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The Restaurant Industry

Franchising plays an important role in the U.S. Restaurant Industry.  According to the 2012 U.S. Economic Census, franchise restaurants numbered almost 151,000 or about one third of all full¹ and limited-service² restaurants in the U.S.  Franchising is much more prevalent in the limited-service sector with about 122,000 or 54% of the total number of limited-service restaurants, which numbered about 225,000 in 2012.

This compares with 29,000 or 12.5% of the total number of full-service restaurants which numbered almost 231,000.  The map below illustrates the geographic distribution of full-service restaurants in the U.S.  The number by state ranged from 554 in Wyoming to just over 28,000 in California.

The Number of Full-Service Restaurants by State 2012
(Scroll over a state to highlight details)

Despite the role played by franchise restaurants,  there is little information available on the efficiency³ of full-service franchise restaurants compared to full-service non-franchise restaurants.  Our post therefore examines the effects of franchising on the efficiency of full-service restaurants at the state level.  We do this by using a series of Data Envelopment Analysis models to measure the aggregate efficiency of restaurants at the state level.  We first examine all full-service restaurants and follow by comparing the efficiency of non-franchise restaurants with franchise restaurants.  Finally, we examine the difference in efficiency of franchisee-owned restaurants and franchisor-owned restaurants.

Data released in the 2012 Economic Census for Accommodation and Food Services was used in our analysis.  Full-service restaurants comprise establishments primarily engaged in providing food services to patrons who order and are served while seated (i.e., waiter/waitress service) and pay after eating.  These establishments may provide this type of food service to patrons in combination with selling alcoholic beverages, providing carry out services, or presenting live nontheatrical entertainment.

Based on our analysis of the aggregate performance of full-service restaurants at the state level, we find a statistically significant difference between the mean efficiency of franchise and non-franchise full-service restaurants, with non-franchise full-service restaurants slightly more efficient than franchise full-service restaurants (Two-tailed p value = 0.03722).  We also demonstrate that of the franchise full-service restaurants, the franchisee-owned restaurants were more efficient that the franchisor-owned restaurants.

 

Data Envelopment Analysis

For the purposes of determining the efficiency of the full-service restaurant industry in each state, we used Data Envelopment Analysis (DEA).  DEA is a non-parametric linear programming technique that computes a comparative ratio of outputs to inputs for each unit (state in our case), which is reported as the relative efficiency score. The efficiency score is usually expressed as either a number between zero and one or 0 and 100%.  A unit (state) with a score less than one is deemed inefficient relative to other units (states).  DEA’s main usefulness, however, lies in its ability to generate potential improvements (i.e. achievable targets) for inefficient units and identifying the units to benchmark.  DEA modeling allows for the selection of inputs and outputs.  For the purpose of choosing a final set of inputs and outputs we examined:

  • Non-discretionary or uncontrolled inputs (number of restaurants, population and medium household income)
  • Discretionary or controllable inputs (annual payroll, number of paid employees and number of seats), and
  • Outputs (value of sales)

Our final model used three inputs; number of restaurants, state population, annual payroll and one output; sales.  Detailed statistics for the inputs and outputs for each of the states are found in the table at the bottom of the post.  The data set was analyzed under the assumptions of input minimization and variable returns to scale. For an explanation of how DEA has been used to determine the efficiency of individual restaurants, please refer to the articles listed at the end of the post.

 

Results

The following table shows the relative efficiency scores for the different sectors of the full-service restaurant industry in each of the 51 states.  The full-service restaurant industry in twelve states, including California, New York, Texas and Florida was deemed efficient, while in 39 it was deemed inefficient with and average efficiency score of 90.5%.

Efficiency Score Ranking for Full-Service Restaurants Across U.S. States

StateAll RestaurantsNon-Franchise
Restaurants
Franchise
Restaurants
Franchisee-Owned RestaurantsFranchisor-Owned Restaurants
Average92.792.990.890.082.7
Alaska10010088.296n/a
California100100100100100
District of Columbia100100100100100
Florida100100100100100
Hawaii10010010010092
Massachusetts10010082.584.475.8
Nevada100100100100100
New Jersey10010010098.5100
New York10010010010089.8
North Dakota10010010010065.6
Texas100100100100100
Wyoming100100100100100
Delaware98.495.9100100100
Montana98.499.796.8n/an/a
Mississippi98.497.510093.199.3
Maryland98.398.490.68985.3
Pennsylvania96.698.385.784.580.4
Rhode Island95.294.796.383.671.2
South Dakota9595.395.893.5100
Illinois94.194.989.882.298.2
West Virginia9494.686.48588.8
Vermont92.590.410088.284
Virginia92.59297.210073.9
Georgia92.193.410010082.8
Arkansas929289.291.668.9
Connecticut91.993.181.78568.7
Wisconsin91.894.279.381.459.3
South Carolina91.693.487.687.473.3
Oklahoma91.59290.489.180.2
Ohio91.588.810092.5100
Idaho91.390.585.487.251.4
Nebraska91.294.375.272.376.2
North Carolina90.290.294.292.482.6
Alabama89.988.796.910073.1
Michigan89.791.787.991.268.3
Louisiana89.48988.985.791.3
Kentucky89.289.9939292.7
Kansas88.689.489.694.169.4
Iowa88.490.384.688.263.8
Indiana88.286.7100100100
Oregon86.887.682.277.4100
Minnesota86.58786.18285.9
Tennessee86.485.791.794.183.6
Missouri85.886.988.786.877.8
Maine85.686.172.575.358
New Mexico8585.77877.673.3
Colorado84.984.783.281.774.9
Utah84.985.575.276.767.5
Arizona83.883.68483.772.5
New Hampshire83.683.772.975.271.9
Washington82.882.782.882.178.5
Source: Hotel Investment Strategies, LLC based on an analysis of U.S. Census Bureau Data (2012 Economic Census for Accommodation and Food Services NAICS Sector 72)
Please feel free to download the heat-map of efficiency scores for full and limited service restaurants across U.S. states: Efficiency Score Ranking for Full & Limited Service Restaurants Across U.S. States

Using a paired t test we found the difference in mean efficiencies for non-franchised and franchised full-service restaurants to be statistically significant (two-tailed P value 0.0372). The difference in mean efficiencies for franchisee-owned and franchisor-owned full-service restaurants were found to be extremely statistically significant (two-tailed P value 0.0001).

Summary statistics for the DEA technique are found in the following table. The mean efficiency score of 92.7 for all full-service restaurants suggests that the average full-service restaurant is 92.7% efficient compared with the most efficient full-service restaurants. The average efficiency score for the states with an inefficient full-service restaurant sector ranges from 90.7% in the case of non-franchise restaurants to 77% in the case of franchisor-owned restaurants.

Descriptive Data on Efficiency Scores for Full-Service Restaurants Across U.S. States

VariableAll RestaurantsNon-Franchise
Restaurants
Franchise
Restaurants
Franchisee-Owned RestaurantsFranchisor-Owned Restaurants
Average92.792.990.890.082.7
Standard Deviation5.65.68.48.313.8
Maximum100100100100100
Minimum82.882.772.572.351.4
Average Inefficient90.590.786.686.177.0
Source: Hotel Investment Strategies, LLC based on an analysis of U.S. Census Bureau Data (2012 Economic Census for Accommodation and Food Services NAICS Sector 72)

Characteristics of Full-Service Restaurants by State

StateNumber of RestaurantsNumber of seats as of December 31Value of sales, shipments, receipts, revenue, or business done ($1,000)Annual payroll ($1,000)Number of paid employees for period including March 12Population
Alabama28042341992467928818447602354813946
Alaska560437205293331680607989730825
Arizona388238409540852181465341961726544211
Arkansas19401419621392695457419359202949208
California28089232437628512017942393354825038019006
Colorado4691427086455594616348481022535186330
Connecticut33362484122871363931079530563597705
Delaware7417637984451526570917296916868
District of Columbia73497860136852147273823174635630
Florida14747144290917058969561650734222619341327
Georgia6720573496644355521107911444789911171
Hawaii12041287551968924595675328931392772
Idaho121981635790891267894203761594673
Illinois90617929528977494295457718547612878494
Indiana4419399612403666013558181034476535665
Iowa25211727951645029559487461043074386
Kansas20901658841622455551169450132885316
Kentucky25982419042512586840348621684383673
Louisiana27472441592913546972140649244602681
Maine1441990041006254359897216471328101
Maryland334437128443139671395097854025891680
Massachusetts6110562020659113921520181229836659627
Michigan6908570217591435919455061441459886610
Minnesota376836207637147551274462883915377695
Mississippi16361231391313236404068309642982963
Missouri455938002038709101336157984566023267
Montana105974814774358244044172851003522
Nebraska14151114241052007352086283151854862
Nevada17302186552865428981347485242752410
New Hampshire12581108591135100414507245521320923
New Jersey6906539958620376918294031084428882095
New Mexico13151101631163991416149291552083590
New York18899138772417939912575148829389319625409
North Carolina7213585119626605320504251475669755299
North Dakota5555116151034117818912955701380
Ohio72486927977430273251803618190911546969
Oklahoma24501971772125750694188543273815298
Oregon39602680222910284998632597933893920
Pennsylvania93157466998295469261685318942612768034
Rhode Island111487047984932318058198321052761
South Carolina372030458432508991053779750624719009
South Dakota7185154449181616712013119832576
Tennessee423140299142768861476646995476450632
Texas16128163218517939115583754439115126078327
Utah14801263081295698462097339612854222
Vermont7174339945025016090210439625606
Virginia6336545945604478219627251323448188656
Washington561243139748736581739750937046890899
West Virginia114684884934800304956232961855360
Wisconsin497935119233754751090733909325721075
Wyoming554381694074881380019327576608
Source: U.S. Census Bureau (Economic Census: Core Business Statistics Series, 2012: Franchise Status for Selected Industries and States: 2012) and Hotel Investment Strategies, LLC


¹ Full-service restaurants comprise establishments primarily engaged in providing food services to patrons who order and are served while seated (i.e., waiter/waitress service) and pay after eating. These establishments may provide this type of food service to patrons in combination with selling alcoholic beverages, providing carry out services, or presenting live nontheatrical entertainment.

² Limited-service industry comprise establishments primarily engaged in providing food services (except snack and nonalcoholic beverage bars) where patrons generally order or select items and pay before eating. Food and drink may be consumed on premises, taken out, or delivered to the customer’s location. Some establishments in this industry may provide these food services in combination with selling alcoholic beverages.

³ Productivity and efficiency are used interchangeably throughout the post. Efficiency refers to the ability to convert multiple inputs into outputs.

References

An Empirical Examination Of Productivity Of A Chain Restaurant Using Data Envelopment Analysis (DEA)

Multi-unit Restaurant-productivity Assessment: A Test of Data-envelopment Analysis

Measuring Efficiency Of Restaurants Using The Data Envelopment Analysis Methodology

Data Envelopment Analysis