An Information System Approach to the Analysis of Job Design

  • Peter S. Albin
  • Farrokh Z. Hormozi
  • Stergios L. Mourgos
  • Arthur Weinberg

Abstract

In many structured job designs, job content can be identified with the complexity of human-machine interfaces, with the computational or logical complexity of decision routines, and with interactive complexities associating with organizational or command structures. We have argued elsewhere(2) that such complexities may be measured or evaluated using established results in the theory of automata(3–5) and methods developed by us(6,7) to yield a practically small set of complexity parameters and class indices descriptive of an entire job and/or routines and tasks within the job. In turn, it is hypothesized that complexity parameters and indices so derived can be used to predict behavioral responses to the job. Appropriate job content can affect attitudes toward work generally, improve performance specifically, and may assist in developing responsibility. In an industrial setting, these effects would be partial determinants of general productivity and individual satisfaction. They may also associate with performance reliability for an operation or system and with the developments of responsibility, efficiency, and sustainable interest for individuals and groups.

Keywords

Univer MSCL 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    R. J. Hackman and G. R. Oldham, Work Redesign, Addison-Wesley, Reading, Massachusetts, 1980.Google Scholar
  2. 2.
    P. S. Albin and A. S. Weinberg, Work complexity in structured job designs, Human Syst. Manage. (1983) (forthcoming).Google Scholar
  3. 3.
    A. Ginsburg, Algebraic Theory of Automata, Academic Press, New York, 1968.Google Scholar
  4. 4.
    K. Krohn and J. Rhodes, Algebraic theory of machines, Trans. Am. Math. Soc. 116, 450–464 (1965).MathSciNetMATHCrossRefGoogle Scholar
  5. 5.
    A. R. Smith, Cellular automata complexity trade-offs, Inf. Control, 18, 446–482 1971.CrossRefGoogle Scholar
  6. 6.
    P. S. Albin, The Analysis of Complex Socio-Economic Systems, D. C. Heath & Co., Lexington, Massachusetts, 1975.Google Scholar
  7. 7.
    P. S. Albin, The complexity of social groups and social systems described by graph structures, Math. Social Sci. 1, 101–129 (1980).MathSciNetMATHCrossRefGoogle Scholar
  8. 8.
    N. Chomsky, Syntactic Structures, Mouten, London, 1965.Google Scholar
  9. 9.
    M. Minsky, Computation: Finite and Infinite Machines, Prentice-Hall, Englewood Cliffs, New Jersey, 1967.Google Scholar
  10. 10.
    C. Futia, The Complexity of Economic Decision Rules, Bell Laboratories, Murray Hill, New Jersey, January 1975.Google Scholar
  11. 11.
    P. S. Albin, C. Bahn et al. Worker perception of job complexity, Research Paper #RM.ll. Center for the Study of System Structure and Industrial Complexity, CUNY, 1983.Google Scholar
  12. 12.
    P. S. Albin, The metalogic of economic predictions, calculations and propositions, Math. Social Sci. 3, 329–358 (1982).MathSciNetMATHCrossRefGoogle Scholar
  13. 13.
    H. A. Simon, Rationality as process and as product of thought, Am. Econ. Rev. 68(2), 1–16 May (1978).Google Scholar
  14. 14.
    G. E. Flueckiger, A finite automaton model of behavior and learning, Econ. Inquiry, XVI(4), 508–530 (1978).CrossRefGoogle Scholar
  15. 15.
    R. B. Freeman, Job satisfaction as an economic variable, Discussion paper #592, Harvard Institute of Economic Research, Harvard University, Cambridge, Massachusetts, 1977.Google Scholar
  16. 16.
    Dictionary of Occupational Titles, U.S. Department of Labor, 1977.Google Scholar

Copyright information

© Plenum Press, New York 1984

Authors and Affiliations

  • Peter S. Albin
    • 1
  • Farrokh Z. Hormozi
    • 2
  • Stergios L. Mourgos
    • 1
  • Arthur Weinberg
    • 1
  1. 1.John Jay CollegeCity University of New YorkNew YorkUSA
  2. 2.Pace UniversityPleasantvilleUSA

Personalised recommendations