Skip to main content
SpringerLink
Log in

Organizational Learning Curves: An Overview

  • Chapter
  • First Online:
Organizational Learning

Abstract

“Learning curves” have been found in many organizations. As organizations produce more of a product, the unit cost of production typically decreases at a decreasing rate. A learning curve for the production of an advanced military jet built in the 1970s and 1980s is shown in Fig. 1.1. The number of direct labor hours required to assemble each jet aircraft is plotted on the vertical axis; the cumulative number of aircraft produced is plotted on the horizontal axis. As can be seen from Fig. 1.1, the number of direct labor hours required to assemble each aircraft decreased significantly as experience was gained in production, and the rate of decrease declined with rising cumulative output. This and related phenomena are referred to as learning curves, progress curves, experience curves, or learning by doing.

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

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 189.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 249.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 249.99
Price excludes VAT (USA)
  • Durable hardcover 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.

    The classic learning curve in Eq. (1.1), \( y=a{x}^{b}\), can be expressed as a production function. The dependent variable in Eq. (1.1) is labor hours per output \( \left(y=h/q\right)\). Equation (1.1) can be rewritten as \( q={a}^{-1}h{x}^{-b}\). Thus, the production function implicit in the conventional learning curve has a single input, labor hours (h), and a single measure of organizational experience—cumulative output (x). The conventional formulation also imposes the assumption of proportionality between output and labor hours. Thus, the conventional formulation of the learning curve is a special case of the more general production function approach.

  2. 2.

    The relationship between the progress ratio and the learning rate from Eq. (1.1) can be derived as follows:

    Let y 1  =  unit cost of producing unit x, y 2  =  unit cost of producing unit 2x. Then

    $$ {y}_{1}=a{x}^{b},{y}_{2}=a{\left(2x\right)}^{b},\rm\rm{and}\rm{y}_{2}/{y}_{1}={2}^{b}.$$

References

  • Adler, P. S., & Clark, K. B. (1991). Behind the learning curve: A sketch of the learning process. Management Science, 37, 267–281.

    Google Scholar 

  • Alchian, A. (1963). Reliability of progress curves in airframe production. Econometrica, 31, 679–693.

    Google Scholar 

  • Argote, L. (1993). Group and organizational learning curves: Individual, system and environmental components. British Journal of Social Psychology, 32, 31–51.

    Google Scholar 

  • Argote, L., Beckman, S. L., & Epple, D. (1990). The persistence and transfer of learning in industrial settings. Management Science, 36, 140–154.

    Google Scholar 

  • Argote, L., & Darr, E. D. (2000). Repositories of knowledge in franchise organizations: Individual, structural and technological. In G. Dosi, R. Nelson, & S. Winter (Eds.), Nature and dynamics of organizational capabilities (pp. 51–68). Oxford: Oxford University Press.

    Google Scholar 

  • Argote, L., Denomme, C., & Fuchs, E. (2011). Organizational learning across boundaries: The effect of geographic distribution on organizational learning and knowledge transfer. In M. Easterby-Smith & M. Lyles (Eds.), Handbook of organizational learning and knowledge management (pp. 656–684). Chester, UK: Wiley.

    Google Scholar 

  • Argote, L., & Epple, D. (1990). Learning curves in manufacturing. Science, 247, 920–924.

    Google Scholar 

  • Argote, L., Epple, D., Rao, R. D., & Murphy, K. (1997). The acquisition and depreciation of knowledge in a manufacturing organization: Turnover and plant productivity. Working paper, Graduate School of Industrial Administration, Carnegie Mellon University.

    Google Scholar 

  • Argote, L., & Ingram, P. (2000). Knowledge transfer: A basis for competitive advantage in firms. Organizational Behavior and Human Decision Processes, 82(1), 150–169.

    Google Scholar 

  • Argyris, C. (1990). Overcoming organizational defenses: Facilitating organizational learning. Boston: Allyn and Bacon.

    Google Scholar 

  • Arrow, K. J. (1962). The economic implications of learning by doing. Review of Economic Studies, 29, 155–173.

    Google Scholar 

  • Asher, H. (1956). Cost-quantity relationships in the air-frame industry. Santa Monica, CA: Rand Corporation.

    Google Scholar 

  • Bahk, B., & Gort, M. (1993). Decomposing learning by doing in new plants. Journal of Political Economy, 101, 561–582.

    Google Scholar 

  • Baldwin, R., & Krugman, P. (1988). Industrial policy and international competition in wide-bodied jet aircraft. In R. Baldwin (Ed.), Trade policy and empirical analysis (pp. 45–71). Chicago: University of Chicago Press.

    Google Scholar 

  • Baloff, N. (1966). Startups in machine intensive production systems. Journal of Industrial Engineering, 17, 25–32.

    Google Scholar 

  • Baloff, N. (1971). Extension of the learning curve−some empirical results. Operations Research Quarterly, 22, 329–340.

    Google Scholar 

  • Barkai, H., & Levhari, D. (1973). The impact of experience on kibbutz farming. Review of Economics and Statistics, 55, 56–63.

    Google Scholar 

  • Barney, J. B. (1991). Firm resources and sustained competitive advantage. Journal of Management, 17, 99–120.

    Google Scholar 

  • Baum, J. A. C., & Greve, H. R. (Eds.). (2001). Multiunit organizations and multiunit strategy: Advances in strategic management (Vol. 18). Oxford, UK: Elsevier.

    Google Scholar 

  • Baum, J. A. C., & Ingram, P. (1998). Survival-enhancing learning in the Manhattan hotel industry, 1898–1980. Management Science, 44, 996–1016.

    Google Scholar 

  • Benkard, C. L. (2000). Learning and forgetting: The dynamics of aircraft production. American Economic Review, 90(4), 1034–1054.

    Google Scholar 

  • Benkard, C. L. (2004). A dynamic analysis of the market for wide-bodied commercial aircraft. Review of Economic Studies, 71, 581–611.

    Google Scholar 

  • Besanko, D., Doraszelski, W., Kryukov, Y., & Satterthwaite, M. (2010). Learning-by-doing, organizational forgetting, and industry dynamics. Econometrica, 78(2), 453–508.

    Google Scholar 

  • Blumenstein, R. (1997, August 4). GM is building plants in developing nations to woo new markets. The Wall Street Journal, pp. A1, A4.

    Google Scholar 

  • Borgatti, S. P., & Cross, R. (2003). A relational view of information seeking and learning in social networks. Management Science, 49(4), 432–445.

    Google Scholar 

  • Bresman, H. (2010). External learning activities and team performance: A multimethod field study. Organization Science, 21, 81–96.

    Google Scholar 

  • Carlile, P. (2004). Transferring, translating and transforming: An integrative framework for managing knowledge across boundaries. Organization Science, 15, 555–568.

    Google Scholar 

  • Chew, W. B., Bresnahan, T. F., & Clark, K. B. (1990). Measurement, coordination and learning in a multi-plant network. In R. S. Kaplan (Ed.), Measures for manufacturing excellence (pp. 129–162). Boston: Harvard Business Press.

    Google Scholar 

  • Conley, P. (1970). Experience curves as a planning tool. IEEE Spectrum, 7, 63–68.

    Google Scholar 

  • Conway, R., & Schultz, J. (1959). The manufacturing progress function. Journal of Industrial Engineering, 10, 39–53.

    Google Scholar 

  • Darr, E., Argote, L., & Epple, D. (1995). The acquisition, transfer and depreciation of knowledge in service organizations: Productivity in franchises. Management Science, 41, 1750–1762.

    Google Scholar 

  • Dasgupta, P., & Stiglitz, J. (1988). Learning by doing, market structure and industrial and trade policies. Oxford Economic Papers, 40, 246–268.

    Google Scholar 

  • Davenport, T., & Prusak, L. (1998). Working knowledge: How organizations manage what they know. Boston, MA: Harvard Business School Press.

    Google Scholar 

  • Delaney, P. F., Reder, L. M., Staszewski, J. J., & Ritter, F. E. (1998). The strategy-specific nature of improvement: The power law applies by strategy within task. Psychological Science, 9, 1–7.

    Google Scholar 

  • Dorroh, J. R., Gulledge, T. R., & Womer, N. K. (1994). Investment in knowledge: A generalization of learning by experience. Management Science, 40, 947–958.

    Google Scholar 

  • Duncan, R., & Weiss, A. (1979). Organizational learning: Implications for organizational design. Research in Organizational Behavior, 1, 75–123.

    Google Scholar 

  • Dutton, J. M., & Thomas, A. (1984). Treating progress functions as a managerial opportunity. Academy of Management Review, 9, 235–247.

    Google Scholar 

  • Dutton, J. M., Thomas, A., & Butler, J. E. (1984). The history of progress functions as a managerial technology. Business History Review, 58, 204–233.

    Google Scholar 

  • Easterby-Smith, M. (1997). Disciplines of organizational learning: Contributions and critiques. Human Relations, 50, 1085–1113.

    Google Scholar 

  • Easterby-Smith, M., & Lyles, M. (Eds.). (2011). Handbook of organizational learning and knowledge management. Chichester, UK: Wiley.

    Google Scholar 

  • Ebbinghaus, H. (1964). Memory: A contribution to experimental psychology. (H. A. Ruger & C. E. Bussenius, Trans.). New York: Dover (Original work published 1885).

    Google Scholar 

  • Epple, D., Argote, L., & Devadas, R. (1991). Organizational learning curves: A method for investigating intra-plant transfer of knowledge acquired through learning by doing. Organization Science, 2, 58–70.

    Google Scholar 

  • Epple, D., Argote, L., & Murphy, K. (1996). An empirical investigation of the micro structure of knowledge acquisition and transfer through learning by doing. Operations Research, 44, 77–86.

    Google Scholar 

  • Fang, C. (2011). Organizational learning as credit assignment: A model and two experiments. Organization Science. doi:10.1287/orsc.1110.0710.

    Google Scholar 

  • Fiol, C. M., & Lyles, M. A. (1985). Organizational learning. Academy of Management Review, 10, 803–813.

    Google Scholar 

  • Fu, W., & Anderson, J. (2006). From recurrent choice to skilled learning: A reinforcement learning model. Journal of Experimental Psychology: General, 135(2), 184–206.

    Google Scholar 

  • Galbraith, C. S. (1990). Transferring core manufacturing technologies in high technology firms. California Management Review, 32(4), 56–70.

    Google Scholar 

  • Garvin, D. A. (2000). Learning in action: A guide to putting the learning organization to work. Boston, MA: Harvard Business School Press.

    Google Scholar 

  • Ghemawat, P. (1985). Building strategy on the experience curve. Harvard Business Review, 63(2), 143–149.

    Google Scholar 

  • Ghemawat, P., & Spence, A. M. (1985). Learning curve spillovers and market performance. The Quarterly Journal of Economics, 100(Supplement), 839–852.

    Google Scholar 

  • Gherardi, S. (2006). Organizational knowledge: The texture of workplace learning. Malden, MA: Blackwell.

    Google Scholar 

  • Goodman, P. S., & Darr, E. (1996). Exchanging best practices through computer-aided systems. Academy of Management Executive, 10(2), 7–18.

    Google Scholar 

  • Greenberg, L. (1971). Why the mine injury picture is out of focus. Mining Engineering, 23, 51–53.

    Google Scholar 

  • Greve, H. (2003). Organizational learning from performance feedback. Cambridge, UK: Cambridge University Press.

    Google Scholar 

  • Gruber, H. (1994). The yield factor and the learning curve in semiconductor production. Applied Economics, 26, 837–843.

    Google Scholar 

  • Gruenspecht, H. (1988). Dumping and dynamic competition. Journal of International Economics, 12, 225–248.

    Google Scholar 

  • Guetzkow, H., & Simon, H. A. (1955). The impact of certain communication nets upon organization and performance in task-oriented groups. Management Science, 1, 233–250.

    Google Scholar 

  • Haleblian, J., & Finkelstein, S. (1999). The influence of organization acquisition experience on acquisition performance: A behavioral learning theory perspective. Administrative Science Quarterly, 44, 29–56.

    Google Scholar 

  • Hansen, M. (1999). The search transfer problem: The role of weak ties in sharing knowledge across organization subunits. Administrative Science Quarterly, 44, 82–111.

    Google Scholar 

  • Haunschild, P. R., & Miner, A. S. (1997). Modes of interorganizational imitation: The effects of outcome salience and uncertainty. Administrative Science Quarterly, 42, 472–500.

    Google Scholar 

  • Hayes, R. H., & Clark, K. B. (1986). Why some factories are more productive than others. Harvard Business Review, 64(5), 66–73.

    Google Scholar 

  • Hayes, R. H., & Wheelwright, S. C. (1984). Restoring our competitive edge: Competing through manufacturing. New York: Wiley.

    Google Scholar 

  • Hayward, M. L. A. (2002). When do firms learn from their acquisition experience? Evidence from 1990–1995. Strategic Management Journal, 23(1), 21–40.

    Google Scholar 

  • Henderson, B. D. (1984). The application and misapplication of the experience curve. The Journal of Business Strategy, 4(3), 3–9.

    Google Scholar 

  • Henderson, R., & Cockburn, I. (1994). Measuring competence? Exploring firm effects in pharmaceutical research. Strategic Management Journal, 15, 63–84.

    Google Scholar 

  • Hilgard, E. R., & Bower, G. H. (1975). Theories of learning (4th ed.). Englewood Cliffs, NJ: Prentice-Hall.

    Google Scholar 

  • Hirsch, W. Z. (1952). Manufacturing progress functions. Review of Economics and Statistics, 34, 143–155.

    Google Scholar 

  • Hirschmann, W. B. (1964). Profit from the learning curve. Harvard Business Review, 42(1), 125–139.

    Google Scholar 

  • Houston, J. P. (1986). Fundamentals of learning and memory (3rd ed.). New York: Harcourt Brace Jovanovich.

    Google Scholar 

  • Huber, G. P. (1991). Organizational learning: The contributing processes and the literatures. Organization Science, 2, 88–115.

    Google Scholar 

  • Huberman, B. A. (2001). The dynamics of organizational learning. Computational & Mathematical Organization Theory, 7, 145–153.

    Google Scholar 

  • Ingram, P. (2002). Intraorganizational learning. In J. A. C. Baum (Ed.), Blackwell Companion to Organizations (pp. 642–663). Oxford: Blackwell Publishers.

    Google Scholar 

  • Ingram, P., & Baum, J. A. C. (1997). Opportunity and constraint: Organizations’ learning from the operating and competitive experience of industries. Strategic Management Journal, 18, 75–98.

    Google Scholar 

  • Jarmin, R. S. (1994). Learning by doing and competition in the early rayon industry. The Rand Journal of Economics, 25, 441–454.

    Google Scholar 

  • Joskow, P. L., & Rozanski, G. A. (1979). The effects of learning by doing on nuclear plant operating reliability. Review of Economics and Statistics, 61, 161–168.

    Google Scholar 

  • Jucker, J. V. (1977). The transfer of domestic-market production to a foreign site. AIIE Transactions, 9, 321–329.

    Google Scholar 

  • Kellogg, R. (2011). Learning by drilling: Inter-firm learning and relationship persistence in the Texas oilpatch. Quarterly Journal of Economics, 126(4), 1961–2004.

    Google Scholar 

  • Kelsey, S. F., Mullin, S. M., Detre, K. M., Mitchell, H., Cowley, M. J., Gruentzig, A. R., & Kent, K. M. (1984). Effect of investigator experience on percutaneous transluminal coronary angioplasty. American Journal of Cardiology, 53, 56C–64C.

    Google Scholar 

  • Kiechel, W. (1981). The decline of the experience curve. Fortune, 104(7), 139–146.

    Google Scholar 

  • Kim, Y., Krishnan, R., & Argote, L. (2012). The learning curve of IT knowledge workers in a computing call center. Information Systems Research. doi:isre.1110.0401.

  • Kimble, G. A. (1961). Hilgard and Marquis’ conditioning and learning. New York: Appleton-Century-Crofts.

    Google Scholar 

  • Kozlowski, S. W. J., Chao, G. T., & Jensen, J. M. (2010). Building an infrastructure for organizational learning: A multilevel approach. In S. W. J. Kozlowski & E. Salas (Eds.), Learning, training and development in organizations (pp. 361–400). New York: Rutledge Academic.

    Google Scholar 

  • Krugman, P. A. (1991). Myths and realities of U.S. competitiveness. Science, 254, 811–815.

    Google Scholar 

  • Lapré, M. A., & Nembhard, I. M. (2010). Inside the organizational learning curve: Understanding the organizational learning process. Foundations and Trends in Technology, Information, and Operations Management, 4(1), 1–103.

    Google Scholar 

  • Leavitt, H. J. (1951). Some effects of certain communication patterns on group performance. Journal of Abnormal and Social Psychology, 46, 38–50.

    Google Scholar 

  • Lester, R. K., & McCabe, M. J. (1993). The effect of industrial structure on learning by doing in nuclear power plant operation. The Rand Journal of Economics, 24, 418–438.

    Google Scholar 

  • Levitt, B., & March, J. G. (1988). Organizational learning. Annual Review of Sociology, 14, 319–340.

    Google Scholar 

  • Levy, F. K. (1965). Adaptation in the production process. Management Science, 11(6), B136–B154.

    Google Scholar 

  • Lieberman, M. B. (1984). The learning curve and pricing in the chemical processing industries. The Rand Journal of Economics, 15, 213–228.

    Google Scholar 

  • Lieberman, M. B. (1987). The learning curve, diffusion, and competitive strategy. Strategic Management Journal, 8, 441–452.

    Google Scholar 

  • Lippman, S. A., & Rumelt, R. P. (1982). Uncertain imitability: An analysis of interfirm differences in efficiency under competition. The Rand Journal of Economics, 13, 418–438.

    Google Scholar 

  • Lipshitz, R., Friedman, V. J., & Popper, M. (2007). Demystifying organizational learning. Thousand Oaks, CA: Sage.

    Google Scholar 

  • Lucas, R. E. (1993). Making a miracle. Econometrica, 61, 251–272.

    Google Scholar 

  • March, J. G. (2010). The ambiguities of experiences. Ithaca, NY: Cornell University Press.

    Google Scholar 

  • Mayer, K., & Argyres, N. S. (2004). Learning to contract: Evidence from the personal computer industry. Organization Science, 15(4), 394–410.

    Google Scholar 

  • Mazur, J. E., & Hastie, R. (1978). Learning as accumulation: A reexamination of the learning curve. Psychological Bulletin, 85, 1256–1274.

    Google Scholar 

  • Minabe, S. (1986). Japanese competitiveness and Japanese management. Science, 233, 301–304.

    Google Scholar 

  • Miner, A. S., & Anderson, P. (1999). Industry and population-level learning: Organizational, interorganizational, and collaborative learning processes. In A. S. Miner & P. Anderson (Eds.), Population-level learning and organizational change. Advances in Strategic Management, 16, 1–30. Stamford, CT: JAI Press.

    Google Scholar 

  • Miner, A. S., & Haunschild, P. R. (1995). Population-level learning. Research in Organizational Behavior, 17, 115–166.

    Google Scholar 

  • Miner, A. S., & Mezias, S. J. (1996). Ugly duckling no more: Pasts and futures of organizational learning research. Organization Science, 7, 88–99.

    Google Scholar 

  • Montgomery, C. A. (Ed.). (1995). Resource-based and evolutionary theories of the firm: Towards a synthesis. Norwell, MA: Kluwer.

    Google Scholar 

  • Mukhopadhyay, T., Singh, P. V., & Kim, S. H. (2011). Learning curves of agents with diverse skills in information technology-enabled physician referral systems. Information Systems Research, 22, 586–605.

    Google Scholar 

  • Muth, J. F. (1986). Search theory and the manufacturing progress function. Management Science, 32, 948–962.

    Google Scholar 

  • Nelson, R. R. (1991). Why do firms differ, and how does it matter? Strategic Management Journal, 12, 61–74.

    Google Scholar 

  • Newell, A., & Rosenbloom, P. S. (1981). Mechanisms of skill acquisition and the law of practice. In J. R. Anderson (Ed.), Cognitive skills and their acquisition (pp. 1–55). Hillsdale, NJ: Lawrence Erlbaum.

    Google Scholar 

  • Nonaka, I., & Takeuchi, H. (1995). The knowledge-creating company. New York: Oxford University Press.

    Google Scholar 

  • Pisano, G. P., Bohmer, R. M. J., & Edmondson, A. C. (2001). Organizational differences in rates of learning: Evidence from the adoption of minimally invasive cardiac surgery. Management Science, 47(6), 752–768.

    Google Scholar 

  • Powell, W. W., Koput, K. W., & Smith-Doerr, L. (1996). Interorganizational collaboration and the locus of innovation: Networks of learning in biotechnology. Administrative Science Quarterly, 41, 116–145.

    Google Scholar 

  • Prahalad, C. K., & Hamel, G. (1990). The core competence of the corporation. Harvard Business Review, 68(3), 79–91.

    Google Scholar 

  • Preston, L., & Keachie, E. (1964). Cost functions and progress functions: An integration. American Economic Review, 54(2), 100–107.

    Google Scholar 

  • Rapping, L. (1965). Learning and World War II production functions. Review of Economics and Statistics, 47, 81–86.

    Google Scholar 

  • Reagans, R., Argote, L., & Brooks, D. (2005). Individual experience and experience working together: Predicting learning rates from knowing what to do and knowing who knows what. Management Science, 51, 869–881.

    Google Scholar 

  • Reagans, R., & McEvily, B. (2003). Network structure and knowledge transfer: The effects of cohesion and range. Administrative Science Quarterly, 48, 240–267.

    Google Scholar 

  • Roberts, P. C. (1983). A theory of the learning process. Journal of Operations Research, 34, 71–79.

    Google Scholar 

  • Searle, A. D., & Gody, C. S. (1945). Productivity changes in selected wartime shipbuilding programs. Monthly Labor Review, 61, 1132–1147.

    Google Scholar 

  • Senge, P. M. (1990). The fifth discipline: The art and practice of the learning organization. New York: Currency Doubleday.

    Google Scholar 

  • Sheshinski, E. (1967). Tests of the learning by doing hypothesis. Review of Economics and Statistics, 49, 568–578.

    Google Scholar 

  • Shure, G. H., Rogers, M. S., Larsen, I. M., & Tassone, J. (1962). Group planning and task effectiveness. Sociometry, 25(3), 263–383.

    Google Scholar 

  • 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, 28–45.

    Google Scholar 

  • Singh, P. V., Ton, Y., & Youn, N. (2011). A hidden Markov model of developer learning dynamics in open source software projects. Information Systems Research, 22, 790–807.

    Google Scholar 

  • Solow, R. (1957). Technical change and the aggregate production function. Review of Economics and Statistics, 39, 312–320.

    Google Scholar 

  • Spence, A. M. (1981). The learning curve and competition. Bell Journal of Economics, 12, 49–70.

    Google Scholar 

  • Stein, E. W., & Zwass, V. (1995). Actualizing organizational memory with information systems. Information Systems Research, 6, 85–117.

    Google Scholar 

  • A survey of manufacturing: Meet the global factory (1998, June 20). The Economist, pp. M1–M18.

    Google Scholar 

  • Szulanski, G. (1996). Exploring internal stickiness: Impediments to the transfer of best practice within the firm. Strategic Management Journal, 17, 27–43.

    Google Scholar 

  • Teece, D. J. (1998). Capturing value from knowledge assets: The new economy, markets for know-how and intangible assets. California Management Review, 40(3), 55–79.

    Google Scholar 

  • The TriStar’s trail of red ink (1980, July 28). Business Week, pp. 88, 90.

    Google Scholar 

  • Thorndike, E. L. (1898). Animal intelligence: An experimental study of the associative processes in animals. The Psychological Review: Series of Monograph Supplements, 2, 1–109.

    Google Scholar 

  • Thurstone, L. L. (1919). The learning curve equation. Psychological Monographs, 26, 1–51.

    Google Scholar 

  • Tsai, W. (2002). Social structure of “coopetition” within a multiunit organization: Coordination, competition, and intraorganizational knowledge sharing. Organization Science, 13(2), 179–190.

    Google Scholar 

  • Vanneste, B. S., & Puranam, P. (2010). Repeated interactions and contractual detail: Identifying the learning effect. Organization Science, 21, 186–201.

    Google Scholar 

  • Walsh, J. P. (1995). Managerial and organizational cognition: Notes from a trip down memory lane. Organization Science, 6, 280–322.

    Google Scholar 

  • Wingfield, A. (1979). Human learning and memory: An introduction. New York: Harper & Row.

    Google Scholar 

  • Winter, S. G. (1995). Four Rs of profitability: Rents, resources, routines and replication. In C. A. Montgomery (Ed.), Resource based and evolutionary theories of the firm. Norwell, MA: Kluwer.

    Google Scholar 

  • Womer, N. K. (1979). Learning curves, production rate, and program costs. Management Science, 25, 312–319.

    Google Scholar 

  • Womer, N. K. (1984). Estimating learning curves from aggregate monthly data. Management Science, 30, 982–992.

    Google Scholar 

  • Wright, T. P. (1936). Factors affecting the costs of airplanes. Journal of the Aeronautical Sciences, 3, 122–128.

    Google Scholar 

  • Yelle, L. E. (1979). The learning curve: Historical review and comprehensive survey. Decision Sciences, 10, 302–328.

    Google Scholar 

  • Young, A. (1991). Learning by doing and the dynamic effects of international trade. The Quarterly Journal of Economics, 106, 369–405.

    Google Scholar 

  • Zander, U., & Kogut, B. (1995). Knowledge and the speed of the transfer and imitation of organizational capabilities: An empirical test. Organization Science, 6, 76–92.

    Google Scholar 

  • Zollo, M., & Reuer, J. (2010). Experience spillovers across corporate development activities. Organization Science, 21, 1195–1212.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Tepper School of Business, Carnegie Mellon University, Schenley Park, Pittsburgh, Pennsylvania, USA

    Linda Argote

Authors
  1. Linda Argote
    View author publications

    You can also search for this author in PubMed Google Scholar

Rights and permissions

Reprints and permissions

Copyright information

© 2013 Springer Science+Business Media New York

About this chapter

Cite this chapter

Argote, L. (2013). Organizational Learning Curves: An Overview. In: Organizational Learning. Springer, Boston, MA. https://doi.org/10.1007/978-1-4614-5251-5_1

Download citation

Publish with us

Policies and ethics

Search

Navigation