 29.3 
 29.2 
 
 8.2 
 8.6 
 9.5 
 
 8.2 
 9.3 
 7.6 
 7.7 
 9.3 
 
 8.8 
 9.7 
 8.6 
 6.9 
 7.2 
 
 7.7 
 8.2 
 7.9 
 7.5 
 7.4 
 7.4 
 
 6.1 
 8.0 
 
 8.2 
 8.3 
 
 
 1935 
 
 
 1940 
 
 37.4 
 
 1941 
 
 39.1 
 
 1942 
 
 37.5 
 
 1943 
 
 32.8 
 
 1944 
 
 34.5 
 
 1945 
 
 33.3 
 
 1946 
 
 34.1 
 
 1947 
 
 37.8 
 
 1948 
 
 37.6 
 
 1949 
 
 38.8 
 
 1950 
 
 38.5 
 
 1951 
 
 36.1 
 
 1952 
 
 37.6 
 
 1953 
 
 39.0 
 
 1954 
 
 40.1 
 
 1955 
 
 41.0 
 
 1956 
 
 42.0 
 
 1957 
 
 42.0 
 
 1958 
 
 43.0 
 
 1959 
 
 36.0 
 
 I960 
 
 37.2 
 
 1961 
 
 37.5 
 
 1962 
 
 37.5 
 
 
 
 Source: Mueller and Garorian, 1961, and Progressive Grocer, 1952-1964. 
 
 [16] 
 
IUU 
 
 95 
 
 - 
 
 
 90 
 
 
 
 85 
 
 
 Chains 
 
 80 
 
 
 
 75 
 
 
 
 70 
 
 
 
 65 
 
 - 
 
 
 60 
 
 7/ f /////// f /777J777777TTT 
 
 ^ 55 
 
 o 
 
 
 /////// Unaffiliated Independents ////// t 
 
 o 
 
 !: so 
 
 - 
 
 
 £ 45 
 
 
 
 I 40 
 
 
 
 35 
 
 
 / Lr 
 
 30 
 
 
 / ^^ 
 
 25 
 
 
 Affiliated Independents 
 
 20 
 
 
 
 15 
 
 
 
 10 
 
 
 
 5 
 
 
 
 
 
 
 1 1 1 
 
 1956 
 
 1958 
 
 1963 
 
 Fig. 5. Distribution of total U. S. grocery store sales. 
 Source: Progressive Grocer, 1952-1964. 
 
 Among the nation's largest food chains, 
 A & P has been and still is the largest 
 (table 10). This dominance is no longer 
 so noticeable, its share having decreased 
 from 14.3 per cent in 1929 to 8.5 per cent 
 in 1962. Safeway 's share rose from 2.9 per 
 cent in 1929 to 4.07 per cent in 1962. The 
 share of the total sales of the four largest 
 chains decreased from 23 per cent to 17.4 
 per cent during that period. The ninth 
 through the twentieth largest chains were 
 the most active with respect to fluctua- 
 tions in their sales levels, having more 
 than doubled their share of total grocery 
 sales from 1941 to 1962. 
 
 When comparing chain store food sales 
 with those of the affiliated and unaffili- 
 ated independents, one finds that the sales 
 of affiliated independent stores have in- 
 creased proportionately, even more than 
 chain store sales. The share of the un- 
 
 affiliated independents has continued to 
 decline in relation to the other groups 
 (figure 5). 
 
 Growth characteristics of chains 
 
 The 30 major food chains selected for 
 this study accounted for about one-third 
 of all grocery store sales in 1963. Table 11 
 ranks them according to their annual sales 
 within the chain store group for selected 
 years, beginning in 1940. 
 
 Table 12 shows the relative size of the 
 30 major chains and the estimated per- 
 centage of all sales made by all food 
 stores during 1963. 
 
 Growth Indices. As stated, the 30 
 chains were divided into three size groups 
 — small, medium, and large — of 10 chains 
 each. Both the net sales and the number 
 of stores for each chain for the 1953-1963 
 period were converted into indices, with 
 
 [17] 
 
Table 11 
 
 DISTRIBUTION OF SALES OF 30 MAJOR FOOD CHAINS AS A PERCENTAGE 
 
 OF TOTAL GROCERY STORE SALES FOR SELECTED YEARS 
 
 Firm 
 
 1940 
 
 1955 
 
 1958 
 
 1959 
 
 1960 
 
 1961 
 
 1962 
 
 1963 
 
 per cent 
 
 The Great Atlantic and Pacific Tea 
 
 Company, Inc 
 
 Safeway Stores, Inc 
 
 The Kroger Company 
 
 American Variety Stores 
 
 National Tea Company 
 
 Food Fair Stores, Inc 
 
 Winn Dixie Stores, Inc 
 
 First National Stores 
 
 The Grand Union Company 
 
 Colonial Stores, Inc 
 
 Jewel Tea Company, Inc 
 
 Wrigley Supermarkets 
 
 Loblaw, Inc 
 
 Stop and Shop, Inc 
 
 Penn Fruit Company, Inc 
 
 Thirftimart, Inc 
 
 Red Owl Stores, Inc 
 
 H. C. Bohack Company, Inc 
 
 Lucky Stores, Inc 
 
 J. Weingarten, Inc 
 
 Mayfair Super Markets, Inc 
 
 Thorofare Markets, Inc 
 
 Fisher Foods, Inc 
 
 Purity Stores, Inc 
 
 Market Basket 
 
 Shopping Bag Supermarkets 
 
 Daitch Shopwell 
 
 Alpha Beta Stores 
 
 Food Mart, Inc 
 
 Marsh Supermarkets, Inc 
 
 35.8 
 12.8 
 8.3 
 4.0 
 2.0 
 
 .9 
 
 .4 
 
 4.6 
 
 1.1 
 
 1.5 
 
 .9 
 .07 
 
 .7 
 
 .7 
 NA 
 
 .2 
 .4 
 
 .4 
 
 NA 
 NA 
 NA 
 NA 
 NA 
 
 NA 
 NA 
 NA 
 NA 
 
 NA 
 
 29.03 
 13.55 
 8.55 
 4.38 
 4.04 
 
 2.88 
 1.83 
 3.30 
 1.54 
 2.66 
 
 1.93 
 
 NA 
 1.33 
 
 NA 
 .76 
 
 .37 
 .79 
 .95 
 .31 
 .55 
 .47 
 .57 
 .60 
 .65 
 
 .45 
 
 .34 
 .32 
 .12 
 .13 
 
 26.6 
 11.6 
 9.3 
 4.6 
 4.1 
 
 3.7 
 3.3 
 2.9 
 2.6 
 2.3 
 
 2.3 
 2.0 
 1.5 
 1.0 
 
 26.16 
 12.24 
 9.84 
 4.49 
 4.26 
 
 3.77 
 3.42 
 2.73 
 2.59 
 2.31 
 
 2.28 
 1.86 
 1.46 
 1.00 
 .86 
 
 1.02 
 .82 
 .92 
 .64 
 .79 
 .57 
 .51 
 .51 
 .49 
 
 NA 
 .43 
 
 NA 
 .30 
 .33 
 
 23.81 
 11.65 
 8.82 
 4.63 
 4.04 
 
 3.64 
 3.40 
 
 2.48 
 2.95 
 2.10 
 
 2.32 
 1.64 
 1.56 
 1.13 
 .79 
 
 .79 
 1.07 
 .81 
 .90 
 .65 
 .96 
 .58 
 .50 
 .48 
 .49 
 
 NA 
 .42 
 
 NA 
 .28 
 .37 
 
 23.79 
 11.51 
 8.36 
 4.59 
 4.03 
 
 3.81 
 3.48 
 2.43 
 2.74 
 2.00 
 
 2.31 
 1.73 
 1.40 
 1.34 
 
 .81 
 1.25 
 .75 
 .91 
 .63 
 1.16 
 .58 
 .49 
 .48 
 .54 
 
 NA 
 .38 
 
 NA 
 .28 
 .36 
 
 22.64 
 10.84 
 8.41 
 4.47 
 4.23 
 
 3.99 
 3.34 
 3.07 
 
 2.77 
 1.94 
 
 2.39 
 1.68 
 2.15 
 1.37 
 
 .75 
 
 1.21 
 
 .76 
 1.00 
 .59 
 1.25 
 .38 
 .45 
 .46 
 .52 
 
 NA 
 .46 
 
 NA 
 .29 
 .35 
 
 22.01 
 10.98 
 
 8.71 
 NA 
 4.38 
 
 4.16 
 3.45 
 3.09 
 2.61 
 1.90 
 
 2.56 
 
 .67 
 
 1.24 
 .79 
 
 1.07 
 .59 
 
 NA 
 .60 
 .41 
 .45 
 
 NA 
 
 NA 
 .52 
 
 NA 
 .35 
 
 Source: Progressive Grocer, 1952-1964. 
 
 1953 as base year. These indices were 
 used to calculate an "expansion ratio" 
 which was obtained by dividing the sales 
 index of a firm for a given year by its 
 index of the number of stores for the 
 same year. The resulting "expansion 
 ratio" becomes a rough measure for the 
 proportional increase in annual sales per 
 store over the observation period. 
 
 Figure 6 shows a fairly consistent in- 
 crease in the average annual net sales for 
 Group I for the period 1953-1963. After 
 1956, the increase for Colonial Stores, 
 Inc., was very small; however, the most 
 revealing fact is that an average of the 
 five largest chains (1-5) had sales expan- 
 
 sion indices lower than the Group I aver- 
 age. This indicates that, with respect to 
 sales, the nation's five largest chains were 
 maintaining a lower sales growth pro- 
 portional to the average of Group I. It 
 must be noted, however, that a base pe- 
 riod analysis gives an advantage to firms 
 with a smaller base and discloses nothing 
 about increases in absolute sales volume. 
 Food Fair Stores, Inc., and Winn Dixie 
 Stores, Inc., experienced the greatest rela- 
 tive growth in the number of food stores 
 in Group I (figure 7). The number of 
 stores for the two largest chains changed 
 very little, while the absolute number de- 
 creased for three of the ten chains. These 
 
 [18] 
 
Table 12 
 
 PERCENTAGE SHARE OF ALL 1963 GROCERY STORE SALES 
 
 FOR EACH OF THE 30 MAJOR CHAINS 
 
 Chain 
 
 Percentage of 
 
 U. S. grocery 
 
 store sales 
 
 (1963) 
 
 Chain 
 
 Percentage of 
 U. S. grocery- 
 store sales 
 (1963) 
 
 A&P 
 
 Safeway 
 
 Kroger 
 
 American 
 
 National Food 
 Food Fair. . . . 
 Winn Dixie. . . 
 First National 
 Grand Union. 
 
 Jewel Tea 
 
 Loblaw 
 
 Colonial 
 
 Wrigley 
 
 Stop & Shop.. 
 Red Owl 
 
 4.12 
 
 3.27 
 
 1.68(1962) 
 
 1.64 
 
 1.56 
 
 1.29 
 
 1.16 
 
 .81 
 .71 
 .62 
 .62 
 .47 
 
 Mayfair Markets 
 
 Lucky Stores 
 
 Thriftimart 
 
 Bohack 
 
 Penn Fruit 
 
 Weingarten 
 
 Thorofare 
 
 Market Basket. . 
 Daitch Shopwell 
 
 Purity Stores 
 
 Fisher Bros 
 
 Food Mart 
 
 Marsh, Inc 
 
 Shopping Bag. .. 
 Alpha Beta 
 
 .47(1962) 
 .40 
 .34 
 .29 
 .25 
 .22 
 .22 
 
 .20(1962) 
 .19 
 .17 
 .15 
 .13 
 .12 
 NA 
 NA 
 
 Source: Progressive Grocer, 1952-1964. 
 
 store expansion data do not distinguish 
 between new stores and acquired or pur- 
 chased stores, nor do they show the closing 
 of old, small, or inefficient stores. 
 
 As mentioned, those chains in the 
 eleventh through twentieth categories 
 
 seemed to be the most dynamic (figure 
 8). Although the Group II average net 
 sales index moved steadily upward after 
 1953, the sales of individual firms within 
 Group II diverged considerably from the 
 average. Lucky Stores, Inc., and Mayfair 
 
 550 
 
 500 
 
 450 
 
 -400 
 a. 
 
 £350 
 
 ^ 300 
 
 z 
 
 ^250 
 
 4> 
 
 c 
 
 .2 200 
 
 B 
 D 
 
 ^150 
 
 100 
 
 50 
 
 (1) The Great Atlantic and 
 
 Pacific Tea Company , Inc. 
 
 (2) Safeway Stores, Inc. 
 
 (3) The Kroger Company 
 
 (4) American Variety Stores 
 
 (5) National Tea Company 
 
 (6) Food Fair Stores, Inc. 
 
 (7) Winn Dixie Stores, Inc. 
 
 (8) First National Stores 
 
 ( q ) The Grand Union Company 
 (10) Colonial Stores, Inc. 
 — — average 
 
 1953 1954 1955 1956 1957 1958 1959 I960 1961 1962 1963 
 
 Fig. 6. Expansion index of net sales, Group I chains. Source: Appendix table A— 4. 
 
 [19] 
 
500 
 450 
 
 400 
 G 
 
 a. 
 
 3 
 
 J 350 
 
 V) 
 
 I 300 
 >/> 
 
 -5 
 
 I 250 
 
 z 
 
 o 
 
 J 200 
 
 JZ 
 
 I 150 
 
 c 
 a 
 a. 
 
 ■" 100 
 
 50 
 
 - 
 
 (1)A&P (6) Food Fair 
 
 (2) Safeway (7) Winn Dixie 
 
 (3) Kroger (8) First National 
 
 (4) American (9) Grand Union 
 
 (5) National Tea (10) Colonial 
 
 average 
 
 
 - 
 
 
 
 j (6) 
 
 - 
 
 
 
 / ^^ {1) 
 
 .. 1 
 
 
 
 (9) 
 
 --** ' — - _ 
 
 ■ ^) 
 
 ^==-=* ^^ 
 
 
 ■*=-- (10) 
 
 
 
 ~ ^(3) ( 2 ) 
 
 1 1 1 1 
 
 1 1 
 
 *^ (4) (8) 
 1 1 
 
 1953 
 
 1954 
 
 1955 
 
 1956 
 
 1957 
 
 1958 
 
 1959 
 
 1960 
 
 1961 
 
 1962 
 
 1963 
 
 Fig. 7. (above) Expansion index of number of stores, Group I chains. Source: Appendix table A-4 
 Fig. 8. (below) Expansion index of net sales, Group II chains. Source: Appendix table A-4. 
 
 650 
 600 
 550 
 500 
 ^450 
 
 OL 
 3 
 
 o 400 
 
 £ 350 
 
 «> 
 
 z 
 
 *° 300 
 
 250 - 
 
 200 
 
 150 
 
 100 
 
 50 
 
 - 
 
 (11) Jewel Tea Company, Inc. 
 
 (12) Wrigley Supermarkets 
 
 (13) Loblaw, Inc. 
 
 (14) H. C. Bohack Company, Inc. 
 
 (15) Penn Fruit Company, Inc. 
 
 (16) Red Owl Stores 
 
 (17) Lucky Stores, Inc. 
 
 (18) J. Weingarten, Inc. 
 
 (19) Mayfair Super Markets, Inc. 
 
 (20) Thorofare Markets, Inc. 
 — — — — • average 
 
 
 
 Am 
 
 
 
 
 
 .(19) 
 
 
 - 
 
 
 
 
 
 (13) 
 
 - 
 
 
 
 y^'^ / 
 
 1^ 
 
 (20) 
 
 r*/06) 
 
 7^(12) 
 ^-(11) 
 
 (18) 
 "(15) 
 
 ^ — 
 
 
 
 - 
 
 
 
 
 
 . (14) 
 
 1 
 
 1 1 1 
 
 iiii 
 
 1 
 
 1 
 
 1 
 
 1953 
 
 1954 
 
 1055 
 
 1956 
 
 1957 
 
 1<»58 
 
 1959 
 
 I960 
 
 1961 
 
 1962 
 
 1963 
 
 [20] 
 
1953 
 
 1954 
 
 1955 
 
 1956 
 
 Fig. 9. (above) Expansion index of number of stores, Group II chains. Source: Appendix 
 table A-4. Fig. 10. (below) Epansion index of net sales, Group III chains. Source: Appendix 
 table A-4. 
 
 700 
 
 (21) Fisher Foods, Inc. 
 
 
 
 
 650 
 
 (22) Purity Stores, Inc. 
 
 (23) Thriftimort, Inc. 
 
 (24) Market Basket 
 
 
 
 (29) 
 
 600 
 
 — (25) Shopping Bag Superma 
 (26) Daitch Shopwell 
 
 rkets 
 
 
 
 550 
 
 (27) Alpha Beta Stores 
 
 (28) Food Mart, Inc. 
 
 (29) Marsh Supermarkets, 1 
 
 rtc. / 
 
 
 (26) 
 // (28) 
 
 I 450 
 
 (30) A. J. Bay less Markets 
 
 , Inc. / 
 
 
 
 — average 
 
 
 
 / /^ (23) 
 
 -5 400 
 
 
 
 
 
 " 350 
 
 o 
 
 
 
 
 
 i 300 
 
 
 
 
 
 c 
 o 
 
 1 250 
 
 o 
 
 a. 
 
 ^ 200 
 
 150 
 
 /^^^"^ JLt^^^^ 
 
 / J27) 
 
 ^<^Z^^ 
 
 (30) ,' 
 
 -~~ (24) 
 
 . (21) -(77, 
 
 100 
 
 
 Z^^^ (25) 
 
 
 
 50 
 
 
 
 
 
 
 
 i i i i 
 
 , 
 
 i I l 
 
 i i 
 
 1953 
 
 1954 
 
 1955 
 
 1956 
 
 1957 
 
 1958 
 
 1959 1960 
 
 1961 
 
 1962 
 
 1963 
 
 [21] 
 
600 
 
 
 (21) Fisher Bros. 
 
 (26) Daitch Shopwell 
 
 550 
 
 (22) Purity Stores 
 
 (27) Alpha Beta 
 
 
 (23) Thriftimart 
 
 (28) Food Mart 
 
 
 (24) Market Basket 
 
 (29) Marsh, Inc. 
 
 500 
 
 - (25) Shopping Bag 
 
 (30) Bayless 
 
 ^450 
 
 
 
 1 
 
 
 
 a. 
 
 
 
 2 400 
 
 
 
 o 
 
 
 
 average 
 
 1953 1954 1955 1956 1957 1958 1959 1960 1961 1962 1963 
 
 Fig. 11. Expansion index of number of stores, Group III chains. Source: Appendix table A-4. 
 
 Super Markets, Inc., experienced the 
 greatest proportional growth; H. C. Bo- 
 hack Co., Inc., experienced the least. 
 Chains 13, 17, and 19 seem to have ex- 
 panded sales at an increasing rate, while 
 
 the remaining firms' expansion rate 
 tapered slightly in more recent years. 
 
 Except for Bohack, Group II chains in- 
 creased their number of stores during the 
 observation period. Chains 15, 17, and 19 
 
 Fig. 12. Expansion index of net sales and number of stores, by group. Source: Appendix table A-4. 
 
 400 
 
 350 
 
 1 300 
 
 o 
 
 c5 
 -£"250 
 
 01 
 
 -a 
 
 1200 
 
 o 
 
 Ui 
 
 c 
 
 1 150 
 
 UJ 
 
 1 100 
 
 < 
 
 50 
 
 
 1953 
 
 Net Sales 
 Number of Stores 
 
 m 
 i 
 
 
 1954 
 
 1955 
 
 1956 
 
 1957 
 
 1958 
 
 [22] 
 
 1959 
 
 1960 
 
 1961 
 
 1962 
 
 1963 
 
were near the top of the expansion, while 
 14 was at the bottom (figure 9). 
 
 Group III showed a less erratic expan- 
 sion of net sales than Group II. Never- 
 theless, there were substantial differences 
 among individual chains within Group 
 III. As shown in figure 10, the ten chains 
 seem to fall into three general growth 
 patterns. Chains 21 and 22 had very little 
 proportional growth in net sales, chains 
 24, 27, and 30 experienced nominal 
 growth and the remaining four chains had 
 net sales growth far above the group aver- 
 age. For all three groups, 1955-1959 was 
 the period of greatest sales expansion and 
 1960-1962 the period of greatest irregu- 
 larity. 
 
 In figure 11, the expansion in number 
 of stores generally falls in the same three 
 growth patterns mentioned above. How- 
 ever, chains 21 and 22 had very little 
 growth of net sales and actually had a 
 decline in the number of stores. This 
 raises the question of whether the small 
 proportional sales growth was the cause 
 
 or effect of the decrease in the number of 
 stores. The decline in store numbers seems 
 to have picked up momentum during the 
 latter part of the observation period. In 
 view of this, one would suspect that the 
 relatively small sales gain in the earlier 
 years actually caused these chains to close, 
 merge, or sell some of their old or unpro- 
 ductive operations. 
 
 Figure 12 shows the average expansion 
 index of net sales and number of stores 
 by group. In almost every year of the ob- 
 servation period, the proportional expan- 
 sion rates for the two largest groups were 
 lower than those of the smaller group. 
 
 To reiterate: The expansion ratio is the 
 quotient of the net food sales index di- 
 vided by the number of stores index for a 
 given firm. Hence, the quotient will be 
 affected by disproportionate changes in 
 the divisor and dividend. Figure 13 shows 
 the 1963 expansion ratios for all 30 of 
 the nation's larger food chains. The aver- 
 age expansion ratio for all 30 chains is 
 approximately 1.6 which, loosely inter- 
 
 Fig. 13. Expansion ratio, for all chains, groups, and individual chains, 1963. 
 Source: Appendix table A-5. 
 
 12 3 4 5 6 7 
 
 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 
 
 Number of Chains 
 Largest > Smallest 
 
 [23 1 
 
preted, indicates that average sales per 
 store in the 30 chains have increased 60 
 per cent from 1953 to 1963. This figure is 
 consistent with the increases in the aver- 
 age physical size of food stores and average 
 number of items sold per store. For ex- 
 ample, over the same period, the average 
 number of items sold per store increased 
 about 45 per cent and store size increased 
 about 35 per cent. 
 
 The average expansion ratio of Group 
 
 I was above that of Group II, but both 
 were below Group III. In general, it seems 
 that the smaller chains made the greatest 
 advances in sales per store, while Group 
 
 II had the lowest increase in sales per 
 store. This should not seem overly sur- 
 prising in view of the great increases in 
 both sales and number of stores in 
 Group II. 
 
 There is little or no similarity in the 
 expansion ratios among chains of like 
 size. Group II has the greatest range of 
 variation, as would be expected, in view 
 of the dynamic characteristics of this 
 group. 
 
 Effects of growth 
 
 In view of the different rates of growth 
 of the three groups of chains, the re- 
 searchers turned their attention to the 
 relationship between growth and the fol- 
 lowing important financial items: 
 
 • Profits, 
 
 • Merchandise inventory, 
 
 • Fixed assets (buildings and 
 equipment), 
 
 • Accounts payable, and 
 
 • Net worth. 
 
 The graphic presentation in figures 14 
 through 18 depicts the effects of growth 
 of chains by size groups on the financial 
 factors listed above for the period 1953- 
 1963. 
 
 Profits. Profit rates per dollar sales for 
 each of the three size groups rose sharply 
 from 1953 through 1955 and leveled off 
 through 1957 (figure 14). A significant de- 
 cline occurred in Group III chains from 
 1957-1961. A similar though less drastic 
 decline affected Group II chains begin- 
 ning in 1959. The larger chains in Group 
 I, collectively, showed much less decline 
 
 than the small and medium chains. The 
 researchers do not have a complete ex- 
 planation for the sharp decline in net 
 profits in two of the groups. In their 
 judgment, however, the pressure of rising 
 labor costs, technological changes requir- 
 ing greater capital investment, and price- 
 quality competition for customers and 
 sales volume, which prevented prices from 
 going much above those of the Group I 
 chains, are the main reasons for the de- 
 cline. 
 
 Merchandise inventory. For 1953, and 
 from 1957 onward, the Group II chains' 
 merchandise inventory as a percentage of 
 current assets averaged lower than the 
 other groups (figure 15). A factor that 
 could have affected the inventory policy 
 of the Group II chains was their greater 
 reliance on wholesalers to perform the 
 merchandise storage function. On an aver- 
 age, the 30 chains studied maintained a 
 sales inventory ratio of 2 to 1 (see pages 
 26 to 29). 
 
 Fixed assets as a percentage of total 
 assets generally rose for all chain groups 
 from 1953 to 1960-1961, and for groups 
 I and III the trend was upward through 
 1963. The sharp drop of percentage in 
 Group II is explained partly by a rela- 
 tively greater increase in leasing rather 
 than ownership of buildings used in the 
 merchandising operations (figure 16). 
 
 Accounts payable was the principal item 
 of indebtedness in each of the chains 
 studied. The rising importance of this 
 method of financing expansion of food 
 chains is shown in figure 17. After 1953, 
 groups I and II began to rely more on 
 open accounts as a source of credit financ- 
 ing. Group III also sharply increased its 
 use of this form of credit after 1957. 
 
 Net worth. This marked increase in 
 creditor financing by accounts payable 
 should be considered in conjunction with 
 the relative decline in net worth or 
 owners' equities in relation to the total 
 assets used by the business (figure 18). For 
 Group II, a sharp downward change in 
 owner financing began in 1955. A less 
 drastic downward change occurred for 
 Group III after 1959. Group I chains 
 financed their expansion by increasing 
 both forms of equities. The rapid growth 
 of groups II and III chains would appear 
 
 [24] 
 
1953 1954 1955 1956 1957 1958 1959 1960 1961 1962 1963 1964 
 
 Fig. 14. (above) Net profit as a percentage of total sales. Source: Fairchild Publications, Inc., 1953- 
 1963. Fig. 15. (below) Merchandise inventory as a percentage of current assets. Source: Fairchild Publica- 
 tion, Inc., 1953-1963. 
 
 1953 1954 1955 1956 1957 1958 1959 1960 1961 1962 1963 1964 
 
 [25] 
 
39 
 38 
 
 - 
 
 ^1 
 
 37 
 
 
 / / \ / 
 
 36 
 
 
 1 / \ 
 
 
 A 
 
 / / / * /*■ 
 
 35 
 
 " 
 
 / 1 r ^' 
 
 34 
 
 / \ 
 
 / // 
 
 
 J A 
 
 !/:j 
 
 33 
 
 / if 
 / /I 
 
 
 
 / A 
 
 
 32 
 
 - / / 
 
 
 31 
 
 // 
 /7 
 
 
 30 
 
 ^/ 
 
 
 o1 
 
 1 1 1 
 
 i i i i i i i 
 
 1953 1954 1955 1956 1957 1958 1959 1960 1961 1962 1963 1964 
 
 Fig. 16. Fixed assets as a percentage of total assets. Source: Fairchild Publications, Inc., 1953-1963. 
 
 to be supported by liberal credit from 
 grocery wholesalers and /or brand-product 
 manufacturers who were greatly depend- 
 ent on small- and medium-size chains for 
 access to consumers. 
 
 Financial interrelationships 
 
 The financial reports of the 30 chains 
 studied provide one basis for a better 
 understanding of certain management 
 practices and their results. For this phase 
 of the analysis, the three-group classifica- 
 tion of chains (I, II, and III) is again 
 used. 
 
 While the preceding discussion con- 
 sidered financial trends over time, the fol- 
 lowing appraises certain financial inter- 
 relationships which might exist within a 
 chain or group of chains, irrespective of 
 
 time. For example, this analysis attempts 
 to determine what relationship one finan- 
 cial factor has with another and how this 
 relationship differs among chains and 
 groups of chains. 
 
 Regression analyses (appendix C) were 
 used to find the following relationships: 
 
 • Net dollar sales as a function of the 
 number of stores, 
 
 • Net dollar profit as a function of the 
 number of stores, 
 
 • Inventory as a function of net sales, 
 
 • Current assets as a function of inven- 
 tory, 
 
 • Fixed assets as a function of total 
 assets, and 
 
 • Total liabilities as a function of ac- 
 counts payable and current liabili- 
 ties. 
 
 [26] 
 
74 
 
 - 
 
 
 
 
 ,m 
 
 73 
 
 
 
 
 
 / 
 
 72 
 
 - 
 
 
 
 
 71 
 70 
 
 — 
 
 
 
 
 A ■' 
 
 69 
 
 - 
 
 
 
 
 / \ / 
 
 68 
 67 
 66 
 
 
 
 
 / 
 / 
 
 ■J V 
 
 I 
 
 65 
 64 
 
 
 
 
 / / 
 
 c 63 
 u 62 
 
 
 
 
 LA 
 
 
 0> 
 
 tL 61 
 
 60 
 59 
 58 
 57 
 56 
 55 
 54 
 53 
 
 
 A 
 / \ 
 * /* 
 
 s 
 s 
 s 
 
 s 
 
 *-- 
 
 XT 
 
 V 
 
 r 
 
 V// 
 
 52 
 
 
 
 
 
 
 6 
 
 1 
 
 1 1 1 
 
 i i 
 
 1 
 
 1 1 1 1 
 
 1953 1954 1955 1956 1957 1958 1959 1960 1961 1962 1963 1964 
 
 Fig. 17. (above) Accounts payable as a percentage of current liabilities. 
 Source: Fairchild Publications, Inc., 1953—1963. Fig. 18 (below) Net worth as a 
 percentage of total assets. Source: Fairchild Publications, Inc., 1953—1963. 
 
 1953 1954 1955 1956 1957 1958 1959 1960 1961 1962 1963 1964 
 
 [27] 
 
The 30 chains. A condensed presenta- 
 tion of results from the analysis for the 30 
 major retail food chains shows the follow- 
 ing: 
 
 • As expected, a statistically strong, 
 positive relationship was found be- 
 tween net sales and number of 
 stores. Excluding the effects of loca- 
 tion, a chain could expect on an 
 average a total net sales increase of 
 slightly more than $1 million by add- 
 ing one retail outlet. 
 
 • Also, as expected, a positive rela- 
 tionship existed between net profit 
 and number of stores. By increasing 
 the number of stores by one, a chain 
 could expect an increase in total net 
 profit of approximately $11,000. 3 
 Paragraphs 1 and 2 tell us that for 
 every new store, one could expect 
 about 1.1 per cent of net sales to be 
 retained as net profit (11,000 -f- 1,- 
 000,000). 
 
 • If net sales were to increase $1 mil- 
 lion, it would be expected that the 
 necessary inventory would increase by 
 $500,000. This indicates that a 50 per 
 cent backup in inventory is necessary 
 for each dollar's worth of product 
 sales. 
 
 • Associated with a $1 million increase 
 in inventory, there would be a $1.5 
 million expected increase in current 
 assets. This indicates the predomi- 
 nance of inventory in that current 
 asset group. 
 
 • For a $1 million increase in total 
 assets, one would expect a $390,000 
 increase in fixed assets. These results 
 are consistent with figure 8 which 
 shows fixed assets approaching 40 per 
 cent of total assets. Unfortunately, 
 the data do not disclose any informa- 
 tion regarding the recent "buy-build- 
 lease-back" trend used by chains to 
 reduce the large amount of invest- 
 ment in fixed assets. 
 
 • Associated with a $1 million increase 
 in accounts payable, there would be 
 
 a $1.65 million increase in total lia- 
 bilities; and for a $1 million increase 
 in total current liabilities, total lia- 
 bilities would increase by $1.95 mil- 
 lion. This latter comparison indicates 
 that short-run debt, other than ac- 
 counts payable, fluctuates more ex- 
 tensively than does accounts payable. 
 
 The three groups. A comparison of 
 the three groups on the six points men- 
 tioned shows the following: 
 
 • Net sales were more responsive to 
 store numbers in larger chains than 
 in smaller ones, indicating that large 
 chains are catching up with small 
 chains in terms of average store size. 
 
 • Net profit responded to store num- 
 bers at approximately the $10,000 
 per store level, except for the smallest 
 size chain group. However, store 
 numbers, accounted for very small 
 amounts of variation in net profits 
 for groups II and III. 
 
 • The inventory response to net sales 
 changes was relatively similar for all 
 three size groups, coefficients ranging 
 from .05 to .08. 4 This is reasonable 
 because the "inventory margin of 
 safety" should be about the same for 
 all groups, considering the availa- 
 bility of products and the time re- 
 quired for delivery. 
 
 • The relationship between current 
 assets and inventory change was con- 
 sistent among the three groups, with 
 coefficients of from 1.52 to 1.64. In all 
 three groups, more than 90 per cent 
 of the variation was explained by the 
 equation. This relationship is to be 
 expected since inventory accounts for 
 a major part of the total current 
 assets of retail food firms. 
 
 • In the fifth equation also, consistent 
 results were obtained from the analy- 
 sis of the three groups. Fixed assets 
 were shown to change at about one- 
 third the magnitude of total assets, 
 and about 90 per cent of the varia- 
 tion was explained by the factor con- 
 
 3 Slightly overestimated because of the approximately 10 per cent increase in the retail food 
 price index during the observation period 1953-1963. 
 
 4 Coefficient statistics such as these indicate the extent and direction of a response by the 
 dependent factor, given a one-unit increase in the size of the independent factor. For example, 
 given a $1 million increase in net sales, it can be expected that inventory requirements will 
 increase (positive coefficient) by $500,000 to $800,000. 
 
 [28] 
 
sidered. Again, this correlation fails 
 to distinguish differences among 
 firms with respect to the ownership 
 or lease method for obtaining build- 
 ings and equipment. 
 • In the sixth equation, different re- 
 lationships were found for the three 
 groups; however, in most cases the 
 results were statistically significant. 
 This indicates that total liabilities 
 responded quite differently to ac- 
 counts payable and total current lia- 
 bilities in the three size groups. Even 
 though there was considerable varia- 
 tion among groups I, II, and III, the 
 results indicated a heavy reliance on 
 open account purchases of merchan- 
 dise for resale by all the chains. 
 
 The individual chains. As mentioned, 
 Group II was the most expansion ori- 
 ented. For this reason, each of the 10 
 
 chains in this group was analyzed sepa- 
 rately, using the same six equations. A 
 brief glance at the regression coefficients 
 is sufficient to show the large extent of 
 variations among chains' operations. The 
 magnitude, as well as the direction of the 
 relationships, varied considerably among 
 chains. Relationships among equations 
 number 3, 4, and 5 were consistent. Equa- 
 tion 3 shows that each chain's inventory 
 responded similarly to net sales; equation 
 4 shows an impressive relationship be- 
 tween current assets and inventory; and 
 equation 5 again points out the 30-40 per 
 cent responsiveness of fixed assets to total 
 assets. It is worth noting that in the 
 second relationship, the net profit of some 
 of the Group II chains responded favora- 
 bly to increased store numbers, while 
 others did not. This suggests a great dif- 
 ference in individual new-store profita- 
 bility. 
 
 INDUSTRY PERFORMANCE AND PUBLIC POLICY 
 
 Methods used 
 
 The preceding discussion shows the more 
 favorable earnings record of the chains 
 in Group I. The smallest chains, Group 
 III, had the least favorable earnings rec- 
 ord. On the other hand, the medium-sized 
 chains, Group II, were expanding faster 
 in terms of both sales and outlets. It could 
 be that the management objective of firms 
 in both groups II and III was to compete 
 for sales volume by means of prices and/ 
 or services. 
 
 Here are three management practices 
 that might keep groups II and III earnings 
 below those of competing chains in 
 Group I: 
 
 • "Follow-the-leader" pricing, even 
 though the delivered on-the-shelf cost 
 of products might exceed those of 
 chains in Group I. This would result 
 in a lower net, assuming handling 
 costs are comparable. 
 
 • Lower markup and prices on mer- 
 chandise which would yield a lower 
 net, assuming handling costs are com- 
 parable. 
 
 • "Follow-the-leader" on prices for 
 products, plus extra customer services 
 
 which add to the retailers' handling 
 costs and thereby reduce net earnings. 
 
 Undoubtedly, the various firms use all 
 three of these practices to meet competi- 
 tive conditions relative to specific products 
 or product groups. For example, a firm 
 might have a "follow-the-leader" pricing 
 system for meat and a low markup and 
 pricing policy for fresh fruits and vege- 
 tables. The lower prices would be designed 
 to draw customers and would constitute 
 a form of sales promotion cost. This is 
 consistent with the objective of a firm that 
 wishes to expand or perhaps hold its busi- 
 ness, the ultimate goal being to achieve 
 higher profits by means of the scale econ- 
 omies of buying and selling merchandise. 
 
 Growth patterns 
 
 The total sales of the food chains have 
 continued to rise faster than nonchain 
 retail firms. This increase began during 
 the mid-1940's and gained momentum with 
 the removal of price controls and ration- 
 ing in 1946 (figure 19). This trend toward 
 concentrating more sales in fewer retail 
 food firms has brought forth charges of an 
 unwarranted concentration of economic 
 
 [29] 
 
44 
 
 Price controls and rationing removed 
 
 1 I l_l L 
 
 1929 
 
 1935 
 
 1940 
 
 1945 
 
 1950 
 
 1955 
 
 1960 1962 
 
 Fig. 19. Chain store sales as a percentage of all grocery store sales for selected years. (Chain stores 
 are considered firms with 1 1 or more outlets.) Source: Progressive Grocer, 1952—1964. 
 
 power that has been, and will continue to 
 be, harmful to our nation's economy (U. S. 
 Federal Trade Commission, 1960, p. 1.) Let 
 us examine the major aspects of the al- 
 legation. 
 
 Although it is true that the corporate 
 chains are rising in the grocery business, 
 additional chains entered the market be- 
 tween 1953 and 1964 and are competing 
 successfully for a greater share of the total 
 grocery store business (table 9). For ex- 
 ample, the 1962 sales of each of the two 
 largest chains, A 8c P and Safeway, propor- 
 tionately were below their 1954 share of 
 the total. Table 13 and figure 20 indicates 
 the rise in the relative importance of the 
 small chains within the group of 30 firms 
 under study. The substantial increase in 
 the number of small chains (table 8) sug- 
 gests the absence of an effective barrier to 
 entry in food retailing (Mooney, 1964). 
 
 The growth pattern of chain sales as a 
 
 percentage of all grocery store sales is 
 shown in figure 19. The change in the dis- 
 tribution of sales among the 30 large 
 chains, according to size, is brought out in 
 table 13 and figure 20. According to the 
 data that could be obtained, the Group II 
 and III chains are growing relatively faster 
 than the Group I chains. Should this 
 trend continue, there would be a virtual 
 elimination of the very small chains now 
 represented by Group III. In an effort to 
 get some further statistical verification of 
 the probability that smaller chains will 
 continue to move into a higher sales level 
 and achieve a greater relative share of the 
 total sales of the 30 chains under study, the 
 authors experimented with various tech- 
 niques, one of which was the "Markov 
 Chain" procedure, which is discussed in 
 appendix D. The calculations also pre- 
 sented in appendix D and graphically in 
 figure 21 indicate the following: 
 
 [30] 
 
Table 13 
 CONCENTRATION OF NATION'S 30 MAJOR RETAIL FOOD CHAINS 
 
 Chain 
 
 Average total net sales (1953-1963) 
 $15,389,399 
 
 Total net sales (1962) 
 $19,039,659 
 
 Total net sales (1954) 
 $11,167,604 
 
 Percentage 
 of total 
 
 Accumulated 
 total 
 
 Percentage 
 of total 
 
 Accumulated 
 total 
 
 Percentage 
 of total 
 
 Accumulated 
 total 
 
 
 per cent 
 
 1 
 
 30.35 
 
 30.35 
 
 27.51 
 
 27.51 
 
 35.72 
 
 35.72 
 
 2 
 
 14.40 
 
 47.75 
 
 13.17 
 
 40.68 
 
 16.24 
 
 51.96 
 
 3 
 
 10.63 
 
 55.38 
 
 10.22 
 
 50.90 
 
 9.93 
 
 61.89 
 
 4 
 
 5.17 
 
 60.55 
 
 5.42 
 
 56.32 
 
 5.41 
 
 67.30 
 
 5 
 
 4.88 
 
 65.43 
 
 5.13 
 
 61.45 
 
 4.66 
 
 71.96 
 
 6 
 
 4.10 
 
 69.53 
 
 4.84 
 
 66.29 
 
 3.96 
 
 75.92 
 
 7 
 
 3.53 
 
 73.06 
 
 4.04 
 
 70.33 
 
 3.12 
 
 79.04 
 
 8 
 
 3.49 
 
 76.55 
 
 3.72 
 
 74.05 
 
 3.12 
 
 82.16 
 
 9 
 
 2.76 
 
 79.31 
 
 3.36 
 
 77.41 
 
 2.18 
 
 84.34 
 
 10 
 
 2.66 
 
 81.97 
 
 2.90 
 
 80.31 
 
 2.04 
 
 86.38 
 
 11 
 
 2.61 
 
 84.58 
 
 2.61 
 
 82.92 
 
 1.81 
 
 88.19 
 
 12 
 
 2.18 
 
 86.76 
 
 2.60 
 
 85.52 
 
 1.49 
 
 89.68 
 
 13 
 
 1.85 
 
 88.61 
 
 2.04 
 
 87.56 
 
 1.19 
 
 90.87 
 
 14 
 
 1.21 
 
 89.82 
 
 1.50 
 
 89.06 
 
 1.16 
 
 92.03 
 
 15 
 
 1.09 
 
 90.91 
 
 1.46 
 
 90.52 
 
 .96 
 
 92.99 
 
 16 
 
 .94 
 
 91.85 
 
 1.22 
 
 91.74 
 
 .84 
 
 93.83 
 
 17 
 
 .93 
 
 92.78 
 
 1.09 
 
 92.83 
 
 .79 
 
 94.63 
 
 18 
 
 .93 
 
 93.71 
 
 .92 
 
 93.75 
 
 .77 
 
 95.39 
 
 19 
 
 .90 
 
 94.61 
 
 .90 
 
 94.65 
 
 .63 
 
 96.02 
 
 20 
 
 .71 
 
 95.32 
 
 .70 
 
 95.35 
 
 .56 
 
 96.58 
 
 21 
 
 .65 
 
 95.97 
 
 .63 
 
 95.98 
 
 .55 
 
 97.13 
 
 22 
 
 .64 
 
 96.61 
 
 .56 
 
 96.54 
 
 .52 
 
 97.65 
 
 23 
 
 .62 
 
 97.23 
 
 .55 
 
 97.09 
 
 .49 
 
 98.14 
 
 24 
 
 .57 
 
 97.80 
 
 .54 
 
 97.63 
 
 .43 
 
 98.57 
 
 25 
 
 .48 
 
 98.28 
 
 .46 
 
 98.09 
 
 .36 
 
 98.93 
 
 26 
 
 .47 
 
 98.75 
 
 .45 
 
 98.54 
 
 .34 
 
 99.29 
 
 27 
 
 .32 
 
 99.07 
 
 .42 
 
 98.96 
 
 .24 
 
 99.51 
 
 28 
 
 .32 
 
 99.39 
 
 .36 
 
 99.32 
 
 .23 
 
 99.74 
 
 29 
 
 .32 
 
 99.71 
 
 .34 
 
 99.66 
 
 .14 
 
 99.88 
 
 30 
 
 .29 
 
 100.00 
 
 .32 
 
 100.00 
 
 .13 
 
 100.00 
 
 preceding analysis is that chain firms will 
 tend to become larger. In view of this 
 tendency and the allegations in the U. S. 
 Federal Trade Commission Resolution of 
 October 9, 1958, that the concentration of 
 economic power in the food industry may 
 restrict competition by collusive price ac- 
 tion and unfair competitive methods (U. S. 
 Federal Trade Commission, 1960), the 
 probable growth pattern deserves further 
 attention. 
 
 Growth in the size of food chains has 
 been accomplished by means of (1) inter- 
 nal growth — a reinvestment of earnings, 
 expansion of borrowings by the firm, 
 and/or sale of stock; (2) purchase or ac- 
 quisition of other firms; and (3) merger. 
 The usual purpose of this drive toward 
 
 5 Small-chain entries into the market during this period are possible, but we are unable to 
 analyze such movements in our "closed market" study (see appendix F). 
 
 • Smaller retail firms will tend to in- 
 crease their relative share of the total 
 sales of the 30 chains. 
 
 • Larger firms can be expected to lose 
 some of their relative share of the 
 sales of the group of 30 chains. 
 
 • Both the small and large chains that 
 were operating in 1954 will move to- 
 ward or into size classification E 
 which, relative to total sales, is 
 smaller than the largest size group F. 
 
 • Given the assumptions on which the 
 projection is based, the 30 chains 
 move toward a structural equilibrium. 
 In other words, smaller firms will be- 
 come larger and larger firms will be- 
 come relatively smaller. 5 
 
 The most obvious deduction from the 
 
 [31] 
 
Number of Chains 
 
 Largest > Smallest 
 
 Fig. 20. Retail food chain concentration among 30 major chains. The 45° line represents an industry of 
 30 firms in which every firm is of equal size, i.e., 5 per cent of the firms have 5 per cent of total market 
 sales, 10 per cent of firms have 10 per cent of market sales, etc. Source: Table 13. 
 
 [32] 
 
2b 
 24 
 23 
 22 
 21 
 20 
 19 
 18 
 
 
 Group Classification 
 A .1000 - .2714 percent of total chain sales 
 B .2715 - .7366 percent of total chain sales 
 C .7367 - 1.9991 percent of total chain sales 
 D 1.9992- 5.4256 percent of total chain sales 
 E 5.4257 - 14.7251 percent of total chain sales 
 F 14.7252 - 39.9639 percent of total chain sales 
 
 
 
 17 
 
 
 
 
 
 16 
 
 
 
 
 
 » 15 
 f 14 
 
 
 
 
 
 
 
 o 13 
 5 12 
 
 1 
 
 
 
 
 
 
 "E 11 
 
 
 
 
 
 
 
 
 
 z 10 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 9 
 
 8 
 
 7 
 
 - 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 6 
 
 _ 
 
 
 
 
 
 
 
 — 1 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 5 
 4 
 
 - 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 3 
 2 
 
 _ 
 
 A 
 
 B 
 
 C 
 
 D 
 
 E 
 
 F A 
 
 n 
 
 B 
 
 c 
 
 D 
 
 E 
 
 F A 
 
 B 
 
 C 
 
 D 
 
 E 
 
 F 
 
 A 
 
 B 
 
 C 
 
 D 
 
 E 
 
 F 
 
 A 
 
 B 
 
 C 
 
 D 
 
 E 
 
 F 
 
 1 
 
 
 — 
 
 
 
 
 
 ~ 
 
 r 
 
 
 
 
 
 -i r 
 
 
 
 
 
 — \ 
 
 _c 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 I ) I ) I ) 
 Y V V 
 
 ^-v— J 
 
 I 
 
 < ' 
 
 
 \ 
 
 
 
 
 
 19 
 
 54 
 
 
 
 
 19 
 
 62 
 
 
 
 
 19 
 
 70 
 
 
 
 
 
 1978 
 
 
 
 
 
 1986 
 
 
 
 Fig. 21. Distribution of 30 major chains by size in 1954 and 1962, and projections by eight-year 
 intervals through 1986. Source: Appendix D. 
 
 "bigness" has been to improve the total 
 net earnings of the firms through mass 
 buying and selling of merchandise. 
 
 Because one of the effects of mergers and 
 acquisitions is to reduce the number of 
 firms and ownership entities, such actions 
 could be regarded as a method of reducing 
 competition. Conversely, they could be 
 looked upon as the only means of eco- 
 nomic survival in an industry in which 
 certain operating efficiencies, e.g., purchas- 
 ing and advertising, are a function of sales 
 volume. Even single-store grocery firms 
 that do not want to integrate in an own- 
 ership sense are often achieving the basic 
 economies of mass buying and warehous- 
 ing through retailer-owned cooperative as- 
 sociations or wholesaler-sponsored buying 
 groups. 
 
 Internal growth is usually characterized 
 by reinvesting earnings or borrowed funds 
 in larger stores and other facility improve- 
 ments. This usually forms a part of a 
 general modernization and replacement 
 
 program of the firm. Capital for these pur- 
 poses is less frequently obtained from the 
 sale of stock. 
 
 Food firms have been seeking to in- 
 crease their sales volume and net earnings 
 or profits in a number of ways other than 
 those discussed on page 29. Rapidly grow- 
 ing chains often are attaining their goal 
 of increased sales by expanding the num- 
 ber of store outlets. Others are increasing 
 the number of stores and the size of stores, 
 either by modernizing old or building 
 larger new stores. The well-established 
 large chains appear to be going through a 
 store modernization and consolidation 
 process, the outcome of which seems to be 
 a temporary reduction in the total num- 
 ber of stores operated by a firm. In addi- 
 tion to varying the size and/or number of 
 stores, another approach to increasing sales 
 and profits has been to find the most de- 
 sirable locations for the stores operated by 
 the firm. This has meant adjusting loca- 
 tion plans to population movements. A 
 
 [33] 
 
third approach has been to vary the num- 
 ber and quality of services offered to con- 
 sumers. This has been characterized by the 
 development of small, convenience-type 
 stores (superettes) featuring quick service 
 and long store hours; and minimum serv- 
 ice or "discount" stores." 
 
 Effect of population changes on 
 
 number and location of 
 
 grocery stores 
 
 The assumption that "trade follows peo- 
 ple" is especially applicable to the busi- 
 ness of supplying food to our population. 
 The almost complete dependence of our 
 people on retail grocery stores is indicated 
 by the following discussion. 
 
 The past 10 years have been character- 
 ized by a rather steady increase in the 
 United States population and a sharp de- 
 cline in the number of retail grocery stores. 
 Based on the available data, the authors 
 estimate that the number of people per 
 grocery store has increased from an aver- 
 age 465 in 1955 to 828 in 1964. Demog- 
 raphers currently predict an increase of 
 24,240,000 people by 1975. It also seems 
 highly probable that grocery store numbers 
 will continue to decrease; however, the 
 rate of decline may taper off somewhat. 6 
 
 In general, therefore, we should be able 
 to make some statements as to the future 
 movement of the "population per store" 
 statistic. As shown in figure 22, this statis- 
 tic has increased in an almost linear fash- 
 ion over the past 10 years. A linear extra- 
 polation of this trend leads us to expect 
 that in 1975 the average United States 
 grocery store will be serving approximately 
 1,300 people. One's first impression would 
 tempt him to deflate this estimate in view 
 of this tapering off in the rate of decline 
 of the number of grocery stores. However, 
 this tendency is counterbalanced with the 
 assumption that those new stores, which 
 will be built in the future, are likely to be 
 even larger in size than most current stores. 
 
 Given the United States population pro- 
 jection and the average size (1,300 persons 
 
 6 Past declines in grocery store numbers can be partially attributed to the business failures 
 of the small "corner grocers." Since corner grocers are no longer so numerous, their decline in 
 numbers will be of a smaller magnitude. 
 
 7 "Performance or service" is used here to indicate a measure of availability, quantity, and 
 quality of food products currently available to the average customer in the average United 
 States grocery store. 
 
 [34] 
 
 per store) of the retail grocery store in 
 1975, the estimated number of additional 
 retail grocery stores which will have to be 
 built in the United States over the next 10 
 years in order to maintain the current 
 level of service or market performance 
 equals 18,648. 7 This change is approxi- 
 mately an 8 per cent increase over current 
 store numbers. 
 
 The typical procedure generally would 
 be to apply the above technique to more 
 specific areas such as a particular state or 
 even a metropolitan area in order to ob- 
 tain more applicable results. Unfortu- 
 nately, this procedure cannot be followed 
 because the data used in this study deal 
 basically with industry, structural changes, 
 and market characteristics on a national 
 basis. Therefore, any attempt to apply the 
 general conclusions and /or projections to 
 a smaller geographic area can only result 
 in reducing the validity of the end prod- 
 uct. 
 
 To illustrate further this graphical lim- 
 itation, we shall choose a particular state 
 and a metropolitan area, discuss its par- 
 ticular and differentiating market charac- 
 teristics, and then demonstrate the result- 
 ing inconsistencies. 
 
 Demographers predict that California 
 can expect an increase in population of 
 4,590,000 people by 1975. By using the na- 
 tional projection of expected store size, 
 one could conclude that California would 
 need approximately 3,500 additional gro- 
 cery stores. However, the California retail 
 food industry has experienced a growth 
 pattern quite different from that of the 
 nation as a whole. Since the 1940's, Cali- 
 fornia has experienced a massive growth 
 in its population. This population has 
 spread itself over areas which were unin- 
 habited desert a short time before. The re- 
 tail food industry has been forced to fol- 
 low this population movement by building 
 a large number of stores. While the major- 
 ity of other states have had a decrease in 
 the number of grocery stores, California 
 has experienced a 50 per cent increase in 
 grocery store numbers over the past 10 
 

 1330 
 
 
 
 
 
 
 • 
 
 
 1250 
 
 
 
 
 
 
 ,' 
 
 
 1170 
 
 
 * 
 * 
 
 
 
 
 ,' 
 
 
 1090 
 
 
 
 
 
 
 * 
 
 
 101C 
 
 
 
 
 
 
 + 
 
 
 
 
 ' 
 
 ~ 
 
 930 
 
 — 
 
 s 
 
 jK 
 
 
 
 / 
 
 
 
 
 • 
 
 
 850 
 
 
 y 
 
 
 
 
 
 
 
 
 
 a 
 
 770 
 
 — 
 
 
 
 
 
 
 o 
 
 
 
 
 t 
 
 690 
 
 
 
 / 
 
 
 
 - 
 
 ^y — Projected 
 
 
 610 
 
 — >/ 
 
 
 
 530 
 
 - y 
 
 
 
 450 
 
 
 
 
 
 
 7 , , , , , 
 
 1 
 
 Fig. 22. Population per grocery store in U. S., 1955-1975. Source: Progressive 
 Grocer, 1955-1965; Appendix table D-3; and Bureau of Census, 1965. 
 
 years (see appendix table B-l). As a result, 
 population per store has remained rela- 
 tively constant at about 870. Therefore, if 
 this present population to number of gro- 
 cery stores ratio continues, California will 
 require approximately 4,300 (as compared 
 with 3,500) additional grocery stores by 
 1975. 
 
 A similar inconsistency would occur if 
 national data were applied to an ever 
 smaller area such as the San Francisco- 
 Oakland Metropolitan Area. While the 
 estimated population increase of 1,890,000 
 people implies a substantial increase in 
 store numbers, authorities have often de- 
 scribed this particular area as "over-stored" 
 and capable of meeting greatly increased 
 consumer demands with the present store 
 facilities. This further illustrates the need 
 to analyze each market area individually, 
 thereby avoiding the possible misfortunes 
 resulting from the application of national 
 projections. 
 
 Conduct and performance 
 of chains 
 
 Mass distribution methods for food have 
 been encouraged by technological ad- 
 vances; higher capital requirements; 
 higher salaries, wages, and fringe benefits; 
 
 rising consumer disposable income; and 
 population concentration. These forces 
 also have been behind the mass production 
 of food and nonfood products. In any 
 case, mass distribution practices and chains 
 seem to be interwoven. This implies a con- 
 centration of economic power in the food 
 field. The real economic and legal issue is 
 how the chains use this power which comes 
 from their dominance of sales. 
 
 With the few exceptions which are a 
 matter of court record, there is not much 
 to support or refute any charge against 
 the food chains of any overt misuse of their 
 market power, either as buyers of goods to 
 be resold to consumers or as retailers. The 
 available statistical evidence shows that 
 the medium and large retail chains are 
 winning the competitive struggle for cus- 
 tomers and sales. It does not show that 
 competition is being eliminated. In fact, 
 the research department of the largest se- 
 curity investment firm in the United States 
 rates only one firm's common stock — Great 
 Atlantic and Pacific Tea Company — as a 
 recommended high-quality, investment- 
 type risk. All others are average or specu- 
 lative-type investments (Merrill Lynch et 
 al., 1966). The basics reasons for the low 
 investment appraisal are keen competition 
 and overexpansion. In view of the charges 
 
 [35] 
 
that competitors are being eliminated by 
 a misuse of economic power, the advice of 
 the investment firm to its clients is inserted 
 here. 
 
 In relation to other segments of the econ- 
 omy, the food-chain industry fared poorly 
 in 1965; and indications are that business 
 will continue to be characterized by in- 
 tensely competitive conditions and pres- 
 sure on profit margins during the current 
 year. . . . Despite this relatively poor per- 
 formance, food chains continue to expand 
 outlets, causing overstoring in certain 
 areas of the country and intensified price 
 competition as the chains try to build ade- 
 quate volume in the new units. In some 
 areas, the situation has been further ag- 
 gravated by discontinuing trading stamps 
 and by converting many units to a "dis- 
 count" image. Under existing conditions, 
 many companies are having difficulty pass- 
 ing on increases in wholesale costs of food, 
 particularly meat. 
 
 On the positive side, a number of com- 
 panies continue to register sastisfactory 
 earnings gains as a result of new-store ex- 
 pansion, above-average population growth 
 in their operating areas, and the ability 
 to increase their share of markets by ef- 
 fective merchandising. 
 
 Conclusive evidence shows a growing 
 concentration of sales in the retail chains, 
 and also a corresponding concentration of 
 buying power. However, this structural 
 characteristic does not connote an arbi- 
 trary use of market power to frustrate nor- 
 mal marketing and pricing processes. It is 
 possible that the large retail chains would 
 be at a disadvantage during periods of 
 short supply in obtaining the quantities 
 of uniformly graded products to meet their 
 demand. This has happened a number of 
 times since 1941, particularly during the 
 World War II period when price ceilings 
 and product rationing were used. 
 
 Many of the complaints about "unfair" 
 buying practices and "market manipula- 
 tion" originate with growers and shippers 
 of fresh fruits and vegetables. Because of 
 repeated complaints from lettuce growers 
 and shippers in Salinas, Miklius and De- 
 Loach (1965) chose to examine the basis 
 for the charge of "market manipulation" 
 by chains. The researchers had three ob- 
 
 jectives in mind: to investigate available 
 evidence regarding the change in the num- 
 ber of buyers and sellers in the market; to 
 estimate the relative volumes bought by 
 the principal chains; and to investigate the 
 purchasing patterns of the three principal 
 buyers in order to learn whether their pat- 
 terns resembled those which could be ex- 
 pected in an oligopsony market. The prin- 
 cipal findings were: 
 
 • Although the records are incomplete, 
 it appears that the number of lettuce 
 buyers declined during the decade 
 1953-1963. The change was neither 
 drastic nor abrupt, and it was offset, 
 to some extent, by a decrease in the 
 number of shippers. 
 
 • The three principal chain buyers ac- 
 counted for a relatively small share of 
 the market. During the 92 days of the 
 1963 shipping season, they purchased 
 about 10 per cent of the daily supply 
 of Salinas lettuce. 
 
 • The principal buyers paid either 
 average or above-average market 
 prices. Their purchasing patterns did 
 not show interdependence in the var- 
 iation of quantities purchased. 
 
 • The study did not disclose any overt 
 attempt by the buyers to follow a 
 strategy of withdrawing from the mar- 
 ket during periods of falling prices, 
 which would have encouraged a fur- 
 ther price decline. 
 
 The authors recognized the weaknesses 
 of the approach used; nonetheless, they 
 believe that the same research approach 
 would be applicable to other commodities 
 and the results would be very useful to a 
 better understanding of the conduct of the 
 large retail food firms. 
 
 Viewing the chains as sellers, one must 
 face the problem of a concentration of 
 economic power in terms of market dom- 
 ination. The declining importance of the 
 small, independent retailers is evident 
 from the statistics already presented. It 
 also is equally clear that the small store, 
 regardless of ownership arrangement, is 
 under severe competitive pressure. But 
 this pressure usually arises from the ina- 
 bility of the small operator to fit into a 
 pattern of mass buying and selling. The 
 best illustration of this economic pressure 
 
 [36] 
 
on small retailers is found in the current 
 policy of most retailer-owned cooperative 
 buying groups which either deny member- 
 ship to small retail firms, set up subsidiary 
 organizations to supply them, or charge 
 special service fees for small volume trans- 
 actions. Cooperatives make no effort to en- 
 courage small retailer members to retain 
 their membership. Since the small stores 
 lack sales volume, they also lack purchas- 
 ing volume and bargaining power, even 
 among independents. 
 
 The claim that chains have resorted to 
 unfair selling practices generally means 
 that the claimant believes that chain 
 prices, particularly on specials, often are 
 lower than wholesale costs to the small 
 operator, or that the quality of chain 
 products and other consumer services are 
 inferior. Many states have sought to end 
 below-cost pricing by means of minimum 
 price laws. Also, state and federal laws 
 forbid unfair selling practices. In view of 
 the fact that relatively few court cases have 
 been recorded as a result of actions to en- 
 force these statutes, one might infer that 
 most claims of unfair practices are ques- 
 tionable. If one chooses to accept the con- 
 sumer as the judge of such questions as 
 prices, services, and product qualities, one 
 will see that they have largely shifted their 
 patronage to large stores, either independ- 
 ent-affiliated stores or chains. Moreover, 
 this shift took place when alternatives were 
 available and it is continuing while alter- 
 natives are available. 
 
 The Bureau of Labor Statistics Food 
 Price Index reflects the upward movement 
 of retail prices for food (table 14). The 
 United States Department of Agriculture's 
 Market Basket Index reflects the rising 
 spread between farm prices and retail 
 prices of fresh and processed products sold 
 in retail stores. Both indexes are used as a 
 basis for the charge that "distribution 
 costs too much," and that buying and sell- 
 ing practices of large retail firms are the 
 principal reason (Supermarket News, 
 1966). 
 
 The U. S. Department of Agriculture 
 has published an informative list of re- 
 ports over the last 15 years dealing with 
 retail margins on food and the compo- 
 nents of those margins (Hamilton, 1959; 
 
 Table 14 
 
 AVERAGE RETAIL FOOD 
 
 PRICE INDEX 
 
 (1947-1949 = 100) 
 
 Year 
 
 Index 
 
 Year 
 
 Index 
 
 1964 
 
 1963 
 
 1962 
 
 1961 
 
 1960 
 
 1959 
 
 1958 
 
 1957 
 
 1956 
 
 1955 
 
 1954 
 
 1953 
 
 1952 
 
 1951 
 
 1950 
 
 1949 
 
 1948 
 
 1947 
 
 1946 
 
 1945 
 
 1944 
 
 1943 
 
 1942 
 
 125.5 
 124.0 
 122.0 
 121.1 
 119.7 
 118.2 
 119.4 
 115.4 
 111.7 
 110.9 
 112.6 
 112.8 
 114.6 
 112.6 
 101.2 
 100.0 
 104.1 
 95.9 
 79.0 
 68.9 
 67.4 
 68.3 
 61.3 
 
 1941 
 
 1940 
 
 1939 
 
 1938 
 
 1937 
 
 1936 
 
 1935 
 
 1934 
 
 1933 
 
 1932 
 
 1931 
 
 1930 
 
 1929 
 
 1928 
 
 1927 
 
 1926 
 
 1925 
 
 1924 
 
 1923 
 
 1921 
 
 1920 
 
 1919 
 
 52.2 
 47.8 
 47.1 
 48.4 
 52.1 
 50.1 
 49.7 
 46.4 
 41.6 
 42.8 
 51.4 
 62.4 
 65.6 
 64.8 
 65.5 
 68.0 
 65.8 
 60.8 
 61.4 
 63.5 
 83.6 
 74.2 
 
 Source: U. S. Department of Labor, 1951 and 1952; 
 1961-1963. 
 
 U. S. Department of Agriculture 1957, 
 1965a and b). These reports have not con- 
 sidered profits in any great detail. On the 
 other hand, they establish the fact that the 
 rise in retail margins parallels the rise in 
 the costs of the two components, labor 
 and capital. The Department's reports 
 state that the increases arose mainly from 
 rates for labor and capital and a very sub- 
 stantial increase in the customer services 
 included with the product purchased. 
 
 Considering the alternative channels 
 available in most markets, there is no 
 really sound basis for stating that retail 
 store customers are being forced to pur- 
 chase unwanted services other than those 
 rendered in response to those customers. 
 In a previous study, one of the present 
 authors chose to approach the problem 
 indirectly. He attempted to compare the 
 prices and services of four stores of a 
 large, highly successful consumer coopera- 
 tive with those of four stores of compara- 
 ble size operated by different food chains 
 in the same California communities where 
 labor contracts were operative and rentals 
 
 [37] 
 
were fairly uniform. 8 The net price dif- 
 ferences, including patronage dividends to 
 cooperative members, were negligible. The 
 customer services in the form of pre- 
 cooked food, high-priced specialty prod- 
 ucts, and advisory services were slightly 
 greater for cooperative patrons. Since 
 there are relatively few successful con- 
 sumer cooperatives in urban areas in the 
 United States and the cooperative objec- 
 tive is to serve patrons at cost, the fore- 
 going comparison implies that retail mar- 
 keting margins are fairly well governed by 
 input costs and that prices to customers 
 must be competitive even between coop- 
 eratives and profit-type firms. 
 
 For the 30 chains for which data are 
 available, the authors were able to estab- 
 lish a positive relationship between the 
 size of the firm and net returns per dollar 
 of sales or investment. Industry-wide data 
 also are sufficient to compare food retail- 
 
 ing profits with those of a few other indus- 
 tries; however, this type of comparison pre- 
 sents difficulties. 
 
 Because our economy consists of indus- 
 tries of varying sizes, dollar profits vary 
 considerably. Hence, comparisons are in 
 terms of profit ratios or percentage rates 
 of return, either on sales or net worth. 
 
 Figures 23 and 24 contain a comparison 
 of profits for selected industries for 1954, 
 1959, and 1964. The story about profits is 
 rather simple. In condensed form, one 
 may say: 
 
 • Profits as a percentage of both net 
 worth and dollar sales rose steadily 
 for four of the industry groups in- 
 cluded in the comparison. For food 
 retailing and agriculture, 1964 ab- 
 solute profits were above 1954; how- 
 ever, 1964 profits were below those of 
 1959 for both retailing and agricul- 
 ture. 
 
 Fig. 23. Comparison of profits as a percentage of sales, selected industries, 1954, 1959, and 1964. 
 Source: Appendix table E-l. See footnote in that table for method used to arrive at net profits for 
 agriculture. 
 
 18 
 
 17 
 16 
 15 
 14 
 
 13 - 
 12 
 11 
 10 - 
 
 Agriculture 
 
 Durable goods 
 industry 
 
 Other 
 
 consumer goods 
 
 industry 
 
 Food processing 
 industry 
 
 Retai I food 
 
 industry 
 A 
 
 Nation's 500 
 
 largest 
 
 industrial 
 
 corporations 
 
 8 DeLoach, D. B., A comparison of prices among selected retail food chains and a consumer 
 Cooperative, 1964, 25 pp., unpublished manuscript. 
 
 [38] 
 
Retail food 
 industry 
 
 Durable goods 
 industry! 
 
 Food processing 
 industry?.' 
 
 Other 
 
 consumer goods 
 
 industry?/ 
 
 Agr 
 
 iculture 
 
 
 
 
 
 
 o- 
 
 
 
 Fig. 24. Comparison of profits as a percentage of net worth, selected industries 1954, 1959, and 1964. 
 Source: Appendix table E— 1. See footonote in that table for method used to arrive at net profits for 
 agriculture. 
 
 • The food retailing industry operated 
 with the lowest percentage return per 
 sales dollar; agriculture had the high- 
 est return per sales dollar. 
 
 Conversely, agriculture had the lowest 
 percentage return on net worth; the food 
 retailing industry's return on net worth 
 was favorable. This latter comparison 
 shows the effects of sales volume on the net 
 return on capital, reflecting larger total 
 profits for a large-volume, small-profit 
 item than for a small volume, high profit 
 product. In this respect, it is worth men- 
 tioning that the average U. S. farm pro- 
 duces enough food for 28 persons; the 
 average retail grocery store supplies an 
 average of more than 700 persons. 
 
 The food retailing industry usually 
 shows its net profits as a percentage of dol- 
 lar sales; agricultural groups state theirs in 
 terms of return on net worth. These im- 
 plied preferences are associated with the 
 desires of the groups to convey a notion 
 of "fairness" or "unfairness" of returns to 
 them for the activities in which they are 
 involved. 
 
 The food retailing industry, in common 
 with other industries, has no criteria for 
 determining what is a "fair" rate of re- 
 turn. Returns have been sufficiently high 
 since 1946 to induce investors to provide 
 adequate funds for expansion, either from 
 new capital from outside sources or from 
 retained industry earnings. 
 
 In reference to a "fair" return on own- 
 er's investment, various government agen- 
 cies have arrived at about 10.5 per cent as 
 a justifiable net profit rate. 9 By doing this, 
 the government agency became a judge of 
 "fairness." For the three years — 1954, 1959, 
 and 1964 — food retailing was within an 
 8.8 to 13.1 per cent range. This percentage 
 return is significant in view of the previ- 
 ously mentioned claims that the food 
 chains are using their concentrated market 
 power to hold farm prices down and retail 
 prices up in order to gain excessive profits. 
 Retailers also cite studies of their costs of 
 operations to show increasing prices are 
 a result of higher costs (England, 1959). 
 The retail food industry also claims that 
 it takes only $15 a year per family in the 
 form of net profit for its services. 
 
 8 The Interstate Commerce Commission recently used this figure in analyzing the possible 
 existence of excess profit in the nation's public transportation sector. Similarly, the Federal 
 Aviation Authorities used approximately the same return for domestic airlines. 
 
 [39] 
 
GOVERNMENT REGULATION 
 
 The rapid growth in the economic power 
 of grocery chains has forced some major 
 adjustments in marketing channels and 
 methods. The policy of larger chains to 
 circumvent wholesalers and purchase di- 
 rect from manufacturers and packers or 
 growers, or even to engage in manufactur- 
 ing and packing activities, has descreased 
 the importance of wholesalers. The con- 
 sumers' support of chains, as indicated by 
 their patronage, concentrates selling power 
 in relatively few firms, thereby enhancing 
 the bargaining power of some chains in 
 dealing with manufacturers. Finally, the 
 shift of consumer patronage to chains or 
 to large independent supermarkets has 
 considerably diminished the economic 
 power of small, independent grocers, but 
 it has not lessened their political power. 
 
 In a competitive struggle for business 
 survival, those who have been affected ad- 
 versely by the growth of chains have sought 
 to buttress their weakening economic posi- 
 tion by appealing for public support or 
 seeking legal constraints based on the pre- 
 cept of "preserving competition." by 
 means of such activities they have had con- 
 siderable influence in the development of 
 whatever public policy we now have in the 
 area of food distribution. 
 
 It is not the purpose of this paper to 
 analyze state and federal activities which 
 restrain the development and use of eco- 
 nomic power in the market place. How- 
 ever, a few brief comments about this sub- 
 ject should suffice to describe the environ- 
 ment in which the growth of grocery chains 
 is occurring. Most of these government ac- 
 tivities are federal in origin; hence, the 
 comments will relate to these only. 
 
 Legal restraints 
 
 The economic growth of the grocery chains 
 has been influenced greatly by the various 
 antitrust laws — Sherman (1890), Clayton 
 (1914), Federal Trade Commission (1914), 
 Packers and Stockyards (1921), and Robin- 
 son-Patman (1936). The essence of the 
 antitrust legislation is to prevent or break 
 down any undue concentration of market 
 power which is, or threatens to become, a 
 monopoly in restraint of trade or to regu- 
 
 [ 
 
 late business conduct and trading prac- 
 tices that could be, or are, injurious to 
 competitors. All such legislation is nega- 
 tive in the sense that it follows the prin- 
 ciple of "thou shalt not." 
 
 Administration of the Sherman Act is 
 a function of the U. S. Department of Jus- 
 tice. This department also shares with the 
 U. S. Federal Trade Commission the re- 
 sponsibilities for enforcing the Clayton 
 Act. The Robinson-Patman and U. S. Fed- 
 eral Trade Commission Acts are assigned 
 to the U. S. Federal Trade Commission; 
 the Packers and Stockyards Act to the Sec- 
 retary of Agriculture. 
 
 In the past, investigators centered pri- 
 marily on the large meat packers and gen- 
 eral food manufacturers. Investigations 
 have been centered on the food chains in 
 more recent years, largely because they are 
 disturbing to the small retailer and large 
 meat packers and food manufacturers who 
 have developed market interests which are 
 being undermined by mass buying and 
 selling practices. 
 
 With the exception of antitrust actions 
 against A & P, the chains were relatively 
 free of significant investigations until the 
 early 1930's when Congress undertook a 
 broad inquiry that subsequently resulted 
 in the enactment of the Robinson-Patman 
 Act. Since 1946, a number of Congressional 
 and special Commission inquiries, U. S. 
 Federal Trade Commission and Packers 
 and Stockyard Administration actions, and 
 Department of Justice suits have been in- 
 stituted. Some have been concluded. A 
 few observations regarding the current 
 inquiry of the National Commission on 
 Food Marketing, the activities and impli- 
 cations of the U. S. Federal Trade Com- 
 mission, and court rulings on cases 
 brought by the Department of Justice or 
 other plaintiffs are contained in the fol- 
 lowing section. 
 
 Public opinion 
 
 When legal remedies are lacking, those 
 who claim injury from competitive prac- 
 tices often seek relief by appealing to their 
 legislative representatives for an investiga- 
 tion or an enactment of remedial legisla- 
 
 40] 
 
tion. A second procedure is to request an 
 administrative agency to conduct an in- 
 quiry with a view toward recommending 
 new legislation (U. S. Federal Trade Com- 
 mission, 1960). A third procedure is to ap- 
 point a special committee or "prestige" 
 commission to conduct an inquiry into an 
 allegation of unfair practices and to pre- 
 sent its findings to the Congress. This lat- 
 ter procedure is often used when estab- 
 lished government agencies are unwilling 
 to undertake such an inquiry or legislators 
 or administrators wish to circumvent es- 
 tablished agencies. Frequently, the real 
 motive for the three types of inquiries is 
 to focus public attention on the subject of 
 the inquiry and thereby induce an alleged 
 offender to mend his ways. In a sense, the 
 public hearings conducted by various gov- 
 ernmental bodies become a source of news 
 for the several news media. The hearings 
 can be and have been extremely damaging 
 to the "image" of a particular firm or an 
 economic group such as grocery chains 
 (U. S. Congress, 1959). 
 
 The current inquiry of the National 
 Commission on Food Marketing is an out- 
 growth of the unrest over rising food prices 
 in retail store and low prices, particularly 
 on beef cattle, at the farm level. Briefly, 
 the Commission was asked to concern it- 
 self with past and future changes in the 
 food industry; what is required to assure 
 an efficient system of production, process- 
 ing, and marketing while maintaining in- 
 dustry competition; methods for achieving 
 a "desired distribution of power" and "de- 
 sired levels of efficiency" within the system; 
 the adequacy of government services and 
 regulatory activities; and the effect of im- 
 ported food on domestic producers, pro- 
 cessors, and consumers (Ginsberg, 1966). 
 
 The National Commission on Food Mar- 
 keting has been assembling and analyzing 
 evidence bearing on the foregoing sub- 
 jects. It seemingly has encountered all of 
 the statistical difficulties faced by previous 
 investigators who were trying to measure 
 performance among the various sectors of 
 food production and marketing. Among 
 these difficulties are a lack of comparabil- 
 ity of many products and customer serv- 
 ices and rather wide variations in account- 
 ing procedures. 
 
 This lack of good statistics handicaps 
 
 any investigational body that is seriously 
 seeking the best answer to the various eco- 
 nomic problems associated with food pro- 
 duction and marketing. Because the whole 
 problem of the validity and adequacy of 
 data has plagued both the industry and 
 various governmental agencies for many 
 years, it would appear that this problem 
 needs to be resolved as a basis for a more 
 complete understanding of the issues in- 
 volved. 
 
 Current investigatory philosophy 
 
 Both the U. S. Department of Justice and 
 the U. S. Federal Trade Commission have 
 used their investigational authority to as- 
 semble and analyze statistics relating to 
 the operating policies and practices of all 
 sectors of the food industry. The objective 
 of such inquiries generally has been di- 
 rected toward either obtaining evidence 
 about trade practices of a given firm, or 
 about concentration of economic power. 
 Inasmuch as the antitrust laws adminis- 
 tered by the two agencies were passed to 
 prevent undue concentrations of eco- 
 nomic power and encourage competition, 
 the administering agencies were given the 
 task of defining "undue concentration" 
 and "competition." 
 
 As is true with any legislation, the ab- 
 sence of precedents means that the admin- 
 istrators of quasi-judicial bodies such as 
 the U. S. Federal Trade Commission build 
 precedents by the manner in which they 
 select firms to be charged with violations, 
 the nature of their evidence, and their 
 subsequent decisions. Similarly the De- 
 partment of Justice has the responsibility 
 for discoving and assessing the evidence 
 of violations of specific statutes, obtaining 
 indictments, and bringing the cases before 
 the courts. The decisions of the courts are 
 then used as precedents. By virtue of the 
 authority of administrative agencies to in- 
 stitute or not institute an antitrust action, 
 one finds a great variation in the applica- 
 tion of the law and the importance the 
 administrative authority attaches to dif- 
 ferent forms of business conduct. 
 
 The published literature on government 
 regulation of monopolies indicates that 
 there is far less than a concensus within 
 and among our courts and various admin- 
 istrative agencies on what constitutes a 
 
 [41] 
 
monopoly in restraint of trade. Certainly 
 there has been uncertainty regarding what 
 constitutes undesirable competitive prac- 
 tices. However, a measure of relief should 
 emerge from the recent practice of the 
 Antitrust Division of the Department of 
 Justice to scrutinize proposed mergers. 
 
 In an effort to preserve and protect 
 small businesses, the concept of the "op- 
 timum social competition" has emerged 
 which means a bypassing of many basic 
 economic considerations. It is under this 
 social concept that the U. S. Federal 
 Trade Commission has been instituting 
 actions to prevent mergers on the theory 
 that such mergers might be harmful to 
 competition. For example, Section 7 of 
 the Clayton Act recently has been used by 
 the Commission to prevent structural 
 changes which create or aggravate sub- 
 stantial market power in one firm, includ- 
 ing changes that fall short of monopoly 
 actions, in order to forestall anticompeti- 
 tive behavior. Unlike other sections of 
 the Act, Section 7 does not focus on 
 whether or not an illegal merger or 
 purchase action has occurred. Insted, it 
 calls for an economic prediction of the 
 competitive effects that are likely to fol- 
 low from a proposed structural change 
 that would further concentrate economic 
 power. In other words, the Commission 
 does not have to prove that further concen- 
 tration will result in monopolistic pricing 
 practices. It only needs to show that, on 
 the basis of economic logic and industrial 
 experience, such behavior is "reasonably 
 probable." 10 
 
 Recently, the Commission handed down 
 a divestiture order based on the above re- 
 lationship. 11 The case later was brought 
 
 before the U. S. Supreme Court which re- 
 versed the Commission's decision and 
 stated, "Probability can best be gauged by 
 what the past has taught. We are con- 
 vinced that the Commission has mistakenly 
 rejected what the record demonstrates as 
 to what actually happened in the past in 
 favor of a future possibility based on con- 
 jecture and speculation." 
 
 Despite this court action, Robert A. 
 Hammond 12 (a proponent of the philoso- 
 phy accepted by the Commission) states, 
 "The costs of such an approach (the insis- 
 tence on the existence of a high degree 
 of certainty prior to any antitrust statute 
 enforcement) . . . might well result in the 
 transformation of the structure of our 
 economy in a way totally inconsistent with 
 our reliance on competition as the pri- 
 mary economic regulator." 
 
 Retail food chains have shown consider- 
 able initiative and ability in adjusting to 
 the legal constraints under which they 
 must operate. The most outstanding exam- 
 ple has been the need of firms to accom- 
 modate themselves to the Robinson-Pat- 
 man Act. In this case, specific buying prac- 
 tices are forbidden as unfair and destruc- 
 tive to competition. Since it is the func- 
 tion of management to develop and use 
 whatever legal and ethical business strat- 
 egies it can in order to find an optimum 
 solution to its problems, retail food firms 
 turned their attention to finding other 
 management procedures for keeping their 
 procurement costs down. Frequently this 
 meant the acquisition of their suppliers' 
 businesses or the development of their 
 own food processing or manufacturing 
 operations. 
 
 10 Brown Shoe Company versus United States, 370, U.S. 294 (1962); and United States versus 
 Continental Can Company, 12L ed. 2d. 953 (1964). 
 
 11 United States versus Kennecott Copper Corporation, 231-F, Supplement 95, (S.D.N.Y.) 1964. 
 
 12 Hammond, R. A., Antitrust in an Expanding Economy, paper presented at conference of 
 National Industrial Conference Board, March 4, 1965. 
 
 [42] 
 
APPENDIX A 
 
 Table A-l 
 
 POPULATION AND DISPOSABLE PERSONAL INCOME, 
 
 BY STATES, 1954 AND 1964 
 
 State 
 
 Population 
 
 1954 
 
 Percentage 
 change 
 
 Per capita disposable income 
 
 1954 
 
 1964 
 
 thousands 
 
 dollars 
 
 Connecticut 
 
 Maine 
 
 Massachusetts 
 
 New Hampshire 
 
 New Jersey 
 
 New York 
 
 Pennsylvania 
 
 Rhode Island 
 
 Vermont 
 
 Illinois 
 
 Indiana 
 
 Iowa 
 
 Kansas 
 
 Michigan 
 
 Minnesota 
 
 Missouri 
 
 Nebraska 
 
 North Dakota 
 
 Ohio 
 
 South Dakota 
 
 Wisconsin 
 
 Alabama 
 
 Arkansas 
 
 Delaware 
 
 District of Columbia 
 
 Florida 
 
 Georgia 
 
 Kentucky 
 
 Louisiana 
 
 Maryland 
 
 Mississippi 
 
 North Carolina 
 
 Oklahoma 
 
 South Carolina 
 
 Tennessee 
 
 Texas 
 
 Virginia 
 
 West Virginia 
 
 Arizona 
 
 California 
 
 Colorado 
 
 Idaho 
 
 Montana 
 
 Nevada 
 
 New Mexico 
 
 Oregon 
 
 Utah 
 
 Washington 
 
 Wyoming 
 
 Total U. S 
 
 2,208 
 
 917 
 
 4,857 
 
 554 
 
 5,249 
 
 15,818 
 
 10,798 
 
 817 
 
 375 
 
 9,087 
 4,266 
 2,631 
 2,031 
 7,040 
 3,127 
 4,139 
 1.329 
 
 623 
 8,962 
 
 662 
 3,599 
 
 3,051 
 
 1,781 
 366 
 828 
 3,462 
 3,651 
 2,912 
 2,887 
 2,642 
 2,079 
 4,185 
 2,157 
 2,234 
 3,364 
 8,449 
 3,483 
 1,927 
 
 932 
 12,738 
 
 1,520 
 589 
 613 
 215 
 784 
 
 1,652 
 762 
 
 2,539 
 300 
 
 161,915 
 
 2,816 
 
 996 
 
 5,505 
 
 639 
 
 6,688 
 
 17,903 
 
 11,764 
 
 927 
 
 405 
 
 10,618 
 5.019 
 2,808 
 2,224 
 8,617 
 3,673 
 4,501 
 1,490 
 641 
 
 10,174 
 
 716 
 
 4.177 
 
 3.409 
 
 1,929 
 511 
 810 
 5.798 
 4,268 
 3,143 
 3,516 
 3,480 
 2,299 
 4,920 
 2,483 
 2,561 
 3,809 
 10,602 
 4.414 
 1,768 
 
 1.670 
 
 18,576 
 
 1,990 
 
 699 
 
 708 
 
 401 
 
 996 
 
 1,980 
 
 1,001 
 
 3,080 
 
 346 
 
 193,468 
 
 27.5 
 
 8.6 
 
 13.3 
 
 15.3 
 
 27.4 
 
 13.2 
 
 8.9 
 
 13.5 
 
 8.0 
 
 17.7 
 6.7 
 9.5 
 
 22.4 
 
 17.5 
 8.7 
 
 12.1 
 2.9 
 
 13.5 
 8.2 
 
 16.1 
 
 21.8 
 31.7 
 10.6 
 17.6 
 15.1 
 14.6 
 13.2 
 25.5 
 26.7 
 - 8.3 
 
 79.2 
 
 1,984 
 1,343 
 1,663 
 1,378 
 1,872 
 1,821 
 1,614 
 1,579 
 1,283 
 
 1,854 
 1,649 
 1,484 
 1,482 
 1,686 
 1.418 
 1.476 
 1,446 
 1,384 
 1,752 
 1,379 
 1,580 
 
 1,010 
 955 
 2,102 
 2,156 
 1,313 
 1,126 
 1,103 
 1,204 
 1,491 
 817 
 1,035 
 1,272 
 1,022 
 1,118 
 1.457 
 1,290 
 1.185 
 
 1,381 
 1,816 
 1,499 
 1,338 
 1,604 
 1,984 
 1,313 
 1,590 
 1,379 
 1,744 
 1,750 
 
 2,791 
 1,869 
 2,535 
 2,137 
 2,605 
 2,708 
 2,216 
 2,197 
 1,942 
 
 2,610 
 2.222 
 2,122 
 2,041 
 2,359 
 2,087 
 2,266 
 2,144 
 1,894 
 2,235 
 1,855 
 2,214 
 
 1,538 
 1,558 
 2,783 
 3,003 
 1,957 
 1,755 
 1,687 
 1.650 
 2,480 
 1,388 
 1,704 
 1,892 
 1.487 
 1,678 
 1,904 
 1,931 
 1,781 
 
 1,960 
 2,656 
 2,252 
 1,819 
 2,004 
 2,998 
 1,779 
 2,230 
 1,935 
 2,273 
 2,214 
 
 2,225 
 
 Source: Sales Management, 1953-1965. 
 
 [43 
 

 
 
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Table A-4 
 AVERAGE EXPANSION INDICES OF CHAINS AND GROUPS* 
 
 Year 
 
 Net sales expansion index 
 (Year average) 
 
 Number of stores expansion index 
 (Year average) 
 
 
 Group I 
 
 Group 11 
 
 Group III 
 
 Group I 
 
 Group II 
 
 Group III 
 
 1953 
 
 100.0 
 107.8 
 114.9 
 125.2 
 136.0 
 145.7 
 156.9 
 160.4 
 165.2 
 170.7 
 184.4 
 
 100.0 
 111.6 
 125.6 
 146.9 
 183.9 
 206.4 
 226.0 
 244.9 
 262.1 
 290.7 
 313.4 
 
 100.0 
 103.6 
 118.6 
 146.8 
 168.0 
 190.9 
 201.5 
 216.6 
 224.9 
 242.3 
 279.9 
 
 100.0 
 97.8 
 96.5 
 96.3 
 96.9 
 98.7 
 100.0 
 100.3 
 100.7 
 100.8 
 109.5 
 
 100.0 
 98.9 
 107.5 
 118.3 
 124.7 
 134.4 
 148.4 
 160.2 
 174.2 
 167.7 
 164.5 
 
 100 
 
 1954 
 
 100 
 
 1955 
 
 112.2 
 
 1956 
 
 124.4 
 
 1957 
 
 126 8 
 
 1958 
 
 139.0 
 
 1959 
 
 161 
 
 I960 
 
 163.4 
 
 1961 
 
 175.6 
 
 1962 
 
 141.5 
 
 1963 
 
 192.7 
 
 
 
 Chain* 
 
 Net sales expansion index 
 (Chain index) 
 
 Number of stores expansion index 
 (Chain index) 
 
 
 Group I 
 
 Group II 
 
 Group III 
 
 Group I 
 
 Group II 
 
 Group III 
 
 1, 11, 21 
 
 124.4 
 126.5 
 154.6 
 146.6 
 162.5 
 215.7 
 267.0 
 126.5 
 230.8 
 175.3 
 
 176.8 
 251.8 
 211.8 
 136.4 
 185.5 
 195.8 
 345.4 
 161.8 
 230.0 
 217.9 
 
 113.5 
 112.9 
 298.1 
 170.3 
 88.0 
 323.9 
 164.0 
 321.4 
 423.4 
 178.7 
 
 100.5 
 
 101.3 
 
 81.9 
 
 73.8 
 
 124.7 
 
 207.4 
 
 228.0 
 
 75.0 
 
 128.2 
 
 127.0 
 
 134.4 
 115.5 
 140.8 
 
 97.9 
 237.0 
 
 96.3 
 277.1 
 160.7 
 268.8 
 108.5 
 
 86.8 
 
 2, 12, 22 
 
 98.0 
 
 3, 13, 23 
 
 129.7 
 
 4, 14, 24 
 
 140.0 
 
 5, 15, 25 
 
 125.0 
 
 6, 16, 26 
 
 237.5 
 
 7, 17, 27 
 
 126.9 
 
 8, 18, 28 
 
 320.0 
 
 9, 19, 29 
 
 256.3 
 
 10, 20, 30 
 
 152.6 
 
 
 
 Group I, chains 1-10; Group II, chains 11-20; Group III, chains 21-30 (see table A-5 for identification). 
 
 [46] 
 
Table A-5 
 EXPANSION RATIOS OF CHAINS 
 AND GROUPS* 
 
 Chain 
 number 
 
 Chain 
 
 Ratio 
 
 1 
 
 A&P 
 
 1.238 
 
 2 
 
 
 1.248 
 
 3 
 
 
 1.888 
 
 4 
 
 
 .199 
 
 5 
 
 
 1.303 
 
 6 
 
 Food Fair 
 
 1.040 
 
 7 
 
 
 1.171 
 
 8 
 
 
 1.688 
 
 9 
 
 
 1.801 
 
 10 
 
 
 1.380 
 
 
 
 
 
 1.296 
 
 
 
 
 11 
 
 
 1.316 
 
 12 
 
 
 2.779 
 
 13 
 
 
 1.504 
 
 14 
 
 
 1.393 
 
 15 
 
 Penn Fruit 
 
 .782 
 
 16 
 
 Red Owl 
 
 2.034 
 
 17 
 
 
 1.246 
 
 18 
 
 
 1.006 
 
 19 
 
 
 .856 
 
 20 
 
 
 2 000 
 
 
 
 
 
 1.432 
 
 
 
 
 21 
 
 
 1.308 
 
 22 
 
 
 1.152 
 
 23 
 
 Thriftimart 
 
 2.298 
 
 24 
 
 
 1.216 
 
 25 
 
 
 .704 
 
 26 
 
 
 1.364 
 
 27 
 
 
 1.292 
 
 28 
 
 Food Mart 
 
 1.004 
 
 29 
 
 
 1 652 
 
 30 
 
 
 1.171 
 
 
 
 
 
 1 316 
 
 
 
 
 * Net sales index divided by store expansion index. 
 
 [47] 
 
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APPENDIX C 
 
 Table C-l 
 REGRESSION ANALYSIS RESULTS— ALL 30 CHAINS* 
 
 Equation 
 
 Dependent 
 variable 
 
 Independent 
 variable 
 
 Constant 
 
 "b" Coef- 
 ficient 
 
 Coefficient 
 of corre- 
 lation 
 
 £-ratio 
 
 n 
 
 I 
 
 Net sales 
 
 Number of stores 
 
 25.9030 
 
 1.072900 
 
 .97860 
 
 84.04300 
 
 313 
 
 II 
 
 Net profit 
 
 Number of stores 
 
 1.1431 
 
 .011167 
 
 .92408 
 
 42.64000 
 
 313 
 
 III 
 
 Inventory 
 
 Net sales 
 
 3.9665 
 
 .057290 
 
 .95143 
 
 54.49900 
 
 313 
 
 IV 
 
 Current assests 
 
 Inventory 
 
 1.4138 
 
 1.587000 
 
 .99550 
 
 185.49300 
 
 313 
 
 V 
 
 Fixed assets 
 
 Total assets 
 
 1.8153 
 
 .387000 
 
 .96972 
 
 70.03500 
 
 313 
 
 VI 
 
 Total liabilities 
 
 Accounts payable 
 Current liabilities 
 
 9.3857 
 
 1.656890 
 1 959800 
 
 .99136 
 
 8.95870 
 16.32000 
 
 313 
 
 VII 
 
 Net worth 
 Total assets 
 
 Net sales 
 
 47.9168 
 
 .003349 
 
 .19330 
 
 3.47480 
 
 313 
 
 VIII 
 
 Fixed Assets 
 Total assets 
 
 Total assets 
 
 31.3950 
 
 .011456 
 
 .13786 
 
 2.45479 
 
 313 
 
 * Observations are based on annual data covering the period 
 pertaining to the 30 major retail food chains, 
 t Degrees of freedom 312 — 1.959. 
 
 1954-1962, inclusive. Observations consist of data 
 
 [54] 
 
Table C-2 
 REGRESSION ANALYSIS RESULTS— BY SIZE GROUP 
 
 Equation 
 
 Group 
 
 Dependent 
 variable 
 
 Independent 
 variable 
 
 Constant 
 
 "b" 
 Coeffi- 
 cient* 
 
 Coeffi- 
 cient of 
 corre- 
 lation 
 
 <-ratio 
 
 n 
 
 I 
 
 (1) 
 (2) 
 (3) 
 
 Net sales 
 
 Number of stores 
 
 -32.0583 
 84.5949 
 42.0390 
 
 1.0970 
 .8940 
 .6366 
 
 .94610 
 .27540 
 .21530 
 
 43.5585 
 6.3467 
 5.0506 
 
 110 
 
 108 
 95 
 
 11 
 
 (1) 
 (2) 
 (3) 
 
 Net profit 
 
 Number of stores 
 
 2.4506 
 
 1.1119 
 
 .7986 
 
 .0106 
 .0119 
 .0024 
 
 .79714 
 . 12720 
 .02150 
 
 20.6010 
 3.9302 
 1.4278 
 
 110 
 108 
 95 
 
 III 
 
 (1) 
 (2) 
 (3) 
 
 Inventory 
 
 Net sales 
 
 10.7090 
 
 - 4.5370 
 
 - 1.0578 
 
 .0546 
 .0969 
 .0842 
 
 .88610 
 .46730 
 .80830 
 
 28.9923 
 9.6437 
 19.8010 
 
 110 
 108 
 95 
 
 IV 
 
 (1) 
 (2) 
 (3) 
 
 Current assets 
 
 Inventory 
 
 - .5813 
 
 4.2617 
 
 .0683 
 
 1.6001 
 1.5205 
 1.6424 
 
 .99160 
 .90110 
 .97140 
 
 113.0970 
 31.0706 
 56.1980 
 
 110 
 108 
 95 
 
 V 
 
 (1) 
 (2) 
 (3) 
 
 Fixed assets 
 
 Total assets 
 
 6.7927 
 
 - .0910 
 
 .3670 
 
 .3145 
 .3558 
 .3174 
 
 .90230 
 .95650 
 .86660 
 
 31.4380 
 
 48.4858 
 24.5815 
 
 109 
 109 
 95 
 
 VI 
 
 (1) 
 (2) 
 (3) 
 
 Total liabilities 
 
 Accounts payable 
 Current liabilities 
 
 28.8510 
 
 1.9958 
 1.5949 
 
 .98060 
 
 7.5473 
 9.0168 
 
 110 
 
 
 5.2052 
 
 - .3594 
 3.2296 
 
 .97850 
 
 .8628 
 12.1524 
 
 108 
 
 
 2.4363 
 
 3.9019 
 .4672 
 
 .91900 
 
 8.1795 
 1.2846 
 
 95 
 
 VII 
 
 (1) 
 (2) 
 (3) 
 
 Net worth 
 Total assets 
 
 Net sales 
 
 .4861 
 50.1149 
 37.0850 
 
 .0031 
 - .0056 
 
 .1328 
 
 .07600 
 .00230 
 .07690 
 
 2.9823 
 .4950 
 
 2.7652 
 
 110 
 108 
 95 
 
 VIII 
 
 (1) 
 (2) 
 (3) 
 
 Fixed assets 
 Total assets 
 
 Total assets 
 
 32.1226 
 32.7098 
 
 20.8407 
 
 .0076 
 .0206 
 .5851 
 
 .01550 
 .01380 
 .02150 
 
 1.3021 
 1.2196 
 5.0458 
 
 110 
 108 
 95 
 
 D.F. 
 
 t 
 
 109 
 
 1.959 
 
 107 
 
 1.959 
 
 94 
 
 1.959 
 
 [55] 
 
Table C-3 
 REGRESSION ANALYSIS RESULTS— BY INDIVIDUAL CHAIN, GROUP II 
 
 Equa- 
 tion 
 
 Group 
 
 Dependent 
 variable 
 
 Independent 
 variable 
 
 Constant 
 
 "b" Coef- 
 ficient* 
 
 Coeffi- 
 cient of 
 corre 
 lation 
 
 t -ratio 
 
 n 
 
 I 
 
 (ID 
 
 Net sales 
 
 Number of stores 
 
 - 94.09500 
 
 2.30100 
 
 .915000 
 
 9.84600 
 
 11 
 
 
 (12) 
 
 
 
 347.99400 
 
 - .37250 
 
 .044380 
 
 .57010 
 
 
 
 (13) 
 
 
 
 417.91600 
 
 - .81600 
 
 .351200 
 
 2.20730 
 
 
 
 (14) 
 
 
 
 -257.43900 
 
 2.17240 
 
 .329600 
 
 2.10350 
 
 
 
 (15) 
 
 
 
 97.09500 
 
 .70678 
 
 .532800 
 
 3.20380 
 
 
 
 (16) 
 
 
 
 -621.31700 
 
 5.16150 
 
 .578900 
 
 3.51780 
 
 
 
 (17) 
 
 
 
 - 36.25000 
 
 1.85000 
 
 .968600 
 
 1.66690 
 
 
 
 (18) 
 
 
 
 13.38800 
 
 2.15700 
 
 .952800 
 
 13.48290 
 
 
 
 (19) 
 
 
 
 17.64400 
 
 1.42200 
 
 .982400 
 
 21.13890 
 
 
 
 (20) 
 
 
 
 40.11450 
 
 .90320 
 
 .130400 
 
 1.16160 
 
 
 II 
 
 (ID 
 
 Net profit 
 
 Number of stores 
 
 - 3.50300 
 
 .04807 
 
 .923700 
 
 10.43800 
 
 
 
 (12) 
 
 
 
 4.31880 
 
 - .00360 
 
 .023800 
 
 .41270 
 
 
 
 (13) 
 
 
 
 9.92980 
 
 - .03320 
 
 .617900 
 
 3.81500 
 
 
 
 (14) 
 
 
 
 10.12070 
 
 - .04560 
 
 .398200 
 
 2.44000 
 
 
 
 (15) 
 
 
 
 2.47700 
 
 - .01360 
 
 .384000 
 
 2.36870 
 
 
 
 (16) 
 
 
 
 - 3.86800 
 
 .03590 
 
 .306600 
 
 1.99500 
 
 
 
 (17) 
 
 
 
 - .06670 
 
 .02210 
 
 .928800 
 
 10.08340 
 
 
 
 (18) 
 
 
 
 1.33700 
 
 - .00760 
 
 . 109900 
 
 1.05450 
 
 
 
 (19) 
 
 
 
 . 13370 
 
 .01250 
 
 .969400 
 
 15.92900 
 
 10 
 
 
 (20) 
 
 
 
 2.28600 
 
 - .01360 
 
 . 105700 
 
 1.03160 
 
 
 III 
 
 (11) 
 
 Inventory- 
 
 Net sales 
 
 - 7.12330 
 
 .08720 
 
 .854900 
 
 7.28260 
 
 
 
 (12) 
 
 
 
 8.57350 
 
 .01902 
 
 .058800 
 
 .66104 
 
 
 
 (13) 
 
 
 
 - 49.87200 
 
 .30430 
 
 .745300 
 
 5.13160 
 
 
 
 (14) 
 
 
 
 - 8.28550 
 
 .11800 
 
 .530800 
 
 3.19060 
 
 
 
 (15) 
 
 
 
 - 1.00330 
 
 .07110 
 
 .922100 
 
 10.32200 
 
 
 
 (16) 
 
 
 
 - 1.61210 
 
 .07650 
 
 .868300 
 
 7.70390 
 
 
 
 (17) 
 
 
 
 - .02720 
 
 .06150 
 
 .901000 
 
 9.05100 
 
 
 
 (18) 
 
 
 
 - .62150 
 
 .07910 
 
 .859500 
 
 7.42100 
 
 
 
 (19) 
 
 
 
 .97100 
 
 .06010 
 
 .985500 
 
 23.35700 
 
 10 
 
 
 (20) 
 
 
 
 - 1.40300 
 
 .07290 
 
 .526800 
 
 3.16500 
 
 
 IV 
 
 (ID 
 
 Current assets 
 
 Inventory 
 
 - 1.72050 
 
 2.21760 
 
 .985800 
 
 25.02600 
 
 
 
 (12) 
 
 
 
 31.96840 
 
 .37910 
 
 .076700 
 
 .76270 
 
 
 
 (13) 
 
 
 
 - .20690 
 
 1.45600 
 
 .993700 
 
 37.85500 
 
 
 
 (14) 
 
 
 
 1.47800 
 
 1.49800 
 
 .926700 
 
 10.66800 
 
 
 
 (15) 
 
 
 
 1.53500 
 
 1.48960 
 
 .921100 
 
 10.24800 
 
 
 
 (16) 
 
 
 
 .09710 
 
 1.54190 
 
 .981700 
 
 22.02670 
 
 
 
 (17) 
 
 
 
 2.50860 
 
 1.66520 
 
 .926400 
 
 10.64480 
 
 
 
 (18) 
 
 
 
 .71910 
 
 1.82080 
 
 .864200 
 
 7.56950 
 
 
 
 (19) 
 
 
 
 .74850 
 
 1.60700 
 
 .963200 
 
 14.47830 
 
 
 
 (20) 
 
 
 
 1.69350 
 
 1.63480 
 
 9880b0 
 
 27.29500 
 
 
 V 
 
 (11) 
 
 Fixed assets 
 
 Total assets 
 
 - 2.83950 
 
 .34680 
 
 .983900 
 
 23.52100 
 
 
 
 (12) 
 
 
 
 - .36430 
 
 .33830 
 
 .942100 
 
 10.67100 
 
 
 
 (13) 
 
 
 
 - .35620 
 
 .35870 
 
 .959600 
 
 14.62200 
 
 
 
 (14) 
 
 
 
 - 2.71650 
 
 .53370 
 
 .877600 
 
 8.03530 
 
 
 
 (15) 
 
 
 
 - .30000 
 
 .39820 
 
 .968300 
 
 16.58950 
 
 
 
 (16) 
 
 
 
 - .73440 
 
 .31730 
 
 .905100 
 
 9.26800 
 
 
 
 (17) 
 
 
 
 - .44110 
 
 .37810 
 
 .966000 
 
 16.00660 
 
 
 
 (18) 
 
 
 
 1.14450 
 
 .32380 
 
 .737100 
 
 5.02320 
 
 
 
 (19) 
 
 
 
 - 2.61910 
 
 .46160 
 
 .989200 
 
 27.08300 
 
 10 
 
 
 (20) 
 
 
 
 .92730 
 
 .25160 
 
 .909700 
 
 9.52260 
 
 11 
 
 [56] 
 

 
 
 Table C-3 
 
 (Continued) 
 
 
 
 
 
 
 
 
 
 
 
 Coeffi- 
 
 
 
 Equa- 
 tion 
 
 Group 
 
 Dependent 
 variable 
 
 Independent 
 variable 
 
 Constant 
 
 "b" Coef- 
 ficient* 
 
 cient of 
 corre- 
 lation 
 
 2-ratio 
 
 n 
 
 VI 
 
 (11) 
 
 Total liabilities 
 
 Accounts payable 
 Current liabilities 
 
 6.96689 
 
 -1.94610 
 4.04490 
 
 .985600 
 
 .71936 
 2.91730 
 
 11 
 
 
 
 5.12470 
 
 
 3.19970 
 
 
 
 (12) 
 
 
 
 6.47280 
 
 - .42980 
 
 .909200 
 
 .38950 
 
 9 
 
 
 
 1.03810 
 
 
 .48330 
 
 
 
 (13) 
 
 
 
 - 3.08690 
 
 2.41260 
 
 .993000 
 
 1.78270 
 
 11 
 
 
 
 -1.53230 
 
 
 .72340 
 
 
 
 (14) 
 
 
 
 4.81780 
 
 5.08150 
 
 .904100 
 
 3.31780 
 
 11 
 
 
 
 -2.04123 
 
 
 .98122 
 
 
 
 (15) 
 
 
 
 2.60520 
 
 6.56010 
 
 .928900 
 
 4.42900 
 
 11 
 
 
 
 -1.17110 
 
 
 .53600 
 
 
 
 (16) 
 
 
 
 - .36460 
 
 4.06800 
 
 .979000 
 
 3.04980 
 
 11 
 
 
 
 -1.86400 
 
 
 1.16240 
 
 
 
 (17) 
 
 
 
 2.16110 
 
 3.88500 
 
 .966000 
 
 3.24430 
 
 11 
 
 
 
 2.04750 
 
 
 2.91840 
 
 
 
 (18) 
 
 
 
 6.58840 
 
 2.67580 
 
 .922400 
 
 9.71120 
 
 11 
 
 
 
 5. 15910 
 
 
 1.82450 
 
 
 
 (19) 
 
 
 
 - 8.54680 
 
 - .18410 
 
 .972500 
 
 .09060 
 
 10 
 
 
 
 -1.59730 
 
 
 .48030 
 
 
 
 (20) 
 
 
 
 3.05670 
 
 3.71480 
 
 .889500 
 
 1.88260 
 
 11 
 
 VII 
 
 (ID 
 
 Net Worth 
 
 Net sales 
 
 .33020 
 
 .03980 
 
 . 103700 
 
 1.02050 
 
 11 
 
 
 (12) 
 
 Total assets 
 
 
 9.75380 
 
 . 10770 
 
 .827800 
 
 5.80100 
 
 9 
 
 
 (13) 
 
 
 
 41.32760 
 
 - .01010 
 
 .006800 
 
 .24789 
 
 11 
 
 
 (14) 
 
 
 
 27.55200 
 
 - .11640 
 
 .018800 
 
 .41580 
 
 11 
 
 
 (15) 
 
 
 
 80.65900 
 
 - .09450 
 
 .325900 
 
 2.08600 
 
 11 
 
 
 (16) 
 
 
 
 38.50100 
 
 .01980 
 
 .008900 
 
 .28387 
 
 11 
 
 
 (17) 
 
 
 
 50.65200 
 
 - .00043 
 
 .000045 
 
 .02014 
 
 11 
 
 
 (18) 
 
 
 
 73.65500 
 
 - .24570 
 
 .690900 
 
 4.48560 
 
 11 
 
 
 (19) 
 
 
 
 47.55200 
 
 .02910 
 
 .117070 
 
 1.02990 
 
 10 
 
 
 (20) 
 
 
 
 33.98990 
 
 .22270 
 
 .619340 
 
 3.82660 
 
 11 
 
 VIII 
 
 (ID 
 
 Fixed assets 
 
 Total assets 
 
 11.84200 
 
 . 17620 
 
 .657800 
 
 4.15800 
 
 11 
 
 
 (12) 
 
 Total assets 
 
 
 2.22400 
 
 .44040 
 
 .884200 
 
 7.31100 
 
 9 
 
 
 (13) 
 
 
 
 33.40400 
 
 .00800 
 
 .008100 
 
 .27190 
 
 11 
 
 
 (14) 
 
 
 
 - .43340 
 
 1.29260 
 
 .982300 
 
 17.76700 
 
 11 
 
 
 (15) 
 
 
 
 37.23400 
 
 .04910 
 
 .041800 
 
 .62690 
 
 11 
 
 
 (16) 
 
 
 
 10.63900 
 
 .49810 
 
 .594000 
 
 3.62830 
 
 11 
 
 
 (17) 
 
 
 
 38.07100 
 
 - .05220 
 
 .027700 
 
 .50600 
 
 11 
 
 
 (18) 
 
 
 
 38.44700 
 
 - .05690 
 
 .007600 
 
 .26220 
 
 11 
 
 
 (19) 
 
 
 
 25.34600 
 
 .29690 
 
 .818700 
 
 6.01090 
 
 10 
 
 
 (20) 
 
 
 
 33.67400 
 
 - .15350 
 
 .043200 
 
 .63760 
 
 11 
 
 D.F. 
 10 
 
 t 
 
 2.228 
 2.306 
 
APPENDIX D 
 
 Application of Markov 
 technique to structure data 
 
 Economists are often interested in the 
 characteristics of institutional changes over 
 time as well as in the paths these char- 
 actistics are likely to follow in the future. 
 If, in a given sequence of events, the out- 
 come of each event depends on some 
 chance occurrence with a known prob- 
 ability, then such a sequence is called a 
 "stochastic process" to which a Markov 
 Chain Analysis may be applicable (Judge 
 and Swanson, 1961). Such an analysis has 
 been attempted in our study. 
 
 Table D-l shows the changes in the 
 market shares of the 30 largest retail food 
 chains during the 1954-1962 period. Our 
 first step was to develop six classifications 
 according to market share. With these 
 classifications, we could construct a cross- 
 classification table showing how many 
 chains moved into or out of each classifi- 
 cation during this 1954-1962 observation 
 period. 
 
 Given the information in table D-2, it 
 is then possible to construct a possibility 
 tree and attach branch weights that de- 
 scribe the process as it moves through any 
 finite number of steps. Alternatively, the 
 transition probabilities (Pa) can now be 
 calculated and represented in the form of 
 the following transition matrix "P" (table 
 D-S). 
 
 Where's P i} = 1 and Pi^O for all i and 
 
 i =. 1 
 
 /. The elements of "P" denote the prob- 
 ability of moving from some class / to class 
 i in the next step. Since the elements of 
 this matrix are nonnegative and the sum 
 of the elements in any column is I, each 
 column of the matrix is called a probabil- 
 ity vector and the matrix "P" becomes a 
 stochastic matrix. This matrix, together 
 
 with an initial distribution W° 
 
 pletely defines our Markov Chain Process. 
 Given this information, we can determine 
 the outcome of, say, the nth period in the 
 
 Table D-l 
 
 SALES OF INDIVIDUAL CHAINS AS A 
 
 PERCENTAGE OF TOTAL SALES OF 
 
 30 MAJOR CHAINS, 1954 AND 1962 
 
 Chain 
 
 Percentage of total 
 sales of 30 chains 
 
 
 1954 
 
 1962 
 
 A&P 
 
 35.72 
 16.24 
 9.93 
 5.41 
 4.66 
 3.12 
 2.04 
 3.96 
 1.81 
 3.12 
 
 2.18 
 1.12 
 1.49 
 1.16 
 
 .84 
 .96 
 .36 
 .63 
 .55 
 .56 
 
 .77 
 .79 
 .43 
 .52 
 .49 
 .23 
 .34 
 .14 
 .13 
 .24 
 
 27.52 
 
 
 13.18 
 
 
 10.23 
 
 
 5.44 
 
 
 5.14 
 
 Food Fair 
 
 4.85 
 
 
 4.06 
 
 First National 
 
 4.05 
 
 
 3.37 
 
 
 2.36 
 
 
 2.90 
 
 
 2.05 
 
 
 2.62 
 
 
 .93 
 
 Penn Fruit 
 
 .91 
 
 Red Owl 
 
 1.47 
 
 
 1.22 
 
 
 .71 
 
 
 1.51 
 
 
 .46 
 
 
 .55 
 
 
 .56 
 
 Thriftimart 
 
 1.10 
 
 
 .64 
 
 
 .32 
 
 
 .56 
 
 
 .18 
 
 Food Mart 
 
 .35 
 
 
 .43 
 
 
 .33 
 
 
 
 Total 
 
 100.00 
 
 100.00 
 
 
 
 future, i.e., in matrix language: 
 
 rn 
 
 w°P - w 1 where w 1 - 
 w^P = w 2 where w 2 - 
 
 w n - x P - w n where w n - infinite future dis- 
 tribution. 
 Alternatively, this process may be written: 
 
 w n - w opn 
 
 [58 J 
 
Table D-2 
 CROSS CLASSIFICATION TABLE 
 
 
 Size of firm 
 (1962) 
 
 Firms moving from: 
 
 
 Firms 
 
 moving 
 
 to: 
 
 A 
 
 B 
 
 C 
 
 D 
 
 E 
 
 F 
 
 
 Size of firm (1954) 
 
 Total 
 
 
 .1000- 
 
 .2714 
 
 per cent 
 
 .2715- 
 
 .7366 
 
 per cent 
 
 .7367- 
 
 1.9991 
 
 per cent 
 
 1.9992- 
 
 5.4256 
 
 per cent 
 
 5.4257- 
 14.7251 
 per cent 
 
 14.7252- 
 39.9639 
 per cent 
 
 
 A 
 
 .1000- .2714 per cent 
 
 
 
 1 
 
 
 
 
 
 
 
 
 
 1 
 
 B 
 
 .2715- .7366 per cent 
 
 4 
 
 4 
 
 2 
 
 
 
 
 
 
 
 10 
 
 C 
 
 .7367- 1.9991 percent 
 
 
 
 3 
 
 3 
 
 
 
 
 
 
 
 6 
 
 D 
 
 1.9992- 5.4256 per cent 
 
 
 
 
 
 3 
 
 6 
 
 
 
 
 
 9 
 
 E 
 
 5.4257-14.7251 percent 
 
 
 
 
 
 
 
 1 
 
 1 
 
 1 
 
 3 
 
 F 
 
 14.7252-39.9639 per cent 
 
 
 
 
 
 
 
 
 
 
 
 1 
 
 1 
 
 Tc 
 
 >tal 
 
 4 
 
 8 
 
 8 
 
 7 
 
 1 
 
 2 
 
 30 
 
 
 
 If: P is a transition matrix for a "regu- 
 lar (Hart and Prais, 1956) chain, 
 then the powers of P n approach a 
 matrix T, each row T is the same 
 probability vector w, and the com- 
 ponents of w are all positive. 
 If: P is a transition matrix for a regular 
 chain and T and w are as described 
 above, then the unique vector w is 
 the unique probability vector such 
 that wP = w. 
 In other words, this states that if P is a 
 transition matrix for a regular chain, there 
 exists a unique vector w that is both a 
 fixed vector for P and a probability vector 
 whose distribution at time n moves toward 
 this equilibrium vector irrespective of the 
 initial distribution or starting state: 
 e.g., P n — » T as n — > 00 
 
 m 
 i 
 
 and T = e*w where e = 
 equilibrium vector or 
 distribution. 
 
 and w is the 
 probability 
 
 knowns from which the unique values of 
 w can be derived. 
 
 Based on the changes that took place 
 during the 1954-1962 period, we are then 
 able to use the Markov technique to de- 
 termine: 13 
 
 1. the probable structural characteristics 
 of the nation's 30 largest chains at any 
 time (eight-year multiples past 1954) 
 in the future; and 
 
 Table D-3 
 
 STOCHASTIC TRANSITION 
 
 MATRIX "P" 
 
 Firms 
 mov- 
 
 Firms moving from: 
 
 ing to: 
 
 A 
 
 B 
 
 C 
 
 D 
 
 E 
 
 F 
 
 A 
 
 
 
 12.50 
 
 
 
 
 
 
 
 
 
 B 
 
 100.00 
 
 50.00 
 
 25.00 
 
 
 
 
 
 
 
 C 
 
 
 
 37.50 
 
 37.50 
 
 
 
 
 
 
 
 D 
 
 
 
 
 
 37.50 
 
 85.71 
 
 
 
 
 
 E 
 
 
 
 
 
 
 
 14.29 
 
 100.00 
 
 50.00 
 
 F 
 
 
 
 
 
 
 
 
 
 
 
 50.00 
 
 Using this information, one can com- 
 bine equations and form a system of n 
 linearly independent equations with n un- 
 
 13 For more complete descriptions and applications of the Markov Chain Process, see the 
 following: Padberg, 1962; Kemeny, J. G., et ah, 1957; Anderson and Goodman, 1957; and 
 Collins and Preston, 1961. 
 
 [59] 
 
2. the length of time it would take for 
 the dynamics of structural change to 
 reach an equilibrium. 14 Note, how- 
 ever, this term "equilibrium" does not 
 indicate that the 30 food chains will 
 no longer grow or decrease in size or 
 change classifications. In fact, chains 
 will continue to move from one class 
 to another; however, the probability 
 of any chain moving into a given 
 classification, in equilibrium, is ex- 
 actly offset by the probability of a 
 chain moving out of that same classi- 
 fication (Adelman, 1958). 
 
 Limitation to the Markov 
 analysis 
 
 All statistical endeavors such as this have 
 some limitations — some created by data 
 deficiencies and inaccuracies, others in- 
 herent in the statistical process itself. 
 
 In the more common and rigorous ver- 
 sion of the Markov Chain Analysis, an 
 extra column and row are added to the 
 transition matrix. This allows for the in- 
 clusion of data pertaining to the possibil- 
 ity of chains entering or leaving the exist- 
 ing classifications. Unfortunately, however, 
 information on this type of an occurrence 
 was not available. Without the data neces- 
 sary for this type of process expansion, it 
 was necessary that our analysis deal with 
 a type of "closed industry" where barriers 
 of entry and exit prohibited a more rigor- 
 ous study. This restriction admittedly has 
 reduced the applicability of our projec- 
 tions and this must be taken in account 
 with respect to their reliability, especially 
 with respect to any long-run projections. 15 
 
 According to Adelman (1958), two major 
 limitations in the Markov technique itself 
 must be recognized and, if possible, 
 avoided. The first relates to the compara- 
 tive size of the firms falling within the 
 total range of one's classifications. For ex- 
 ample, it is supposedly much easier for a 
 
 firm with $500,000 annual sales to raise 
 its total sales by $1,000 than it is for a firm 
 with only $100,000 annual sales volume to 
 accomplish a similar increase. In other 
 words, in a given set of circumstances, it 
 is probable that the sales volume of a large 
 firm will fluctuate by greater absolute 
 amounts than that of a smaller firm. To 
 eliminate this distortion created by the use 
 of "absolute" measurements, all data were 
 converted into "relative" measurements. 
 All sales data were converted into per- 
 centages relative or proportional to total 
 chain sales. 
 
 The second limitation is related to the 
 establishment of the classification bound- 
 aries. It is obvious that by establishing re- 
 latively many classifications with small 
 ranges, one will find the firms rapidly mov- 
 ing from one classification to another. 
 Conversely, few classifications with ex- 
 tremely large ranges will create an environ- 
 ment where only a very few firms will ever 
 change classifications during the observa- 
 tion period. Additionally, the larger firms 
 again supposedly have the potential to 
 expand (or decrease) their relative sales 
 more than their smaller competitors. 
 Therefore, Adelman states, "The class in- 
 tervals were constructed so that their ab- 
 solute width was greater for large than for 
 small enterprises." Even this procedure, 
 however, should not be subject to the per- 
 sonal whims of the statistician or the 
 "niceties" of the data accumulations. It 
 must basically be a mathematical process, 
 free from personal bias and chosen with 
 some degree of scrutiny. 
 
 The class interval procedure used for 
 this analysis was a mathematical technique 
 called "proportionality from the upper 
 limit." 18 It follows on the opposing page. 
 
 Next, a limitation on the results them- 
 selves must be noted. One must recall that 
 the percentages used herein were relative 
 measurements. Hence, table 20 show that 
 in the year 2010 each of the 30 chains 
 
 14 However, in this particular application, the matrix of transitional probabilities (P) did 
 not meet the requirement of "regularity." In this case, any discussion of an equilibrium be- 
 comes meaningless since all firms move into the absorbing state (or states) as n — > 00. 
 
 15 In a similar way, Collins and Preston (1960) applied the Markov process to the food 
 processing industry. Fortunately, their information allowed them to consider the so-called 
 "not-on-list" column and row. 
 
 16 Pankey, Victor, "Proportionality from the Upper Limit," mathematical technique, Davis: 
 University of California, Department of Agricultural Economics, October 1965, unpublished 
 manuscript. 
 
 [60] 
 
PROPORTIONALITY FROM THE UPPER LIMIT 
 
 a b c 
 
 ! I I I I I I 
 
 12 3 4 5 
 
 % % % % % 10% 
 
 40 = upper limit 40 — e = kiO .: k = 
 
 e = first division 
 
 of classes e = 40 — £40 
 
 40(1 - k) 
 
 20% 
 
 40 - e 
 
 e = upper limit 
 
 He) where (e) = 40 - &40 
 
 d = second division 
 
 of classes e — He) = d 
 
 e(l - ft) - d 
 
 40(1 - AX1 -k) = d 
 
 upper limit d-c = k(d) where '<*) = 40O - ft)(l - k) 
 
 40(1 - fe)« 
 
 third division 
 of classes 
 
 c = d - kd 
 
 c = (1 - &)rf 
 c = (1 - k)* 40 
 
 c = upper limit c — b = k(c) where (c) = 40(1 — &) J 
 
 b = 
 
 fourth division 
 of classes 
 
 b = c — kc 
 
 b = (1 - k)* 40 
 
 upper limit 
 
 fifth division 
 of classes 
 
 Hb) where (b) = (1 - &)« 40 
 (1 - &)» 40 
 
 30% 
 
 a = upper limit 
 . 1 = lower class limit 
 .1 = Wo) where (a) = 40U 
 .1 = a — ka 
 
 .1 = (1 - &)M0 
 
 40% 
 
 (1 - fc)« 
 
 40 
 
 1 -k 
 
 Vlo 
 
 k - l -\j 
 
 40 
 
 = .6318 
 
 
 Range 0.1-40.0% 
 
 
 Size 
 classes 
 
 Per cent of 
 total sales 
 
 a = .2714 
 
 
 A 
 
 .1000- .2714 
 
 6= .7367 
 
 
 B 
 
 .2715- .7367 
 
 c= 1.9992 
 
 
 C 
 
 .7368- 1.9992 
 
 rf = 5.4257 
 
 
 D 
 
 1.9993- 5.4257 
 
 9 = 14.7252 
 
 
 E 
 
 5.4258-14.7252 
 
 
 
 F 
 
 14.7253-40.0000 
 
 Table D-4 
 STEPWISE PRODUCTS OF MATRIX MULTIPLICATION 
 
 Firms moving from: 
 
 Firms 
 moving 
 to: 
 
 
 
 12.50 
 
 
 
 
 
 
 
 
 
 100.00 
 
 50.00 
 
 25.00 
 
 
 
 
 
 
 
 
 
 37.50 
 
 37.50 
 
 
 
 
 
 
 
 
 
 
 
 37.50 
 
 85.71 
 
 
 
 
 
 
 
 
 
 
 
 14.29 
 
 100.00 
 
 50.00 
 
 
 
 
 
 
 
 
 
 
 
 50.00 
 
 [61] 
 
12.50 
 
 6.250 
 
 3.125 
 
 
 
 
 
 
 
 50.00 
 
 46.875 
 
 21.875 
 
 
 
 
 
 
 
 37.50 
 
 32.813 
 
 23.438 
 
 
 
 
 
 
 
 
 
 14.063 
 
 46.204 
 
 73.453 
 
 
 
 
 
 
 
 
 
 5.359 
 
 26.538 
 
 100.00 
 
 75.00 
 
 
 
 
 
 
 
 
 
 
 
 25.00 
 
 
 5.859 
 
 4.736 
 
 2 490 
 
 
 
 
 
 
 
 37.891 
 
 32.275 
 
 16.943 
 
 
 
 
 
 
 
 29.883 
 
 25.415 
 
 13.843 
 
 
 
 
 
 
 
 24.358 
 
 32.083 
 
 47.847 
 
 53.967 
 
 
 
 
 
 2.010 
 
 5.490 
 
 18.876 
 
 46.033 
 
 100.00 
 
 93.750 
 
 
 
 
 
 
 
 
 
 
 
 6.250 
 
 
 2.882 
 
 2.439 
 
 1.293 
 
 
 
 
 
 
 
 19.513 
 
 16.518 
 
 8.758 
 
 
 
 
 
 
 
 15.517 
 
 13.136 
 
 6.967 
 
 
 
 
 
 
 
 41.027 
 
 40.983 
 
 38.488 
 
 29.124 
 
 
 
 
 
 21.061 
 
 26.924 
 
 44.495 
 
 70.876 
 
 100.00 
 
 99.609 
 
 
 
 
 
 
 
 
 
 
 
 .391 
 
 
 .760 
 
 .643 
 
 .341 
 
 
 
 
 
 
 
 5.144 
 
 4.355 
 
 2.309 
 
 
 
 
 
 
 
 4.091 
 
 3.463 
 
 1.836 
 
 
 
 
 
 
 
 27.100 
 
 24.762 
 
 18.010 
 
 8.482 
 
 
 
 
 
 62.904 
 
 66.777 
 
 77.504 
 
 91.518 
 
 100.00 
 
 99.998 
 
 
 
 00 
 
 
 
 
 
 
 
 .002 
 
 
 .053 
 
 .045 
 
 .024 
 
 
 
 
 
 
 
 .358 
 
 .303 
 
 .160 
 
 
 
 
 
 
 
 .284 
 
 .241 
 
 .128 
 
 
 
 
 
 
 
 4.515 
 
 3.977 
 
 2.523 
 
 .719 
 
 
 
 
 
 94.790 
 
 95.435 
 
 97.165 
 
 99.281 
 
 100.00 
 
 99.999 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 .002 
 
 .002 
 
 .001 
 
 
 
 
 
 
 
 .002 
 
 .001 
 
 
 
 
 
 
 
 
 
 .001 
 
 
 
 
 
 
 
 
 
 
 
 .056 
 
 
 
 
 
 .005 
 
 
 
 
 
 99.940 
 
 99.969 
 
 99.969 
 
 99.995 
 
 100.00 
 
 99.999 
 
 
 
 
 
 
 
 
 
 
 
 
 
 [62] 
 
should have sales equaling about 5 per run economic projections (more than 25 
 cent of the average total annual chain sales years) are quite speculative. In view of 
 for the period 1954-1962. Since total chain the dynamic nature of our food industry, 
 sales in 2010 are likely to be much more such projections are even more precarious, 
 than 1962 sales, these results seem reason- Nevertheless, short-term (5-10 years) ap- 
 able (5 per cent refers to level of total praisal may prove useful in business plan- 
 sales in 1962). ning, since it indicates the probable direc- 
 Finally, it must be recognized that long- tion and magnitude of future changes. 
 
 [63] 
 
APPENDIX E 
 
 Table E-l 
 COMPARATIVE PROFIT DATA, SELECTED INDUSTRIES, 1964, 1959, 1954 
 
 
 Retail 
 
 food 
 
 industry 
 
 Food 
 processing 
 industry 
 
 Durable 
 
 goods 
 industry 
 
 Other con- 
 sumer goods 
 industry 
 
 Agriculture 
 
 Nation's 
 
 
 (All food 
 stores) 
 
 (63 largest 
 firms) 
 
 (61 largest 
 firms) 
 
 (39 largest 
 firms) 
 
 (All farms) 
 
 500 largest 
 
 industrial 
 
 corporations 
 
 1964: 
 
 dollars 
 
 
 20,583,834 
 254,048 
 
 29,860,031 
 1,019,900 
 
 85,230,345 18,003,273 
 5,768,288 1,328,232 
 
 41,700,000 
 6,700,000* 
 
 266,497,511 
 17,237,516 
 
 Net profit (after taxes) 
 
 
 per cent 
 
 Profit as percentage of sales. 
 Profit as percentage of net 
 
 1.230 
 10.810 
 
 3.416 
 11.450 
 
 6.767 
 13.696 
 
 7.377 
 13.008 
 
 16.067 
 3.641 
 
 6.468 
 12.105 
 
 
 
 
 (28 largest 
 firms) 
 
 (61 largest 
 firms) 
 
 (85 largest 
 firms) 
 
 (34 largest 
 firms) 
 
 (All farms) 
 
 
 1959: 
 
 dollars 
 
 Sales 
 
 16,880,304 
 214,785 
 
 24,253,174 
 
 722,369 
 
 66,860,685 
 4,249,029 
 
 11,878,864 
 823,625 
 
 37,479,000 
 11,279,000* 
 
 197,394,885 
 
 Net profit (after taxes) 
 
 11,986,772 
 
 
 per cent 
 
 Profit as percentage of sales . 
 Profit as percentage of net 
 
 1.272 
 13.142 
 
 2.978 
 10.786 
 
 6.355 
 12.309 
 
 6.933 
 12.869 
 
 10.486 
 2.246 
 
 6.072 
 11.003 
 
 
 
 
 (29 largest 
 firms) 
 
 (67 largest 
 firms) 
 
 (84 largest 
 firms) 
 
 (35 largest 
 firms) 
 
 (All farms) 
 
 
 1954: 
 
 dollars 
 
 Sales 
 
 11,039,253 
 115,139 
 
 19,373,995 
 456,976 
 
 42,347,046 
 2,612,713 
 
 7,385,349 
 508,540 
 
 34,355,000 
 4,951,000* 
 
 136,782,913 
 
 Net profit (after taxes) 
 
 8,266,557 
 
 
 per cent 
 
 Profit as percentage of sales. 
 Profit as percentage of net 
 
 1.050 
 
 9.880 
 
 2.358 
 
 NA 
 
 6.169 
 
 NA 
 
 6.885 
 
 NA 
 
 14.411 
 
 3.482 
 
 6.043 
 
 NA 
 
 
 
 
 
 * Method Used to Calculate Agriculture's Net Income 
 Cash receipts from farm marketings . 
 Government payments to farmers . . 
 Nonmoney income 
 
 1963 
 
 billion dollars 
 
 36.9 
 
 1.7 
 
 3.1 
 
 Realized gross farm income . 
 Farm production expenses. . 
 
 Farm operators' realized net income. 
 Net change in farm inventories 
 
 Farm operators' total net income 
 
 Farm operators' and family labor charge. 
 
 41.7 
 -29.2 
 
 12.5 
 .5 
 
 13.0 
 -6.3 
 
 Farm operators' actual total net income (profit) . 
 
 6.7 
 
 Source: Fortune, 1955, 1960, 1965; Oarlock, et al„ 1965; and U. S. Department of Agriculture, Farm Income Situation, 
 1964. 
 
 [64] 
 
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 To simplify this information, it is sometimes necessary to use trade names of prod- 
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 implied of similar products not mentioned. 
 
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