Learning Curves in The Knowledge Intensive Services Sub-Sectors

Year 2020, , 477 - 491, 15.07.2020

Gürkan Çalmaşur Hüseyin Daştan Zeynep Karaca

https://doi.org/10.25287/ohuiibf.658987

Cited By: 1

Abstract

The learning curve illustrates the decrease in average cost as the cumulative total output of the firm increases. There are different learning curve models including univariate and multivariate. The traditional univariate learning curve symbolizes a dependent variable such as production cost in terms of independent variables (cumulative output, etc.). The univariate models are the log-linear model, the S-curve, the Stanford-B model, DeJong’s learning formula, Levy’s adaptation function, Glover’s learning formula, Pegel’s exponential function, Knecht’s upturn model, and Yelle’s product model. Among these models, the S-curve or cubic learning model assumes that the level of learning varies over time. The learning curves have traditionally been used for industry and service sectors. Service sector is the branch of industry in which the service is produced rather than the final goods. The main aim of this study is to make a detailed analysis the learning curves in the Turkish Knowledge Intensive Services sub-sectors for 2003-2017 period. In order to satisfy this aim, the cubic learning model has been estimated and calculated the learning (progress) ratio values Knowledge Intensive Services sub-sectors from 2003 to 2017. According to the findings obtained from the study, it was observed that the learning curve in the Knowledge Intensive Services sectors in each sub-sector has four different shapes, convex, concave, negative and positive slope.

Keywords

Learning Curve, Knowledge Intensive Services, Turkey

Bilgi Yoğun Hizmetler Alt Sektörlerinde Öğrenme Eğrileri

Abstract

Öğrenme eğrisi, firmanın kümülatif toplam üretimi arttıkça ortalama maliyetlerindeki düşüşü göstermektedir. Tek değişkenli ve çok değişkenli olmak üzere farklı öğrenme eğrisi modelleri vardır. Geleneksel tek değişkenli öğrenme eğrisi, üretim maliyeti gibi bir bağımlı değişkeni kümülatif üretim miktarı vb. Bağımsız değişkenler açısından açıklamaya çalışmaktadır. Tek değişkenli modeller arasında Log-Lineer model, S-eğrisi, Stanford-B modeli, DeJong'un öğrenme formülü, Levy'nin adaptasyon fonksiyonu, Glover'ın öğrenme formülü, Pegel'in üstel fonksiyonu, Knecht'in yükselme modeli, Yelle'nin ürün modeli sayılabilir. Söz konusu modeller içinde S-eğrisi veya kübik öğrenme modeli, öğrenme seviyesinin zaman içinde değiştiğini varsaymaktadır. Öğrenme eğrileri geleneksel olarak sanayi ve hizmet sektörlerinde kullanılmaktadır. Hizmetler sektörü, nihai ürünlerden ziyade hizmetin üretildiği bir endüstri koludur. Bu çalışmanın ana amacı, 2003-2017 dönemi için Türk Bilgi Yoğun Hizmetler alt sektörlerine ait öğrenme eğrilerini detaylı bir biçimde analiz etmektir. Bu amacı gerçekleştirmek için kübik öğrenme modeli, 2003 ve 2017 yılları arasında Bilgi Yoğun Hizmetler alt sektörleri için öğrenme (ilerleme) oranı değerleri tahmin edilmiş ve hesaplanmıştır. Çalışmadan elde edilen bulgulara göre, Bilgi Yoğun Hizmetler sektörlerinde her bir alt sektördeki öğrenme eğrisinin dış bükey, içbükey, negatif ve pozitif eğimli olmak üzere dört farklı şekle sahip olduğu görülmüştür.

Keywords

Öğrenme Eğrisi, Öğrenme (İlerleme) Oranı, Bilgi Yoğun Hizmetler, Türkiye

References

• Aduba, J. J. & Izawa, H. (2018). Industry (Economic)-Wide Learning: A Comparative Study of Manufacturing and Non-Manufacturing Sector in Japan. Asian Journal of Economics, Business and Accounting, 9(4), 1–14.
• Anzanello, M. J. & Fogliatto, F. S. (2011). Learning Curve Models and Applications: Literature Review and Research Directions. International Journal of Industrial Ergonomics, 41, 573–583.
• Argote, L., Beckman, S. L. & Epple, D. (1990). The Persistence and Transfer of Learning in Industrial Settings. Management Science, 36(2), 140–154.
• Argote, L. & Epple, D. (1990). Learning Curves in Manufacturing. Science, 247(4945), 920–924.
• Asgari, B. & Gonzalez-Cortez, J. L. (2012). Measurement of Technological Progress 
Through Analysis of Learning Rates; The Case of the Manufacturing Industries in Mexico. Ritsumeikan Journal of Asian Pacific Studies, 31, 101–119.
• Asgari, B. & Yen, L. W. (2009). Accumulated Knowledge and Technical Progress in Terms of Learning Rate; A Comparative Analysis on the Manufacturing Industry and Service Industry in Malaysia. Asian Journal of Technological Innovation, 17(2), 71–99.
• Asher, H. (1956). Cost-Quantity Relationships in the Airframe Industry. Report No. 291, RAND Corporation.
• Badiru, B. A. (1992). Computational Survey Univariate and Multivariate Learning Curve Models. IEEE Transaction on Engineering Management, 39, 176–188.
• Baloff, N. (1971). Extension of the Learning Curve-Some Empirical Results. Operational Research Quarterly, 22(4), 329–340.
• Boston Consulting Group. (1970). Perspectives on Experience. Boston: Boston Consulting Group.
• Boston Consulting Group. (1973). The Experience Curve-Reviewed II: History, Perspectives. Boston: Boston Consulting Group.
• Carlson, J. G. (1973). Cubic Learning Curves: Precision Tool for Labor Estimating. Manufacturing Engineering and Management, 71(5), 22–25.
• Chung, S. (2001). The Learning Curve and the Yield Factor: The Case of Korea’s Semiconductor Industry. Applied Economics, 33(4), 473–483.
• Church, J. & Ware, R. (2000). Industrial Organization: A Strategic Approach. Boston: McGraw Hill.
• De Jong, J. R. (1957). The Effects of Increasing Skill on Cycle Time and Its Consequences for Time Standards. Ergonomics, 1(1,) 51–60.
• Dick, A. R. (1991). Learning by Doing and Dumping in the Semiconductor Industry. Journal of Law and Economics, 34(1), 133–159.
• Dinler, Z. (2019). Mikro Ekonomi, 29. Baskı, Bursa: Ekin Basım Yayın Dağıtım.
• Dudley, L. (1972). Learning and Productivity Change in Metal Products. The American Economic Review, 62(4), 662–669.
• Franceschini, F. & Galetto, M. (2002). Asymptotic Defectiveness of Manufacturing Plants: An Estimate Based on Process Learning. International Journal of Production Research, 40(3), 537–545.
• Goldemberg, J., Coelho, S. T., Nastari, P. M. & Lucon, O. (2004). Ethanol Learning Curve-The Brazilian Experience. Biomass and Bioenergy, 26(3), 301–304.
• Hartley, K. (1965). The Learning Curve and Its Application to the Aircraft Industry. The Journal of Industrial Economics, 13(2), 122–128.
• Jarmin, R. S. (1994). Learning by Doing and Competition in the Early Rayon Industry. The RAND Journal of Economics, 25(3), 441–454.
• Kalish, S. (1983). Monopolist Pricing with Dynamic Demand and Production Cost. Marketing Science, 2, 135-159.
• Karaöz, M. & Albeni, M. (2005). Dynamic Technological Learning Trends in Turkish Manufacturing Industries. Technological Forecasting and Social Change, 72(7), 866–885.
• Knecht, G. R. (1974). Costing Technological Growth and Generalized Learning Curves. Operations Research Quarterly, 25(3), 487–491.
• Krajewski, L. J., Malhotra, M. K. & Ritzman, L. (2015). Operations Management: Processes and Supply Chains. Essex: Pearson Education.
• Levy, F. K. (1965). Adaptation in the Production Process. Management Science, 11, 136–154.
• Lieberman, M. B. (1984). The Learning Curve and Pricing in the Chemical Processing Industries. The RAND Journal of Economics, 15(2), 213–228.
• Majd, S. & Pindyck, R. S. (1989). The Learning Curve and Optimal Production under Uncertainty. The RAND Journal of Economics, 20(3), 331-343.
• Nadeau, M., Kar, A., Roth, R. & Kirchain, R. (2010). A Dynamic Process-Based Cost Modeling Approach to Understand Learning Effects in Manufacturing. International Journal of Production Economics, 128(1), 223–234.
• Petrakis, E., Rasmusen, E. & Roy, S. (1997). The Learning Curve in a Competitive Industry. The RAND Journal of Economics, 28(2), 248-268.
• Pramongkit, P., Shawyun, T. & Sirinaovakul, B. (2002). Productivity Growth and Learning Potentials of Thai Industry. Technological Forecasting and Social Change, 69(1), 89–101.
• Salvatore, D. (2003). Microeconomics: Theory and Applications. New York: Oxford University Press.
• Sinclair, G., Klepper, S. & Cohen, W. (2000). What’s Experience Got to Do With it? Sources of Cost Reduction in a Large Specialty Chemicals Producer. Management Science, 46(1), 28–45.
• Spence, A. M. (1981). The Learning Curve and Competition. Bell Journal of Economics, 12, 49-70.
• Sultan, R. (1974). Pricing in the Electrical Oligopoly. Boston: Harvard University Press.
• Tan, W. & Elias, Y. (2000). Learning by Doing in Singapore Construction. Journal of Construction Research, 1(2), 151–158.
• Waldman, D. E. & Jensen, E. J. (2013). Industrial Organization: Theory and Practice. Boston: Pearson Education.
• Wright, T. P. (1936). Factors Affecting the Cost of Airplanes. Journal of the Aeronautical Sciences, 3, 122–128.
• Yelle, L. E. (1979). The Learning Curve: Historical Review and Comprehensive Survey. Decision Science, 10(2), 302–328.