Pricing Analytics and Revenue Management

This document provides an overview of pricing analytics and revenue management. It covers topics such as linear regression model, price elasticity, coefficient of independent variables, log function in excel, and R-square model. It also explains the concept of linear price response function and WTP calculation. The document includes references from books and journals.

Pricing Analytics and
Revenue Management

TASK 1
Linear regression model: Linear regression models are used to demonstrate the relation
among two quantities or parameters or to forecast that. The factors that are used to determine the
dependent variable's value are named the independence factors. According to this model volume
take as dependent variable and other variables are taken as independent.
Price elasticity: The market elasticity’s is an economic indicator of how a consumer's
market affects production and output adjust, and vice versa. And demand stiffness is a shift in
proportion of the increase in volume to the increase in percent of volume. There are using this
formula such as:
= Percentage change in quantity demanded/percentage change in price
Coefficient of impendent variables: The coefficient informs that in correlation with
various independent factors, how much the conditional factor is supposed to increase when the
independent predictor rises by one, keeping all the independent factors unchanged. Please note
the quantities in which the parameters are calculated in. There are taking sales as independent
and price is dependent variable. There understand the relation in both variables in negative
manner.
sales price
Column
1 1
Column
2 -0.0892 1
Log function in excel: The role of the Microsoft Excel LOG restores the logarithm of a
number to a given base. The LOG feature in Excel is a constructed-in feature which is classified
as a Math / Trig feature. In Advance it could be used as a working sheet (WS) feature.
R-Square model: R-squared (R2), which is also the percentage of result variance
described by the parameters of the predictors. In regression analysis designs, R2 equates to the
rectangular similarity between both the designer's measured result principles and the values
predicted. The stronger the R-squared, the stronger the sequence.
TASK 2
Linear price response function: A linear price-response function is a standardized
spread of w.t.p., and vice versa. A standardized allocation of the will to charge. Market-response
processes of continuous conductivity have juncture buoyancy equal at all rates. The appropriate
cost and volume velocities for a monopolistic confronting a linear supply purpose are similar to
the balance velocities in a competitive environment with all the drilling costs doubled to the
average annual cost and strangle cost.

Initially, monopol would demand a price lower than that of the competitive optimum rate
and thus harvest the commodity quite gradually than would have been the situation in
competitiveness. Prices for the privilege would grow less swiftly. If the time night sky is long
that much, the mining will simply continue upon reaching the cost of the stomp. The monopol
confronting a sequential market feature will hit this price of choke purely earlier than would be
the competitive industry39 and the commodity will be extracted for a longer time.
WTP calculation: When deciding the right WTP for your location clients, take such
relevant factors.
 The economical situation.
 How fashionable a commodity is / in summer.
 Private price ranges for buyers.
 Factual requires at various buyers.
 A Item's Rarity.
 A retailer's Price.

REFERENCES
Books and Journal
Rice, S.C., Weber, D.P. and Wu, B., 2015. Does SOX 404 have teeth? Consequences of the failure to
report existing internal control weaknesses. The Accounting Review, 90(3), pp.1169-1200.
Shay, S.E., Fleming Jr, J.C. and Peroni, R.J., 2015. Designing a 21st Century Corporate Tax-An Advance
US Minimum Tax on Foreign Income and Other Measures to Protect the Base. Fla. Tax Rev., 17, p.669.