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Quantitative Model For an Impact Measurement System
Quantitative Model For an Impact Measurement System
Quantitative Model For an Impact Measurement System
Quantitative Model For an Impact Measurement System
Quantitative Model For an Impact Measurement System
Quantitative Model For an Impact Measurement System
Quantitative Model For an Impact Measurement System
Quantitative Model For an Impact Measurement System
Quantitative Model For an Impact Measurement System
Quantitative Model For an Impact Measurement System
Quantitative Model For an Impact Measurement System
Quantitative Model For an Impact Measurement System
Quantitative Model For an Impact Measurement System
Quantitative Model For an Impact Measurement System
Quantitative Model For an Impact Measurement System
Quantitative Model For an Impact Measurement System
Quantitative Model For an Impact Measurement System
Quantitative Model For an Impact Measurement System
Quantitative Model For an Impact Measurement System
Quantitative Model For an Impact Measurement System
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Quantitative Model For an Impact Measurement System

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  • 1. Quantitative model for impact measurement system National Technical University of Athens
  • 2. Identification of impact factors & their relationship
    • Effect of a factor on impact:
    • Direct (vertical) effect
    • Indirect (horizontal) effect
    • Self-interaction effect
  • 3. Structuring the factors hierarchically
    • Cognitive map
    • Cause & effect diagram
    • Tree diagram
  • 4. Quantifying the effect of the factors on impact
    • Comparing factors A i , which one does have stronger impact and how strong?
    • Analytic Hierarchy Process
      • see Saaty, T.L., 1980, “The Analytic Hierarchy Process”, McGraw-Hill, New York
    • Output: Indicators Prioritization
  • 5. Further Indicator Analysis
    • For the most influential factors:
    • Paasche’s Index
    • Laspeyres’ Index
    • Decomposition Analysis
  • 6. Pilot Implementation: Tourism
    • Factors identified:
      • Hotel rooms available (A)
      • Hotel rooms occupied (B)
      • Tourists Arrivals (C)
      • Touristic currency (D)
    • Structure
      • All are one-level sub factors
    • Criteria of factors selection
      • Importance
      • Acquisition Difficulty
  • 7. Analytic Hierarchy Process (I)
    • Create pair wise comparison matrixes for each criteria, for example:
    where a i [1,…,9] ( Z) and declare importance (preference level) 1 a 6 -1 a 5 -1 a 3 -1 D a 6 1 a 4 -1 a 2 -1 C a 5 a 4 1 a 1 -1 B a 3 a 2 a 1 1 A D C B A Importance
  • 8. 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)
  • 9. Analytic Hierarchy Process (III)
    • The following matrix (M 1 ) is now available:
    x 42 x 41 D x 32 x 31 C x 22 x 21 B x 12 x 11 A Difficulty Importance Tourism
  • 10. Analytic Hierarchy Process (IV)
    • Create same-structured pair wise comparison matrix for the criteria for factors selection:
    1 b 1 -1 Difficulty b 1 1 Importance Difficulty Importance Tourism
  • 11. Analytic Hierarchy Process (V)
    • After following the same process (AHP II), the following matrix M 2 would be available:
    y 2 Difficulty y 1 Importance Row average Tourism
  • 12. Analytic Hierarchy Process (VI)
    • The product M=M 1 xM 2 quantifies the prioritization of the factors (indicators)…
    r d D r c C r b B r a A Ranking Tourism
  • 13. 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
  • 14. Paasche’s Index
    • Paasche’s Index of touristic movement:
    • where S(t): touristic currency at year t,
    • CPI: consumer price index
  • 15. Laspeyres’ Index
    • Laspeyres’ index of price changes:
    • Where
        • V j (t) T : Arrivals at year t, tourist category j
        • σ j (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’
  • 16. Philosophy of Deconstruction (Jacques Derrida)…
  • 17. 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
  • 18. 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●’
  • 19. 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
  • 20. 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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