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Thermodynamics of Productivity Framework for Impact of InformationCommunication Investments

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Viterbi School of Engineering Technology Transfer Center ... Thorne, Fernando, Lenden, Silva, 2000. Thermodynamics and Biology Drove New Growth Economics ... – PowerPoint PPT presentation

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Title: Thermodynamics of Productivity Framework for Impact of InformationCommunication Investments


1
Thermodynamics of Productivity Framework for
Impact of Information/Communication Investments
  • Ken Dozier
  • USC Viterbi School of Engineering Technology
    Transfer Center

2
Presentation Outline
  • Problem (7 slides)
  • Approach (9 slides)
  • Results (8 slides)
  • Conclusions (1 slide)
  • Future (1 slide)

3
A System of Forces in Organization
Direction
Cooperation
Efficiency
Proficiency
Competition
Concentration
Innovation
Source The Effective Organization Forces and
Form, Sloan Management Review, Henry Mintzberg,
McGill University 1991
4
Make Sell vs Sense Respond
Chart SourceCorporate Information Systems and
Management, Applegate, 2000
5
Supply Chain (Firm)
Source Gus Koehler, University of Southern
California Department of Policy and Planning,
2002
6
Supply Chain (Government)
Source Gus Koehler, University of Southern
California Department of Policy and Planning,
2002
7
Supply Chain (Framework)
Source Gus Koehler, University of Southern
California Department of Policy and Planning,
2002
8
Supply Chain (Interactions)
Source Gus Koehler, University of Southern
California Department of Policy and Planning,
2002
9
Theoretical Environment
Seven Organizational Change Propositions
Framework, Framing the Domains of IT
Management Zmud 2002
10
Framework Assumptions
  • U.S. Manufacturing Industry Sectors can be
    Stratified using Average Company Size and
    Assigned to Layers of the Change Propositions
  • Layers with Large Average Firm Size Will Have
    High B and Lowest T(1/B)
  • Layers with Small Average Firm Size Will Have Low
    B and High T (1/B)
  • The B and T Values Provide the Entry Point to
    Thermodynamics

11
Thermodynamics ?
  • Ample Examples of Support
  • Long Term Association with Economics
  • Krugman, 2004
  • Systems Far from Equilibrium can be Treated by
    (open systems) Thermodynamics
  • Thorne, Fernando, Lenden, Silva, 2000
  • Thermodynamics and Biology Drove New Growth
    Economics
  • Costanza, Perrings, and Cleveland, 1997
  • Economics and Thermodynamics are Constrained
    Optimization Problems
  • Smith and Foley, 2002

12
Thermodynamics ?
  • Mathematical Complexity Could Discourage
    Practitioners
  • Requires an Extension of Traditional Energy
    Abstractions
  • Expansion May Require Knowledge to be Considered
    Pseudo Form of Energy?!
  • Knowledge Potential and Kinetic States?!
  • Patent potential
  • Technology Transfer Kinetic
  • Tacit versus Explicit

13
Constrained Optimization Approach
  • Thermodynamics
  • A systematic mathematical technique for
    determining what can be inferred from a minimum
    amount of data
  • Key Many microstates possible to give an
    observed macrostate
  • Basic principle Most likely situation given by
    maximization of the number of microstates
    consistent with an observed macrostate
  • Why pseudo?
  • Conventional thermodynamics energy rules
    supreme
  • Thermodynamics of economics phenomena energy
    shown by statistical physics analysis to be
    replaced by quantities related to productivity,
    i.e. output per employee

14
Pseudo-Thermodynamic Approach
  • Macrostate givens N and E, and census-reported
    sector productivities p(i)
  • Total manufacturing output of a metropolitan area
    N
  • Total number of manufacturing employees in
    metropolitan area E
  • Productivities p(i), where p(i) is the
    output/employee of manufacturing sector I
  • Convenient to work with a dimensionless
    productivity
  • p(i) p(i)/ltPgt (Chang Simplification)
  • where ltPgt is the average value for the
    manufacturing sectors of the output/employee for
    the metropolitan area.
  • Thermodynamic problem with the foregoing
    givens
  • What is the most likely distribution of employees
    e(i) over the sectors that comprise the
    metropolitan manufacturing activity ?
  • What is the most likely distribution of output
    n(i) over the sectors?

15
Pseudo-Thermodynamic Approach
  • Relations between total metropolitan employee
    number E and output N and sector employee numbers
    e(i) and outputs n(i)
  • E S e(i)
  • N S n(i)
  • Relation between sector outputs, employee
    numbers, and productivities
  • n(i) e(i) p(i)
  • n(i) e(i)ltPgtp(i)
  • Accordingly,
  • N S n(i) S e(i) ltPgt p(i)

16
Pseudo-Thermodynamic Approach
  • Look for the (microstate) distribution e(i) that
    will give the maximum number of ways W in which a
    known (macrostate) N and E can be achieved.
  • Number of ways (distinguishable permutations) in
    which N and E can be achieved
  • W N! / ? n(i)!E! / ? e(i)!
  • Maximization of W subject to constraint
    equations of previous slide
  • Introduce Lagrange multipliers ? and ß to take
    into account constraint equations
  • Deal with lnW rather than W in order to use
    Stirling approximation for natural logarithm of
    factorials for large numbers
  • lnn! gt n lnn- n when n gtgt1

17
Optimization
  • Maximization of lnW with Lagrange multipliers
  • ? / ? e(i) lnW ?N-Sn(i) ßE-Se(i)
    0
  • Use of relation between n(i) and e(i) and p(i)
  • ?/ ? e(i) lnW ?N-S e(i)ltPgtp(i)
    ßE-Se(i) 0
  • where, using Stirlings approximation
  • lnW N(lnN-1) E(lnE-1) - S e(i)p(i)ltPgtlne(i)
    p(i)ltPgt-1
  • - S e(i)lne(i)-1

18
Resulting Distributions
  • Employee distribution over manufacturing sectors
    e(i)
  • e(i) D p(i)-p(i)/p(i)1 Exp -
    ßp(i)/1p(i)
  • where the constants D and ß are expressible
    in terms of the Lagrange multipliers that allow
    for the constraint relations
  • Output distribution over manufacturing sectors
    n(i)
  • n(i) DltPgt p(i) 1/p(i)1 Exp -
    ßp(i)/1p(i)
  • Two interesting features
  • NonMaxwellian i.e. Not a simple exponential
  • An inverse temperature factor (or bureacratic
    factor) ß that gives the disperion of the
    distribution

19
Figure 1 Predicted shape of output n(i) vs.
productivity p(i) for a sector bureaucratic
factor ß 0.1 lower curve and ß1 upper
curve.
Output
n(i)
p(i)
20
Figure 2. Predicted shape of employee number
e(i) vs. productivity p(i) for a sector
bureaucratic factor ß 0.1 lower curve and ß1
upper curve.
Employment
e(i)
p(i)
21
Figure 3. Data Employment vs productivity for
the 140 manufacturing sectors in the Los Angeles
consolidated metropolitan statistical area in 1997
Data
22
Productivity Paradox
Figure 4. Productivities in Los Angeles
consolidated metropolitan statistical area.
(Ignore Industry Sector Average Company Size)
1.8
1.6
1.4
1.2
1
Ratio of 1997 productivity to 1992 productivity
0.8
0.6
0.4
0.2
0
0
15
30
45
60
75
90
105
120
135
Average rank of per capita information technology
expenditure
23
Stratified
Figure 5. Productivities in Los Angeles
consolidated metropolitan statistical area. (3
Industry sector sizes)
1.8
1.6
26 largest company size sectors
1.4
1.2
26 intermediate company size sectors
24 smallest company size sectors
1
Ratio of 1997 productivity to 1992 productivity
0.8
0.6
0.4
0.2
0
0
15
30
45
60
75
90
105
120
135
Average rank of per capita information technology
expenditure
24
Effects of Technology Transfer
Task 1. Approach
Ln Output
High output N, High temperature 1/b
Costs down
High output N, Low temperature 1/b
Low output N, High temperature 1/b
Entropy up
Low output N, Low temperature 1/b
Unit costs
25
Effects of Technology Transfer
Task 1. Semiconductor example Movement
between 1992 and 1997 on Maxwell Boltzmann plot
1997 High output N, Low temperature 1/b
Ln Output
1992 Low output N, High temperature 1/b
Unit costs
26
Effects of Technology Transfer
Task 1. Heavy spring example Movement between
1992 and 1997 on Maxwell Boltzmann plot
Ln Output
1997 Low output N, High temperature 1/b
1992 Low output N, Low temperature 1/b
Unit costs
27
Conclusions
  • Agreement with industry sector behavior to
    thermodynamic model.
  • Consistent across multiple definitions of
    productivity.
  • Interaction between average per capita
    expenditure on information technology,
    organizational size and the average increase in
    productivity
  • IT investment alters B
  • High IT (electronics) Investor changed their B,
    Low IT Investor (heavy springs) did not

28
Future Work
  • Examine NAICS consistent 2002 and 1997 U.S.
    manufacturing economic census data
  • Use seven organizational change proposition
    strata to further explore the linkage between
    organizational size and productivity.
  • Compare results across the strata and within each
    stratum
  • Check for compliance to thermodynamic model
  • Expand to technology transfer
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