Quantitative Model For an Impact Measurement System

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Quantitative model for impact measurement system

National Technical University of Athens

Identification of impact factors & their relationship

Effect of a factor on impact: Direct (vertical) effect Indirect (horizontal) effect Self-interaction effect

Structuring the factors hierarchically

Cognitive map Cause & effect diagram Tree diagram

Quantifying the effect of the factors on impact

Comparing factors Ai, which one does have stronger impact and how strong?

Analytic Hierarchy Processsee Saaty, T.L., 1980, “The Analytic Hierarchy Process”,

McGraw-Hill, New York

Output: Indicators Prioritization

Further Indicator Analysis

For the most influential factors: Paasche’s Index Laspeyres’ Index Decomposition Analysis

Pilot Implementation: Tourism Factors identified:

Hotel rooms available (A) Hotel rooms occupied (B) Tourists Arrivals (C) Touristic currency (D)

StructureAll are one-level sub factors

Criteria of factors selection Importance Acquisition Difficulty

Analytic Hierarchy Process (I) Create pair wise comparison matrixes for

each criteria, for example:

Importance A B C D

A 1 a1 a2 a3

B a1-1 1 a4 a5

C a2-1 a4

-1 1 a6

D a3-1 a5

-1 a6-1 1

where ai [1,…,9] ( Z) and declare importance (preference level)

Analytic Hierarchy Process (II)

Sum all the values in each column Divide the values in each column by

the corresponding column sum Find the average of each row

(decimal)

Analytic Hierarchy Process (III)

The following matrix (M1) is now available:

Tourism Importance Difficulty

A x11 x12

B x21 x22

C x31 x32

D x41 x42

Analytic Hierarchy Process (IV)

Create same-structured pair wise comparison matrix for the criteria for factors selection:

Tourism Importance Difficulty

Importance 1 b1

Difficulty b1-1 1

Analytic Hierarchy Process (V) After following the same process (AHP

II), the following matrix M2 would be available:

Tourism Row average

Importance y1

Difficulty y2

Analytic Hierarchy Process (VI)

The product M=M1xM2 quantifies the prioritization of the factors (indicators)…

Tourism Ranking

A ra

B rb

C rc

D rd

Further Indicator Analysis

Assume that the AHP suggested the indicators Hotel rooms occupied (B) Tourists Arrivals (C) Touristic currency (D)

Now we can move on to further analysis

Paasche’s Index

Paasche’s Index of touristic movement:

where S(t): touristic currency at year t, CPI: consumer price index

CPIStS

CPI

tSPV

)0()(

)()(

Laspeyres’ Index

Laspeyres’ index of price changes:

Where Vj(t)T: Arrivals at year t, tourist category j σj(t)T: Touristic currency per arrival at year t

(tourist category j) : Touristic currency per arrival at year

t (tourist category j) with prices of year ‘0’

n

jTjTj

n

jTjTj

V

tV

1

1

)0()0(

)(ˆ)0(

Tj t)(̂

Philosophy of Deconstruction (Jacques Derrida)…

n

jTTj

n

jTjTj

T

n

jTjTj

n

jTjTj

Tn

jTjTj

n

jTjTj

tV

tV

tV

tV

ttV

tVV

tV

tS

1

11

1

1

1

)()0(

)()0(

)(

)()0(

)()(

)()0()0(

)(ˆ)0(

)(

Decomposition Analysis (I) Which is the overall change of the

composition of night stays from year 0 to year t, broken into hotel category, country of origin and month?

An objective meter is:

where H: hotel, C: country & M: month

H C M HCM

HCMHCMHCM

ttA

)0(

)(ln)(

Decomposition Analysis (II) number of night stays in

hotel category H, tourists from country C, for all months

cell’s ‘HC●’ participation in total night stays

participation of month ‘M’ in the night stays of cell ‘HC●’

M

HCMHC NN

N

NHCHC

HC

HCMHCHCM N

N

Decomposition Analysis (III)

Quantifies the change in the composition of the total night stays in hotel categories and countries of origin

Quantifies the change in the composition of each ‘HC●’ cell in months

H C HC

HCHCHC

ttA

)0(

)(ln)(

MHCHCO

HCHCOHC

HCMHCHCM

ttA

)0(

)(ln)(

Summary

Finally, the measurement of Olympic impact on each system is modelled through:

Identification of the main impact factors & their relationship structure

Determinable quantification (prioritization) of the factors impact on the system through Analytic Hierarchy Process

Advanced analysis of the most influential indicators

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