Research Methods Multiple Regression
Executive Summary
This research provides statistical analysis for gross monthly sales in 60 stores using five key measures within a 10km vicinity: number of competitors, population in
‘000’s, average population income, average number of cars owned by households, and median age of dwellings. These quantitative variables are the key determinants, which will provide substance for descriptive statistics and the multiple linear regression model. This research reports mainly on statistical analysis, providing a direct interpretation of the research results.
This process quantitates subjective judgments, while offering a scientific method of selecting location when chain convenience store enterprises such as GStore expand their scale.
1
1.0 Introduction
The main purpose of this research is to identify the viability of opening a new GStore chain by analyzing conducting Five variables are used to assist in determining gross sales and predicting the characteristics of G-Store’s potential areas of establishment: a) Number of competitors within 10km
b) Population (in 1000’s) within 10km
c) Average income of the population within 10km
d) Average number of cars owned by households within 10km
e) Median age of dwellings within 10km
It is imperative to understand the relationship between gross monthly sales and the determinants above in different areas. This allows an identification of relationship between the variables thereby allowing the company to make better decisions in determining the most viable place to set up its stores. Data is interpreted for better understanding and recommendations are proposed at the end of this paper.
2
2.0 Literature Review
Corner stores or conveniences stores must consider the market viability as the primary element in operations. The proprietor must analyze many of factors to optimize his final decision. Location, the vicinity such as traffic, competition, accessibility, and
This research provides statistical analysis for gross monthly sales in 60 stores using five key measures within a 10km vicinity: number of competitors, population in
‘000’s, average population income, average number of cars owned by households, and median age of dwellings. These quantitative variables are the key determinants, which will provide substance for descriptive statistics and the multiple linear regression model. This research reports mainly on statistical analysis, providing a direct interpretation of the research results.
This process quantitates subjective judgments, while offering a scientific method of selecting location when chain convenience store enterprises such as GStore expand their scale.
1
1.0 Introduction
The main purpose of this research is to identify the viability of opening a new GStore chain by analyzing conducting Five variables are used to assist in determining gross sales and predicting the characteristics of G-Store’s potential areas of establishment: a) Number of competitors within 10km
b) Population (in 1000’s) within 10km
c) Average income of the population within 10km
d) Average number of cars owned by households within 10km
e) Median age of dwellings within 10km
It is imperative to understand the relationship between gross monthly sales and the determinants above in different areas. This allows an identification of relationship between the variables thereby allowing the company to make better decisions in determining the most viable place to set up its stores. Data is interpreted for better understanding and recommendations are proposed at the end of this paper.
2
2.0 Literature Review
Corner stores or conveniences stores must consider the market viability as the primary element in operations. The proprietor must analyze many of factors to optimize his final decision. Location, the vicinity such as traffic, competition, accessibility, and
References: Euromonitor, 2006. Retailing in Japan [online] Available at: [Accessed 29 May 2013]. Haddock-Fraser, J. Poole, N. and Doishita, M., 2009. The failure of multinational food retailers in Japan: a matter of convenience?. British Food Journal. [e-journal] 111(4). Available through: Emerald. [Accessed 20 May 2013]. 16