Learning by doing and optimal factor demand

Dompere, Kofi Kissi; Nti, Kofi O.

doi:10.1016/0925-5273(91)90037-t

Cited by 9 publications

(4 citation statements)

References 13 publications

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“…Hundreds of articles consider various aspects of the learning curve. Learning curves have been considered from the perspective of: price (Chung, ), cost (Argote & Epple, ; Camm, Evans & Womer, ; Fauber, ; Waring, ), output (Lieberman, ; Yelle, ), yield (Chung, ; Gruber, ; Mody & Wheeler, ), labour required (Boucher, ; Dompere & Nti, ; Gerchak & Parlar, ; Liao & Noftsinger, ; Roser & Sundby, ; Wright, ; Yelle, ) and other inputs (Dorroh, Gulledge & Womer, ). The consensus is that cost – although suffering from variation in input prices – is the most promising variable.…”

Section: Learning and Experience Curves: Current State Of Knowledgementioning

confidence: 99%

Extracting Value from Learning Curves: Integrating Theory and Practice

Linton

Walsh

2013

Creat Innov Manage

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Learning curves are used as management metrics in many industrial settings. However, their apparent simplicity masks the tremendous number of changes and opportunities that are summarized by this apparently simple exponential relationship. Through exploration of these underlying opportunities, practitioners are able to better identify and exploit opportunities. By integrating learning curve theory to include design, supply chain and life cycle management to a framework illustrating the complex series of events that comprise the seemingly parsimonious learning curve, it is possible to better see how learning curves reduce cost, expand existing markets and create new markets. Illustrations are used to assist practitioners in taking economic advantage of the theoretical contributions offered in this framework.

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Section: Learning and Experience Curves: Current State Of Knowledgementioning

confidence: 99%

Extracting Value from Learning Curves: Integrating Theory and Practice

Linton

Walsh

2013

Creat Innov Manage

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“…required (Dompere and Nti, 1991) or other input (Dorroh et al, 1986). The use of a power model has been generally agreed on (1) (Smunt, 1986) to establish the rate of learning.…”

Section: Cost Forecast Of China's Photovoltaic Industrymentioning

confidence: 99%

“…Models have considered elapsed time (Gruber, ), number of units produced (Gruber, ) and investment (Lieberman, ) as independent variables. The corresponding dependent variables offered have been price (Chung, ), cost (Waring, ), output (Yelle, ), yield (Chung, ), labour required (Dompere and Nti, ) or other input (Dorroh et al., ). The use of a power model has been generally agreed on (1) (Smunt, ) to establish the rate of learning.…”

Section: Literature Reviewmentioning

confidence: 99%

Research on the cost forecast of China's photovoltaic industry

Wang

et al. 2014

R & D Management

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Global energy and environmental problems are increasing in severity. Countries worldwide are more concerned about and are paying greater attention to strengthening their energy‐saving and emissions‐reduction efforts, protecting the environment and promoting the development of new energy. Solar energy is becoming the mainstream of the global power industry because of its significant resources and low cost. This paper provides an overview of the current state‐of‐the‐art of photovoltaic electricity technology (‘photovoltaic’ or PV) in China and addresses its potential for future cost reductions. This paper analyses the relationship between current renewable energy costs and cumulative production, development and demonstration expenditures, and other institutional influences. The theoretical framework of a learning curve offers a complete methodology for examining the underlying capital cost trajectory when developing electricity cost estimates used in energy policy planning models. The cumulative production needed to achieve ‘break‐even’ (the point at which PV is competitive with conventional alternatives) is estimated for a range of learning curve parameter values. The social cost (pollution costs and value‐added tax considered) of PV is calculated, and the question of whether and how the ‘cost cap’ can be bridged is posed, the latter being the difference between what this cumulative production will cost and what it would cost if it could be produced at a currently competitive level. We also estimate how much PV could gain if the external costs (attributable to environmental and health damage) of energy were internalised, such as through an energy tax. We use the simulated results to provide suggestions for relevant PV industrial policymaking.

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“…Models consider elapsed time (Gruber, 1992;Towill, 1985), number of units produced (Gruber, 1992;Argote and Epple, 1990;Towill, 1985;Yelle, 1979) and investment (Lieberman, 1984) as independent variables. The corresponding dependent variables offered have been price (Chung, 2001), cost (Waring, 1991;Argote and Epple, 1990;Fauber, 1989;Camm et al, 1987), output (Yelle, 1979;Lieberman, 1984), yield (Chung, 2001;Gruber, 1994;Mody and Wheeler, 1987), labor required (Dompere and Nti, 1991;Gerchak and Parlar, 1990;Boucher, 1987;Roser and Sundby, 1985;Yelle, 1979;Liao and Noftsinger, 1977;Wright, 1936), or some other input (Dorroh et al, 1986). There has been a general agreement on the use of a power model (1) (Smunt, 1986a;Kantor and Zangwill, 1991) to establish the rate of learning.…”

Section: Current State Of Knowledgementioning

confidence: 99%

Integrating innovation and learning curve theory: an enabler for moving nanotechnologies and other emerging process technologies into production

Linton

Walsh

2004

R & D Management

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Process technology selection is biased against selection of emerging process technologies such as nanotechnologies, biotechnology and microtechnologies (MEMS), since these decisions are frequently based on assumptions that are only valid for mature sustaining process technologies. This is a great concern since emerging process technologies are drivers of economic growth, especially in developed economies. We consider the learning curve literature and integrate it with the literature on technological trajectories and innovation to develop a theory for modeling the learning curve for emerging process technologies.

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Learning by doing and optimal factor demand

Cited by 9 publications

References 13 publications

Extracting Value from Learning Curves: Integrating Theory and Practice

Extracting Value from Learning Curves: Integrating Theory and Practice

Research on the cost forecast of China's photovoltaic industry

Integrating innovation and learning curve theory: an enabler for moving nanotechnologies and other emerging process technologies into production

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