The effects of chaos in business operations

  1. Klinkova, Galiya
Dirigida por:
  1. José María Labeaga Azcona Director/a
  2. Michael Grabinski Director/a

Universidad de defensa: UNED. Universidad Nacional de Educación a Distancia

Fecha de defensa: 30 de noviembre de 2017

Tribunal:
  1. Alberto Augusto Álvarez López Presidente/a
  2. Antonio José Heras Martínez Secretario
  3. Elmar Steurer Vocal

Tipo: Tesis

Resumen

It was Edward Lorenz of MIT who found out, that long term weather forecast is impossible due to chaos effects. The small flow of a butterfly wing determines whether it will rain in 30 or say 31 days. This is commonly known as butterfly effect. It sets a natural limit to the weather forecast. Forecasting and planning in business and economics is quite analogous to the weather forecast. Data from the past till present are used to determine the possible data of the future. Is there a “butterfly effect” in forecasting in business and economics? In this thesis four areas are scrutinized in order to answer this question: i) optimal warehouse positions, ii) market forecast, iii) diffusion model of marketing, and iv) financial markets. The results are as follows: i) The topology of a planned (future) warehouse distribution may depend on an arbitrarily small change of the given data. In general, no planning is possible. ii) The market share does not vary chaotically with today’s market data. However, the time to reach a certain market share may vary chaotically. In general, planning of this time is impossible. iii) In the diffusion model of marketing, chaos effects had been predicted in at least one publication of the 1990ties. However, scrutinizing the diffusion model (and its typical usage) shows, that there are no chaos effects if one uses it properly. iv) Market prices in most financial markets are not stable. Together with the complexity of financial markets it will lead to an unpredictable and chaotic development of prices. In physics people deal with otherwise chaotic situations by sticking to conserved quantities only. They cannot vary chaotically, because if, for example, the energy increases in one place it must decrease in some other. A chaotic fluctuation is impossible. In the case of the weather forecast one cannot predict whether it will rain in 30 or 31 days at a certain place. But one can accurately predict the average rainfall over some period. It is a conserved quantity. If it rains, the same amount of water must have been evaporated somewhere else. This has already been used in finance and accounting by defining a conserved value (in contrast to price). All examples in this thesis are in accordance to the general law that conserved quantities cannot vary chaotically.