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Development of Survivor Models Using Technological Growth Models  

Oh, Hyun-Seung (Department of Industrial and Management Engineering, Hannam University)
Cho, Jin-Hyung (Division of Industrial Engineering, Kumoh Institute of Technology)
Publication Information
Journal of Korean Society of Industrial and Systems Engineering / v.33, no.4, 2010 , pp. 167-177 More about this Journal
Abstract
Recent competitive and technological changes during the past decade have accelerated the need for better capital recovery methods. Competition and technology have together shortened the expected lives of property which could not have been forecasted several years ago. Since the usage of technological growth models has been prevalent in various technological forecasting environments, the various forms of growth models have become numerous. Of six such models studied, some models do significantly better than others, especially at low penetration levels in predicting future levels of growth. A set of criteria for choosing an appropriate model for technological growth models was developed. Two major characteristics of an S-shaped curve were elected which differentiate the various models; they are the skewness of the curve and underlying assumptions regarding the variance of error structure of the model.
Keywords
Technological Growth Models; Capital Recovery Methods;
Citations & Related Records
Times Cited By KSCI : 2  (Citation Analysis)
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1 Lakani, H.; "Diffusion of Environment-Saving Technological Change : A Petroleum Refining Case Study," Technological Forecasting and Social Change, 7(1) : 33-35. 1975.   DOI   ScienceOn
2 Sharif, M. N. and Islam, M. N.; "The Weibull distribution as a General Model for Forecasting Technological Change," Technological Forecasting and Social Change, 18 : 247-256, 1980.   DOI   ScienceOn
3 Sharif, M. N. and Uddin, G. A.; "A Procedure for Adapting Technological Forecasting Models," Technological Forecasting and Social Change, 7 : 99-106. 1975.   DOI   ScienceOn
4 Tingyan, X.; "A Combined Growth Model for Trend Forecasts," Technological Forecasting and Social Change, 8 : 175-186, 1990.
5 Weibull, W.; "A Statistical Distribution Function of Wide Applicability," Journal of Applied Mechanics, 18 : 293-297, 1951.
6 White, B. E.; "Economic Forces of Retirement," Proceedings of the Iowa State University Regulatory Conference, Ames, Iowa, 1986.
7 Wissema, J. G.; "Trends in Technology Forecasting," R and D Management, 12(1) : 36, 1982.
8 Wolf, F.; "Forecasting Force of Mortality," Proceedings of the Iowa State University Regulatory Conference, Ames, Iowa, 1985.
9 Hartley, H. O.; "The Modified Gauss-Newton Method for Fitting Non-linear regression Function by Least Squares," Technometrics, 3(2) : 269-280, 1961.   DOI   ScienceOn
10 Hayes, J. G.; Numerical Approximation to Functions and Data, University of London, The Athlone Press, 1970.
11 Krane, S. A.; "Analysis of Survival Data by Regression Techniques," Technometrics, 5 : 161-174, 1963.   DOI   ScienceOn
12 Lawless, J. F.; Statistical Models and Methods for Lifetime Data, New York: John Wiley and Sons, Inc., 1982.
13 Martino, J. P.; Technological Forecasting for Decision Making, Elsevier, New York, U. S. A., 1975.
14 Lenz, R. C. Jr.; Technological Forecasting Report ASDTDR- 62-114, Aeronautical Sysyems Divisions, Wright=Patterson Air Forcs Base, Ohio, 1962.
15 Mansfield, E.; Industrial Research and Technological Innovation: An Econometric Analysis, New York; W.W. Northon and Company, Inc., 1968.
16 Marquardt, D. W.; "An Algorithm for Least Squares Estimation of Nonlinear Parameters," Journal of Society for Industrial and Applied Mathematics, 11 : 431-441, 1963.   DOI
17 May, J. M.; "Extended and Corrected Tables of the Upper Percentage Points of the Studentized Range," Biometrica, 39 : 192-193, 1952.
18 Oh, H. S.; "The Weibull Distribution As An Estimator of Generalized Survivor Curves," M. S. thesis, Iowa State University of Science and Technology, Ames, Iowa, U. S. A., 1986.
19 Oh, H. S.; "The Selection of Technological Forecasting Models in Life Analysis," Ph. D. Dissertation, Iowa State University of Science and Technology, Ames, Iowa, U. S. A, 1988.
20 Pearl, R.; The Biology of Population, New York; Alfred A. Konpf. 1925.
21 Pearl, R. and Reed, L. J.; "A Further Note on the Mathematical Theory of Population Growth," Proceeding of the National Academy of Science, 8 : 365-368, 1922.   DOI   ScienceOn
22 Sharif, M. N. and Kabir, C.; "A Generalized Model For Forecasting Technological Substitution," Technological Forecasting and Social Change, 18 : 353-364, 1976.
23 Ayres, R. U.; "The Future of Technological Forecasting," Technological Forecasting and Social Change, 30 : 4960, 1989 .
24 Balachandra, R.; "Perceived Usefulness of Technological Forecasting Technique," Technological Forecasting and Social Change, 16 : 157, 1980.
25 Blackman, A. W.; "The Market Dynamics of Technological Substitutions," Technological Forecasting and Social Change, 6 : 41-63, 1974.   DOI   ScienceOn
26 Conover, W. J.; Practical Non-parametric Statistics, 2nd Edition, John Wiley and Sons, 1980 .
27 Bass, F. M.; "A New Product Growth Models for Consumer Durables," Management Science, 15 : 215-227, 1989.
28 Bass, F. M., Trichy, V. K., and Dipak, C. J.; "Why the Bass Model Fits without Decision variables," Marketing Science, 13(3) : 203-223, 1994.   DOI   ScienceOn
29 Booth, H.; "Transforming Gompertz's Function for Fertility Analysis : The Development of a Standard for the Relational Gompertz Function," Population Studies, 38 : 495-506, 1984.   DOI   ScienceOn
30 Dandekar, M.; "Investigation the Product Life Cycle Concepts: An Application to Capital Recovery, Evaluation within the Telephone Industry," Ph. D. Dissertation, Iowa State University of Science and Technology, Ames, Iowa, U.S.A., 1987.
31 Elant, R. C. and Johnson, N. L.; Survival Models and Data Analysis, New York: John Wiley and Sons, Inc., 1980.
32 Fisher, J. C. and Pry, R. H.; "A Simple Substitution Model of Technological Change," Technological Forecasting and Social Change, 3 : 75-88, 1971.   DOI
33 Fitch, J. C.; "Conceptual Framework for Forecasting the Useful Life of Industrial Property," Proceedings of the Iowa State University Regulatory Conference, Ames, Iowa, U.S.A., 1984
34 Flody, A. L.; "A Methodology For Trend Forecasting of Figures of Merit," Edited by lR. Bright, Englewood Cliffs, New Jersey : Prantice Hall, Inc., 1986.
35 Goldfeld, S. M. and Quandt, R. E.; "Some Test for Homoscedasticity," Journal of the American Statistical Association, 60(310) : 539-547, 1965.   DOI   ScienceOn
36 오현승, 김종수, 이한교, 임동순, 조진형; "기술 발전에 따른 생존모형 선정", 산업경영시스템학회지, 32(4) : 184-191, 2009.   과학기술학회마을
37 오현승, 이한교, 김경택; "설비 생존곡선 추정을 위한 혼합형 Weibull 함수의 적용", 산업경영시스템학회지, 30(1) : 66-73,2007.   과학기술학회마을