Introduction
The optimum size of company is a very fundamental issue o put into consideration for the growth of the company. Size can have drawbacks and benefits in assisting the management in maximizing the level of output. However, there are those factors that determine the size of the firm. In most cases farm expands their production due to the economies of scale. When the company grows or expands, it is able to take advantage of machine utilization, cost reduction, and bulk discount among others.
Large companies have the cost advantage over the small companies due to economies of scale. This enables the farm to optimize it production hence large volume of output. Although, size of a company could not have a direct relationship with the amount of sales, it could in a way help to reduce the price of the quantity supplied due reduced cost of production. This would make the products of the company more favorable to consumers hence increase in sales.
We assume that the consumers will only be affected on the price of the product when making buying decision. Other factor such as taste and preference, and promotional strategies among others, does not affect the buying decision of the consumers. Thus, the sales volume of the firm will be determined by the total revenue.
In this study, my aim is to research on the relationship between the size of the company and sales. This will be done by conducting a regression analysis on the variables that represents sales and the size of the company.
Previous study
Previous studies had been conducted to determine the relationship between the volume of sales and the size of the firm. A study conducted by Hoerl, & Snee, illustrated that there are a strong positive correlations between the size of the firm and sales. In their study conducted by a sample of 15 large companies and 15 small companies, the result indicated that the correlation between sales and size of the firm was 0.6 (Hoerl & Snee, 2012). Another study conducted by the Michigan State university students indicated that the correlation between these two parameters was 0.75. On their research they indicated that the smaller firms had small production capacity hence low volume of output. Therefore, they observed that the larger the firm the higher the level of sales.
McLeod (2010), conducted a research on the relation between the level of firm’s output and sales and indicated that there exist a positive strong correlation between sales and output. He argued that the larger the company, the larger the output hence more sales. The students from the Michigan State University also observed that the size of the company and the volume of sales are strongly correlated. With a random sample of 12 small, medium and large firms they were able to obtain a correlation coefficient figure of 0.92. That indicated a strong correlation between the two variables.
Description of variables
In this study two variables are used to determine the relationship between the size of the firm and sales. Sales, in our case are considered to be the value of the total revenue of the firm. Total revenue is determined by multiplying the output supplied in the market and the price of the commodities in the market place. On the other hand the size of the firm is determined by its production. In this case the size of the firm is measure by the level of output.
In order to collect the significant data in the analysis a sample of 10 companies is taken randomly from the economy. Their level of production (output) and their total revenue is determined. These values are recorded in the table below.
Values of the output produced and the total revenue for the ten different companies that belongs to the same industry.
Regression analysis
According to the scatter diagram illustrated below, the relationship of size of the firm (level of output) and sales, (total revenue) seems to derive a linear equation. This implies that as the level of output increases, the level of total revenue also increases. Therefore, a linear equation can be written as sales = a + bQ. Where are the other factors that increase sales, where “b” is the slope of the linear equation and Q is the total revenue. The slope indicates by how much sales increases or decreases due to increase or decrease of the total revenue. The linearity of the equation is therefore significant in analyzing the correlation coefficient of the two variables. The correlation coefficient will thus enable us to determine how the sales are and the size of the firm related.
In this analysis, the sales took the position of the dependent variable while total revenue is the independent variable. In other words, sales are dependent of the amount of output produced. This is true because total revenue is a function of output.
The chart above indicated the relationship between the level of output produced and the total revenue
R = nxy- xynx2- (x)2{ny2- (y)2
R= 10*13,597,018,640- 148,031* 691,43210*2,960,362,853- 148,0312{10*63,981,147,760- 691,4322
R= 33,616,816,0107,690,451,569*161733267000
R= 33,616,816,01035,267,575,150
R= 0.95
The correlation coefficient between the output produced and the total revenues is greater than 0.5. Therefore, the correlation coefficient is positively strongly. The relationship between the output produced and the total revenue is strong. Positive sign of the correlation coefficient indicates that the output and total revenue moves in the same direction. In other words, as the output produced increases, the level of the total revenue also increases and vice versa.
Conclusion
Since the relationship between the level of output produced and the total revenue has a linear equation and a high positive correlation, the analysis seems to provide a reasonable and a predictive relationship. As indicated in the regression analyst, the correlation coefficient indicates that the two variables are strongly correlated. Therefore, assuming that the size of te company is determined by the revel of output produced, there is a strong relationship between the firm’s size and the total revenue. Similarly, we assume that the sales of the firms are determined the total revenue earned by the firm. This derives an indirect relationship between the size of the firm and the sales.
Therefore, we can conclude that as the firm expands its operations and performance, its total output increases. Similarly, with the economies of scale, the firm is able to reduce its production cost, hence lowers the price of their commodities, (Albach, Bergendahl, & EIASM, 1977). That is, the large firm enjoys economies of scale hence charges relatively lower prices of the product that the small firms. To the cheaper goods and services offered in the market by the large firms, the consumers are attracted to buy such goods. Thus, the sales of the firm increases as the consumer buy more products. This implies that the sales of the firm is greatly but indirectly affected by the size of the firm. As the size of the firm increases, the volume of the sales also increases and vice versa.
It would be recommended that for a person to establish a firm, he must aim at maximizing the size of the company. This will help them to enjoy economies of scales and more sales of their products as indicate in the above finding. Once the company is able to achieve maximum sales, the profit maximization goal of the firm becomes easier to achieve.
References
Albach, H., Bergendahl, G., & European Institute for Advanced Studies in Management (1977). Production theory and its applications: Proceedings of a workshop. Berlin: Springer-Verlag.
Hoerl, R. W., & Snee, R. D. (2012). Statistical Thinking: Improving Business Performance. Hoboken: John Wiley & Sons.
McLeod, D. (2010). The zero-turnover sales force: How to maximize revenue by keeping your sales team intact. New York: AMACOM/American Management Association.
