Strategic decision making a systems dynamic model of a bulgarian firm
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Strategic Decision Making: A Systems Dynamic Model of a Bulgarian Firm. David L. Olson, University of Nebraska Madeline Johnson, Univ. of Houston-Downtown Margaret F. Shipley, Univ. of Houston-Downtown Nikola Yankov, Tsenov Academy of Economics. Transition Economies.

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Strategic decision making a systems dynamic model of a bulgarian firm

Strategic Decision Making: A Systems Dynamic Model of a Bulgarian Firm

David L. Olson, University of Nebraska

Madeline Johnson, Univ. of Houston-Downtown

Margaret F. Shipley, Univ. of Houston-Downtown

Nikola Yankov, Tsenov Academy of Economics


Transition economies
Transition Economies

  • Transition from centrally-planned to market economies

  • Face ambiguous information and cues

    • Challenge existing ownership & operating principles

    • Firms responsible for strategic decisions


Joint effort
Joint Effort

  • University of Houston-Downtown

    • NSF Grant – Joint International Workshop on the Use of Information Technologies in Modeling the Bulgarian Firm in Transition from a Planned to a Free Market Economy

  • Tsenov Academy of Economics

    • Svishtov, Bulgaria


Subjective system dynamics model
Subjective System Dynamics Model

  • Winery

  • Tool to simulate impact of key strategic decisions:

    • Market selection (local, national, international)

    • Promotion & pricing

    • Product quality decisions

    • Capacity (vineyards and bottling)

    • Distribution


Open systems theory
Open Systems Theory

  • Ludwig von Bertalanffy

    • An organization exists in relation to its environment

    • There is a continuous flow of energy & information

    • System features:

      • Self-organization - progressive differentiation

      • Equifinality – initial condition doesn’t matter

      • Teleology – systems are purpose-driven


Cybernetics
Cybernetics

  • Stafford Beer

    • Cybernetic systems are complex, probabilistic, self-regulatory, purposive, have feedback and control

    • Operations research only works when you consider the whole

    • Viable System Model – organization regulated, learns, adapts, evolves, or doesn’t survive


Mental models
Mental Models

  • Systems consist of interacting parts working toward some end, feedback control

    • Purposive

    • Synergistic

    • Complex

    • Feedback


System dynamics
System Dynamics

  • Jay Forrester

    • Developed technique for deterministic simulation of systems

      • Identify influences

      • Estimate effects

      • Develop feedback model


Forrester s world dynamics model
Forrester’s World Dynamics Model

  • Sectors

    • Population

    • Natural Resources

    • Capital Investment

    • Pollution

  • Metrics

    • Quality of life

    • Material standard of living

    • Ratios for FOOD, CROWDING, POLLUTION


Soft systems theory peter checkland
Soft Systems TheoryPeter Checkland

  • Interpretive action research

  • Model interacting system

    • Define problem done

    • Express situation done

    • Root definition

    • Conceptual model done – simulation model

    • Compare model/real world

    • Use model to determine improved methods

    • Action


Simulation approaches
Simulation Approaches

  • DYNAMO/Ithink/Stella/PowerSim

  • VENSIM

    • Commercial implementation of system dynamics

    • Support conceptual modeling

  • EXCEL

    • Probabilistic simulation over time

  • CRYSTAL BALL

    • Probabilistic simulation output


Development of model
Development of Model

  • Symposium in Svishtov, Bulgaria

    • May 2002

    • About 20 from U.S., 20 from Svishtov

  • Selected winery because of knowledge of Tsenov Academy faculty

  • Selected system dynamics because:

    • Problem involved subjective data

    • Complex interactions among decisions, time


Winery model
Winery Model

  • Time frame: 6 years

    • Show impact of strategic decisions

  • Inputs:

    • Promotion

    • Pricing

    • Quality (grow or purchase grapes)

    • Market selection (local, national, international)

  • Outputs

    • Profit

    • Cash flow

    • Market share by product (3 levels of quality)


Promotion
Promotion

  • Lagged over three month

  • Impact differentials

    • 0.5 prior month

    • 0.35 two months prior

    • 0.15 three months prior

  • Media: firm representatives interacting with distributors

  • Management could constrain local, national, or export markets to emphasize others

    • Demands in each market probabilistic


Quality
Quality

  • If winery controls vineyard, quality higher

  • Constrained by amount of hectares in vines

    • Three years between planting, use

    • Use own grapes as much as possible

      • Any extra production capacity used for purchased grapes (lower quality bottles)


System variables
System Variables

  • Exogenous:

  • System Variables:

  • Control Inputs:


Exogenous variables
Exogenous Variables

  • Demand (normally distributed, change per month)

    • By market (local, national, export)

    • By product (correlated)

    • Seasonal

  • Market Price (normally distributed, change per month)

    • Independent of firm decisions

  • Competitor promotion (normally distributed by market)

  • Market share possibilities

    • Prior market share multiplied by ratio of prior promotion to base promotion, divided by that of competitors

  • Crop yield


Control inputs
Control Inputs

  • Price

    • By product by month

  • Promotion

    • By product by month

  • Plant Capacity

    • Depreciation, plus construction

  • Labor

    • Permanent (higher quality) vs. temporary


System variables1
System Variables

  • Sales

    • By market, by product

  • Inventory

    • High, low quality

  • Bank Balance

    • 5% gain on positive balance, 15% cost on negative


Results
Results

  • Varied prices, promotion levels

    • Price: base, cut 10%, increase 20%

    • Promotion: base, emphasize local, emphasize export

  • Measured

    • bank balance after 6 years

    • Probability of losing initial capital (going broke)

    • Probability of breaking even

    • Market share (low, high quality)



Base model
Base Model

  • 1000 replications

  • Crystal Ball software

  • Cyclical demand for high quality

  • Base case has National focus

  • Without pricing & promotion, loss



Bank balance
Bank Balance

  • Mean 117,458 Lev

  • Probability of losing bankroll: 0.0

  • Probability of losing money: 0.0

  • Most optimistic:

  • Worst: loss:




National market share mixed policies
National Market Share – Mixed policies


Model validation
Model Validation

  • Initial visit May 2002

    • 3 day workshop to build model

  • Built model summer 2002

  • Followup visit October 2003

    • Went over model in detail

    • Refined model structure

    • Identified detailed data needs


Conclusions
Conclusions

  • System dynamics useful to model subjective input, complex interactions in temporal environment

  • Need for validation


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