Managerial and Economics and Globalization

¶ … Pizza Shop Demand Forecasting Pizza Company Entry: Consumer Demand Forecast There are a number of issues a company needs to think about before entering any particular market. In an industry such as the food service industry, there are even more factors to consider. Entering into any market can be a gamble, yet food service is often even more vulnerable in regards to the already strong presence of successful competitors and the income levels of the consumer markets being served.

Within this particular analysis, the data presented in the course shell will be used as a way to determine if the Pizza Company should enter this particular market, and if so, which conditions will be most desirable in order to facilitate the most successful entry into the market. Regression Analysis One of the best forecasting tools companies can use is regression forecasting in order to determine the potential for consumer demand to work in the company's favor.

Such statistical testing can help calculate elements and market factors in a computable way, where certain factors can be adjusted based on changing market conditions as a way to calculate potential changes in consumer demand. The data set was provided within the course shell. This data set was then put into excel in order to run regression statistical testing to better explore the coefficient determinate and thus understand hw various factors of price, competitor price, advertisement budgets, and the average income levels of the consumers who dominate that market environment.

Manipulating these factors to then mimic market conditions as they stand can help provide information for forecasting the future consumer demand, if market conditions do not change dramatically. SUMMARY OUTPUT Regression Statistics Multiple R 0.912678 R Square 0.832981 Adjusted R.

Square 0.806258 Standard Error 14875.95 Observations 30 ANOVA df SS MS F Significance F Regression 4 2.76E+01 31.1708 0 6.90E+09 1 2.20E-09 5.53E+00 2.21E+00 Residual 25 9 8 3.31E+01 Total 29 0 Coefficient ts Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% 69974.8 1.84112 0.0775 272948 272948 Intercept 128832.2 2 3 1 -15283.6 1 15283.6 1 5.54E Price (P) -19876 6 4.84678 5 -28321.8 11430.1 28321.8 11430.1 Competitor 4.47143 0.00014 22592.4 22592.4 Price (PX) 15467.94 2 7 6 6 6 Advertisement 2.77193 0.01036 0.4544 0.067 0.4544 0.260701 0.09405 5 9 0.067001 2 1 2 1.01726 8.63136 5.72E- 10.8755 6.6853 10.8755 Income 8.70403 8 1 9 6.685302 1 2 1 From such testing, an understanding of statistics involved in setting consumer demand can be better understood.

Based on the regression testing, the estimated regression line equation is as follows: Q= 128832.2-19876*Price + 15467.94*Competitor Price + 0.260701*Advertisement + 8.780403*Income With this equation, various entries can be used to thus forecast future consumer environments. The coefficient of determinate is essentially the R. Squared value as computed in Excel by the regression analysis. Within the cope of this analysis, the coefficient determinate represents the largest factor in determining the variation for the consumer demand for the product, pizza.

Within this particular analysis the coefficient determinate is as follows: R=0.832981 As such, this impacts the level that these factors, price, competitor price, advertising funding, and consumer income levels, affects the consumer demand at a specific rate. Within the scope of this analysis, 83.2981% of the demand variation is thus directly related to the price, competitor price, advertisement and income combined by the methods of the equation presented above that represents the true line of regression.

Therefore, it is clear that within the next four periods, there would need to be optimum conditions for the Pizza Company to succeed in the given market place. For demand to remain in their favor, they would have to have a lower price than their competitors, spend more in advertising to keep the brand relevant within the consumer mind frame, and try to work in areas where consumer income was relatively higher than the average.

Discussion It would be best for this particular pizza company to enter into this community marketplace in three most desirable situations, first being a high competitor price already present in the market. It would be wise to enter into the marketplace if the cost of the competitor's product was rated at a high value. If this was the case, the pizza company could come into the market with a lower price point and take over a greater portion of the consumer demand for pizza in that area.

Therefore, there is a high level of price elasticity attached to the competitor pricing model within this particular consumer marketplace. As such, within the competitor pricing model "a slight increase will have a major affect on the demand for the product," especially when a brand new company enters into the marketplace at a lower price for the same quality product (Symes, 2013, p 1). With a greater competitor price, the Pizza Company will benefit dramatically over the span of the next four years.

As long as the competitor price remains at a certain price, it will not detrimentally affect the evolving consumer demand. Essentially, "the availability and perceived of competing products or services will help determine how price increases affect demand" (Symes, 2013, p 1). Thus, the Pizza Company needs to keep an eye out for the price of their competitor's product. Secondly, the results would also be favorable for the pizza company to enter into the market with a large funding potential set aside for advertising.

This increase in advertising spending would help bump up the demand for the company's product in its favor. Statistics have long been used as a way to "measure the effectiveness of advertising by analysis of shifting demand curves," (Green, Carman, & McManus, 1991, p 63). How much advertising a company funds means that its name is out there more within the public eye. This increased market presence often keeps the brand present within the consumer mind frame, and can thus impact overall consumer demand.

Here, the research suggests that "a growing collection of research results indicates that promotion can increase commodity demand," (Green, Carman, & McManus, 1991, p 63). If enough funding is pumped into advertising the pizza product in a way that differentiates it from other competitors in the market and appeals to consumers, "consumers will choose the advertised product when they make their next purchase" (Linton, 2012, p 1).

As such, if advertising budgets are adjusted to out do the competitor, the new name of the product will be the one left on the minds of the consumers. In the last scenario, the pizza company would enter the market in the most favorable conditions if the community it would be serving.