Skip to main content

Models of Technology Design and Adoption

  • Chapter
  • First Online:
Models of Technologies

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 86))

  • 215 Accesses

Abstract

The management problem of the CA technology of OTSs has been considered and formalized in Chap. 1 (also see Belov and Novikov in Methodology of complex activity. Lenand, Moscow, 320 pp., 2018, [1]). More specifically, the most important peculiarities of the CA of OTSs have been analyzed and also formal models and a mathematical setup of this management problem have been presented.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Notes

  1. 1.

    Hereinafter, the symbol “□” indicates the end of a proof or example.

  2. 2.

    Recall that the learning curve Lt describes the probability that the environment will take a new value at time (t + 1). This probability is estimated using the observations during t times inclusive.

  3. 3.

    This model may have an alternative interpretation as follows. Checks are performed at each step while a technology for a new state is designed with some probability determined by a metaprocess. In the logistic model, this probability is equal to the learning level in the process itself; in the hyperbolic model, to the probability of “error” raised to some power with the proportionality factor µ.

References

  1. Belov M, Novikov D (2018) Methodology of complex activity. Lenand, Moscow, 320 pp (in Russian)

    Google Scholar 

  2. Business Process Model and Notation (BPMN), v2.0.2. http://www.omg.org/spec/BPMN/2.0

  3. Novikov D (2013) Theory of control in organizations. Nova Science Publishers, New York, 341 pp

    Google Scholar 

  4. Novikov D (1998) Laws of iterative learning. Trapeznikov Institute of Control Sciences RAS, Moscow, 98 pp (in Russian)

    Google Scholar 

  5. Ebbinghaus H (1885) Über das Gedächtnis. Dunker, Leipzig, 168 pp

    Google Scholar 

  6. Thurstone L (1919) The learning curve equation. Psychol Monogr 26(3):1–51

    Article  Google Scholar 

  7. Thurstone L (1930) The learning function. J Gen Psychol 3:469–493

    Article  Google Scholar 

  8. Tolman E (1934) Theories of learning. In: Moss FA (ed) Comparative psychology. Prentice Hall, New York, pp 232–254

    Google Scholar 

  9. Atkinson R, Bower G, Crothers J (1967) Introduction to mathematical learning theory. Wiley, New York, 429 pp

    Google Scholar 

  10. Bush R, Mosteller F (1955) Stochastic models for learning. Wiley, New York, 365 pp

    Book  Google Scholar 

  11. Hull C (1943) Principles of behavior and introduction to behavior theory. D. Appleton Century Company, New York, 422 pp

    Google Scholar 

  12. Wright T (1936) Factors affecting the cost of airplanes. J Aeronaut Sci 3(4):122–128

    Article  Google Scholar 

  13. Crawford J (1944) Learning curve, ship curve, ratios, related data. Lockheed Aircraft Corporation, pp. 122–128

    Google Scholar 

  14. Henderson B (1984) The application and misapplication of the learning curve. J Bus Strategy 4:3–9

    Article  Google Scholar 

  15. Leibowitz N, Baum B, Enden G, Karniel A (2010) The exponential learning equation as a function of successful trials results in sigmoid performance. J Math Psychol 54:338–340

    Article  MathSciNet  Google Scholar 

  16. Novikov D (2012) Collective learning-by-doing. IFAC Proc Vol 45(11):408–412

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Mikhail V. Belov .

Rights and permissions

Reprints and permissions

Copyright information

© 2020 Springer Nature Switzerland AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Belov, M.V., Novikov, D.A. (2020). Models of Technology Design and Adoption. In: Models of Technologies. Lecture Notes in Networks and Systems, vol 86. Springer, Cham. https://doi.org/10.1007/978-3-030-31084-4_2

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-31084-4_2

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-31083-7

  • Online ISBN: 978-3-030-31084-4

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics