Data Fusion and Separation Meeting A. KrekCarnuntum, Austria, June 2001

Economic Aspects of Data Fusion and Separation

Alenka KrekResearch Assistant

Institute for GeoinformationTechnical University Viennakrek@geoinfo.tuwien.ac.at

Data Fusion and Separation Meeting A. KrekCarnuntum, Austria, June 2001

An Example: Movie Tickets

95

110

95

85

85

Product and Price Differentiation

Price of a movie ticket depends on the row one sits in.

One pays for the valuehe attaches to the product.

Data Fusion and Separation Meeting A. KrekCarnuntum, Austria, June 2001

Motivation

How should Geoinformation products be designed in order to bring the most value to the user?

How to price the products?

Potential buyers differ in their• information needs• willingness to pay (income/revenue level)

Data Fusion and Separation Meeting A. KrekCarnuntum, Austria, June 2001

Outline

The Model of Dataset Qualities

An Example: Street Network Dataset

Data Fusion and Separation

The Ideal Product

“Damaged products”

Economic Aspects of Data Fusion and Separation

Quality-Price Options

Self-selecting Principle

Conclusions

Data Fusion and Separation Meeting A. KrekCarnuntum, Austria, June 2001

An Example: Street Network Dataset

Street network dataset – different categories

One-way streets attributes

Turn restrictions attributes

Data Fusion and Separation Meeting A. KrekCarnuntum, Austria, June 2001

The Model of Dataset Qualities

Dataset quality is defined as a quantifiable property of a dataset which can be linked to the improvement of the decision-making process of the buyer.

A dataset is a composition of qualities.

Example: One-way streets, turn restrictions attributes etc. are dataset qualities for a particular decision-making process

Data Fusion and Separation Meeting A. KrekCarnuntum, Austria, June 2001

Simulations

N9

Position: N1Orientation: N1-N4, N1-N2, N1-N3Destination: N5Objective: the shortest path to the

destination

N1

N2

N3

N4

N5

N6

N7

N8

the ideal case

the distance = 14.7

the distance = 11.4 allToBoth

Some results

Data Fusion and Separation Meeting A. KrekCarnuntum, Austria, June 2001

The Value of a Quality

The buyer does not place the same valuation on all qualities of a dataset.

The valuation of a quality depends on the use of a dataset in a decision-making process.

Data Fusion and Separation Meeting A. KrekCarnuntum, Austria, June 2001

Data Fusion and Separation

Different dataset quality composition is needed for different use.

Several versions of the Geoinformation product can be developed with multiple, different mixes of different qualities.

Different varieties are produced to cater to different types of consumers.

Data Fusion and Separation Meeting A. KrekCarnuntum, Austria, June 2001

The Ideal Product

GI product (GIP) is represented as a point in a multidimensional quality product space.

GIP3 quality space

GIP 3

maximumversion

GIP 1

GIP 2

minimum version

d2

d3

GIP2 quality space

Data Fusion and Separation Meeting A. KrekCarnuntum, Austria, June 2001

“Damaged Goods”

Manufacturers may intentionally damage a portion of their goods in order to price differentiate.

Deneckere and McAfee in their paper (published in the

Journal of Economics&Management Strategy) list many instances of this phenomenon.

Cost advantages.

Data Fusion and Separation Meeting A. KrekCarnuntum, Austria, June 2001

Quality-Price Options

The seller offers a schedule of quality-price options of the same generic type of the product.

The same price is charged to all buyers of a given quality composition.

All buyers are offered the same quality-price schedule on the basis of self-selection principle.

Data Fusion and Separation Meeting A. KrekCarnuntum, Austria, June 2001

Self-selecting Products

Quality-price options give the buyers an incentive to self select the product they are willing to pay and which satisfies their information needs.

The strategy for the seller who can not distinguish among buyers prior to an actual sale.

Data Fusion and Separation Meeting A. KrekCarnuntum, Austria, June 2001

The Economic Aspects

New markets are served – The seller can sell to buyers who do not value the maximum product so much, without decreasing demand for the “ideal” product so much.

Additional revenue for the seller.

Better matching the user’s needs and his/her willingness to pay.

Data Fusion and Separation Meeting A. KrekCarnuntum, Austria, June 2001

Revenue Gained by Selling One Price-Quality Option

Willingness to pay(WTP)

Quantity (q) Q1 Q2 Q3

P1

P2 P3 Di

Data Fusion and Separation Meeting A. KrekCarnuntum, Austria, June 2001

Revenue gained by Selling Several Price-Quality Options

Willingness to pay(WTP)

Quantity (q) Q1 Q2 Q3

P1

P2 P3 Di

Data Fusion and Separation Meeting A. KrekCarnuntum, Austria, June 2001

Conclusions

Data fusion and separation is important from the economic point of view.

Quality differentiated product on the basis of self selecting principle of quality-price options:

The buyer’s perspective

he satisfies his information needs

pays the amount he is willing to pay

The seller’s/producer’s perspective

new markets are served

higher revenue

Data Fusion and Separation Meeting A. KrekCarnuntum, Austria, June 2001

Thank you for your attention!

Questions and Comments are welcome!!

Data Fusion and Separation Meeting A. KrekCarnuntum, Austria, June 2001

Product and Price Differentiation

Product differentiationproducts are similar and different at the same time, they are not complete substitutes

products designed in such a way that they bring the most value for the user/buyer

Price differentiation different price is charged to different users for the same product; -first, -second and -third price discrimination (Pigou 1929) non-linear pricing (Wilson 1995); price is not linear to the quantity purchased