Develop an adjusted exponential smoothing forecast model ( = .40 and = .40) for the data in Problem 42 to forecast seat occupancy,

Develop an adjusted exponential smoothing forecast model (α = .40 and β = .40) for the data in Problem 42 to forecast seat occupancy, and compare its accuracy with the seasonally adjusted model developed in (a).

Data From Problem 42:

Arrow Air is a regional East Coast airline that has collected data for the percentage available seats occupied on its flights for four quarters—(1) January–March, (2) April–June, (3) July– September, and (4) October–December—for the past 5 years. Arrow Air also has collected data for the average percentage fare discount for each of these quarters, as follows:

                                    

a. Develop a seasonally adjusted forecast model for seat occupancy. Forecast seat occupancy for year 6 by using a linear trend line forecast estimate for seat occupancy in year 6.
b. Develop linear regression models relating seat occupancy to discount fares in order to forecast seat occupancy for each quarter in year 6. Assume a fare discount of 20% for quarter 1, 36% for quarter 2, 25% for quarter 3, and 30% for quarter 4.
c. Compare the forecasts developed in (a) and (b) and indicate which one appears to be the best.