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Could you please solve the questions I attached?

I may need people who have knowledge for regression and conjoint analysis on these question.

I also need your explanation that how you get the answer.

Based on an initial conjoint survey (identical to the one you filled out printers), management determined there were 3 segments of printer customers: Price sensitive, Speed sensitive (PPM), and Color sensitive (want a color printer). Based on this, management wanted a market demand curve for different printer configurations. A survey determined that Segment A represented 40% of the market, Segment B represented 35% of the market and Segment C represented 25% of the market.

To determine market demand, 3 regressions were run, one for each segment.

Respondents who were clustered in the same segment were placed in the same regression. For each segment, the regression is:

Ranking = β0 + β1*Price + β2*PPM6+ β3*PPM12 + β4*Color + β5*Epson + β6*Cannon

In the original survey, the prices offered were 299, 399, and 499. In the regression, the Price variable is coded as 0, 100, 200 (i.e., 299 is subtracted). The other variables are coded as 0/1 dummy variables. Thus the “base” model has $299, 3 PPM, Black and White, and HP brand. Because the dummy variables and price are zero for the “base” model, the intercept picks up the average rating of the “base” model.

The output for the regression is the table below:

Segment A |
Segment B |
Segment C |
||

β0 | Intercept |
65.60 | 45.63 | 66.25 |

β1 | Price |
(0.22) | (0.14) | (0.13) |

β2 | PPM: 6 |
11.31 | 13.31 | 17.83 |

β3 | PPM: 12 |
17.11 | 21.83 | 28.42 |

β4 | Color |
6.56 | 36.40 | 14.30 |

β5 | Epson |
(13.41) | (3.52) | 4.84 |

β6 | Cannon |
5.58 | (4.33) | (13.20) |

To help you interpret the Price coefficient, note that in Segment A a price increase of $100 results in an expected decrease of 22 rating points. Further note that a coefficient of 11.31 for PPM: 6 means that the expected rating increases by 11.31 points when a printer has this feature.

### Questions:

- For each segment and each feature, convert the regression coefficients (Intercept, PPM, Color, Brand Name) into a dollar
- Assume that HP is selling its “base” model (3PPM, Black and White) for $279.

Construct the demand curve for Epson’s same “base” model. If Epson matches HP’s price, what is Epson’s expected revenue?

- Assume a price of $279 on the HP base model and assume that Epson matches this price on its identical model. Construct the demand curve for the HP, Color, 6 PPM Assume that the incremental cost of adding color and increasing PPM to the HP base model is $200. Which segments will you target for the HP color printer? Your answer should be both quantitative and qualitative (i.e., think, just don’t crunch numbers).
- Conjoint allows us to assess WTP of a segment and develop a demand

However, within a segment there will be variation in WTP – and we have thus far ignored this aspect of the problem. In words, how will you factor this into your pricing decision?