A Study on Supermarket Profit

Abstract

In Economics, a very simple theory is, more sales tend to more profits. The aim of the study is to find out whether the supermarket profit depends on Food Sale, Nonfood Sales and Store Size. This paper is an economical based study about the profit of supermarket depends on three factors, food & nonfood items sales, and store size of the supermarket.

Introduction

A supermarket is a large form of the traditional grocery store. It is a self-service shop offering a wide variety of food and household products, organized into aisles. It is larger in size and has a wider selection than a traditional grocery store, but is smaller and more limited in the range of merchandise than a hypermarket or big-box market.

According to Investopedia, the United States is so large and diversified that even its “national” grocery chains don’t all operate in every state. Take Kroger for example. The grocery company is one of the largest in the world and it only has stores in 34 states. In 2014, U.S. supermarkets had combined sales of over $638 billion.

Background

The supermarket industry is highly fragmented with the top ten retailers accounting for only 35% of the total number of stores and 68% of sales (1). According to the Progressive Grocer, approximately 35,600 supermarkets were in operation in 2009. Chain supermarkets (29,300 stores) generated $528 billion in sales in 2009 or about 95% of total supermarket sales, while independent supermarkets (6,300 stores), accounted for the balance.

Chain supermarkets are generally considered to have more than ten stores under one management structure while independent supermarkets usually have ten or fewer stores under one management structure. The supermarket industry in the U.S. is mature, highly competitive and rapidly consolidating. It is not uncommon to find competing supermarkets within a mile or two from each other. The industry faces pressure from supercenters, warehouse clubs and other retailers such as natural or gourmet food stores and drugstores. To better compete in such an environment, supermarkets are increasingly tailoring their product offerings to meet consumer interests. For example, according to the Food Marketing Institute, a vast majority of stores now offer prepared foods for take-out and have floral departments in response to customer needs. Supermarkets are also increasingly offering ethnic foods and organic and natural foods.

In the past, food retailing was very personalized, with shop owners living within the neighborhood where they operated. As people started moving to suburbs from cities during a large part of the last century, retailers followed them. This led to growth in the number of shopping centers and to the beginnings of supermarket chains. Sales practices also became complicated as operators were far removed from their customers and had to pay for research to understand their customers’ needs.

Today, supermarket operations include purchasing products from a number of suppliers, having products delivered to the store, maintaining the products’ freshness, marketing the products, and completing sales through checkout stations.

Data and Methods

This study is about the profit of supermarket. The sample size of the survey is very small. Information is collected about only ten (10) supermarkets involve fours variables.

Variables

The study involves four variables. They are: Food Sales (tens of thousands of dollars) X₁, Nonfood Sales (tens of thousands of dollars) X₂, Store Size (thousands of square feet) X₃, and, Profit (thousands of dollars) Y, where, first three (3) variables are considered as independent variables and the last one is considered as dependent variable.

Methods

Multiple regression analysis is used to measure the effect of food sales, nonfood sales and store size on profit. There are two model is constructed and they are compared with each other to determine which one is better. In the first model all three independent variables has taken in the model and in the second model only two independent variables has taken in the model (excluding food sales).

Data

The table which shows the required data about supermarket profit is shown as follows:

Table-1: Supermarket Profit along with Food Sales, Nonfood Sales and Store Size

Objective

1. In this paper, it has been attempted to focus how much the supermarket profit depends on those three independent variables.
2. To identify the effect of independent variables on the supermarket profit.
3. To compare the sales of food and nonfood items.
4. To compare the regression models in terms of presence or, absence of food sales of the supermarket.

Limitation

Since data about only ten (10) supermarkets, so the generalization of the result may be unsatisfactory for entire population of interest.

Results

The information represented in this research paper is obtained from a very small sample.

Sample Characteristics

The Figure-1 shows, the supermarket profit with corresponding food sales and nonfood sales as follows:

Figure-1: The supermarket profit with corresponding food sales and nonfood sales

From the above Figure-1, it is clear that maximum increment in food sales increases the supermarket profit.

1. 20% of the supermarket food sales is 101-150 (thousands of dollars),
2. 30% of the supermarket food sales is 101-150 (thousands of dollars),
3. 10% of the supermarket food sales is 201-250 (thousands of dollars),
4. 20% of the supermarket food sales is 251-300 (thousands of dollars),
5. 10% of the supermarket food sales is 301-350 (thousands of dollars), and
6. 10% of the supermarket food sales is 401-150 (thousands of dollars).
7. 20% of the supermarket nonfood sales is 31-40 (thousands of dollars),
8. 10% of the supermarket nonfood sales is 41-50 (thousands of dollars),
9. 10% of the supermarket nonfood sales is 51-60 (thousands of dollars),
10. 20% of the supermarket nonfood sales is 71-80 (thousands of dollars),
11. 10% of the supermarket nonfood sales is 81-90 (thousands of dollars), and
12. 30% of the supermarket nonfood sales is 91-100 (thousands of dollars). 

The Figure-2 shows, the supermarket profit with corresponding store size as follows:

Figure-2: The supermarket profit with corresponding store sizes

From the above Figure-2, it is quite clear that there is a positive relationship between profit and store size.

1. 20% of the store size of supermarket is 11-20 (thousands of square feet),
2. 30% of the store size of supermarket is 21-30 (thousands of square feet),
3. 30% of the store size of supermarket is 31-40 (thousands of square feet),
4. 10% of the store size of supermarket is 41-50 (thousands of square feet), and
5. 10% of the store size of supermarket is 51-60 (thousands of square feet). 
6.  10% of the supermarket profit is 1-10 (thousands of dollars),
7. 40% of the supermarket profit is 11-20 (thousands of dollars),
8. 30% of the supermarket profit is 21-30 (thousands of dollars), and
9. 20% of the supermarket profit is 31-40 (thousands of dollars).

Descriptive Statistics

Table-2 represents the descriptive statistics of the variables. In the table, maximum value, minimum value, mean, standard deviation and total number of observations of the variables are shown.

Table-2: Descriptive Statistics of the Variables

Table-3 represents the regression model-1 of the Profit (Y) on Food Sales (X₁), Nonfood Sales (X₂) and Store Size (X₃) as follows:

Table-3: Regression model-1 of the Profit (Y) on Food Sales (X₁), Nonfood Sales (X₂) and Store Size (X₃)

If all other variables remain constant then one unit increment in food sales, profit will increase 0.027 units on an average. Similarly, if all other variables remain constant then one unit increment in nonfood sales, profit will increase 0.097 units on an average and if all other variables remain constant then one unit increment in store size, profit will increase 0.525 units on an average. 

Table-4 represents the significance of the regression model of the Profit (Y) on Food Sales (X₁), Nonfood Sales (X₂) and Store Size (X₃) as follows:

Table-4: The significance of the regression model of the Profit (Y) on Food Sales (X₁), Nonfood Sales (X₂) and Store Size (X₃)

Hypothesis

H₀: β₁₀ = β₁ = β₂ = β₃ = 0

vs., H_a: β₁₀ ≠ β₁ ≠ β₂ ≠ β₃ ≠ 0

From the ANOVA Table, it is clear that the regression model-1 is significant.

Discussion

This paper is an economical project. In this analysis, the aim was to find out among three independent variables (Food Sales, Nonfood Sales and Store Size) which independent variable is the most influential for the supermarket profit. Here the findings are saying that the maximum increment in food sales increases the supermarket profit and there is a positive relationship between profit and store size.