Reflection Paper Instructions You are an operations manager for a new regional air cargo company

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Reflection Paper Instructions You are an operations manager for a new regional air cargo company. To support the business plan development, you will conduct preliminary analyses of aircraft pricing, route planning, and cargo loading. These analyses will aid in identifying the type of aircraft the company should purchase, the most efficient route to service initial launch locations, and determine the priority of aircraft cargo loading based on item value. The results of your analyses will be presented to the company board of directors in an executive summary format. See instructions for how to write an executive summary. The Executive Summary should contain the following paragraphs: ? Introduction ? Aircraft purchase pricing discussion and recommendation ? Aircraft route discussion and recommendation ? Cargo loading discussion and recommendation ? Your thoughts on the proposed plan to include pros and cons. Your educated thoughts can expand on the analyses of the previous paragraphs but should be related to these subjects. ? Conclusion The following sections contain amplifying information. Part 1 – Aircraft Purchase Pricing The aircraft sales data table (and Excel file) give the selling price ($ millions), age (years), cargo capacity (m3 ), maximum payload capacity (tonnes), range (km), and aircraft type that have sold in the past year. Develop three regression models to predict aircraft sales price using the following variables: 1. Age, cargo capacity, maximum payload, and range 2. Age, cargo capacity, maximum payload, and type 3. Age, cargo capacity, maximum payload, range, and type Answer the following questions: ? Which of the three models is the best and why? ? Use each of the three models to predict the aircraft sales price for the following variable values. ? Which type of aircraft do you recommend the company purchase? In the appendices of your executive summary, include the following: ? Table for predicted aircraft sales ? Screenshots of the Excel Regression Summary Output for each model. The screenshots should be legible, with each on its own page. Suggestion: use landscape orientation Table X. Aircraft Purchase Characteristics Variable Desired Value Age (years) 15 Cargo Capacity (m3 ) 135 Max Payload (tonnes) 13.0 Range (km) 5500 Type 737, 757, A300, A320 Table X. Predicted Aircraft Sales Price ($ million) Type Model 1 Model 2 Model 3 737 xx.xxx xx.xxx xx.xxx 757 xx.xxx xx.xxx xx.xxx A300 xx.xxx xx.xxx xx.xxx A320 xx.xxx xx.xxx xx.xxx Table 1. Aircraft Pricing Data Price ($ millions) Age (years) Cargo Capacity (m^3) Max Payload (Tonnes) Range (km) Aircraft Type 32 20 179 13 5542 737 54 20 232 20 6229 A300 50 17 142 15 5644 A320 31 12 164 16 5369 737 46 14 126 19 6163 A320 56 12 222 17 6620 757 48 12 248 22 6317 757 29 18 143 12 5426 737 34 14 169 18 5823 737 52 14 267 18 5927 757 50 16 237 23 6795 757 59 10 231 20 5634 A300 54 19 233 20 6085 A300 42 15 132 16 5421 A320 28 15 156 17 5466 737 57 13 242 22 6574 A300 51 20 147 17 5761 A320 53 18 241 20 6751 757 52 13 268 23 6437 A300 46 16 136 16 6356 A320 29 15 179 17 5543 737 27 19 150 18 5147 737 54 13 227 18 6442 757 30 12 171 16 5737 737 44 17 150 17 6012 A320 33 14 179 12 5048 737 56 13 234 25 5787 A300 32 19 185 15 5539 737 58 11 251 20 6139 757 52 16 278 20 6093 A300 54 14 281 25 5925 A300 45 10 143 18 6395 A320 46 18 123 19 5834 A320 57 19 239 21 5967 A300 27 15 171 12 5130 737 59 19 235 24 5933 A300 50 13 233 20 6483 757 52 19 272 25 6227 A300 54 19 265 17 6626 757 46 19 141 18 6005 A320 56 16 257 22 6311 757 52 17 244 19 6339 757 25 11 167 15 5132 737 42 18 144 18 5814 A320 42 16 149 19 6133 A320 59 20 274 24 5889 A300 53 20 235 18 6784 757 55 17 229 23 6454 757 43 14 139 15 5969 A320 50 18 216 21 6388 757 53 16 234 22 6050 A300 58 15 238 20 6119 A300 25 14 157 16 5933 737 46 11 134 14 6133 A320 27 12 150 16 5173 737 61 19 277 25 6387 A300 47 18 134 15 5650 A320 49 15 123 19 6367 A320 52 13 248 23 6377 757 33 14 147 16 5815 737 Part 2 – Route Planning The company is in the process of determining the optimal route structure to support the initial launch locations. Figure 1. depicts all combinations of the potential supporting routes. Table 3. provides the distances between city pairs. Questions: ? Given the aircraft route data, what is the optimal (i.e., shortest) routing to serve the six initial launch locations if the starting location is EYW? ? What is the total distance for the optimal routing? Hint: do not forget to include the distance from the last city back to the starting point of EYW! In the appendices of your executive summary, include the following: ? Create a simple (line diagram) figure depicting the optimal routing ? Screen shot of the Excel model for the network analysis Table 2. Distance (nm) Between City Pairs Distance (nm) Between City Pairs EYW JAX MCO MIA TLH TPA EYW - 354 233 109 376 207 JAX - 125 291 138 157 MCO - 167 198 70 MIA - 350 177 TLH - 174 TPA - Figure 1. Aircraft Route Data Part 3 – Aircraft Loading The cargo loading data table (Table 3) provides information about the value of items ($ 1,000) and the item’s associated cubic volume (m3 ). You are to develop a cargo loading model that prioritizes loading items based on value while accounting for cargo volume. In this analysis, the available cargo capacity is 150 m3 . Questions: ? Use the example table as a guide for the cargo loading plan. Note, the first two columns, value and Vol are provided in the cargo loading table. In the appendices of your executive summary, include the following: ? Table for cargo loading plan and value ? Screen shot of the Excel model Table X. Cargo Loading Plan and Value Item Value ($ 1,000) Vol (m3 ) % Vol Loaded Vol (m3 ) Loaded Value ($ 1,000) Example 5 10 0.55 5.5 2.75 Example 2 10 20 1.00 20.0 10.00 Total - - - 25.5 12.75 Table 3. Cargo Loading Data Item Value (in $1,000) Cargo Cubic Vol m^3 Express mail 3 40 Documents 5 10 Medicines 1 16 Amazon packages 1 44 Food 4 21 Electronics 2 22 Legos 2 19 Clothes 5 29 Toys 1 21 Cheetos 3 44