Learning Curve Theory Research Articles

Knowledge acquisition and transfer among engineers: effects of network structure

AbstractThis paper examines the association between the structure of formal intra‐firm networks and productivity. We focus on two network structure components—department centralization and centrality, within a four department engineering organization. Centrality indicates the number of connections between one department and others within the organization, while centralization captures how much of those connections are concentrated among the workers within the department. Both of these represent specific managerial decisions in a formal network structure. We use learning curve theory to measure accumulated organizational knowledge, its depreciation and intra‐firm transfers. We hypothesize that the departments are more productive, experience less depreciation and realize more knowledge transfer if they have more intra‐firm connections among more workers. The findings suggest a significant yet moderate association between the formal network structure and productivity. Copyright © 2008 John Wiley & Sons, Ltd.

Putting the learning curve in context

In implementation of change, people learn new ways of doing things, develop new skills, and adopt new organizational routines. This paper applies learning curve theory to implementation by developing a system dynamics model that includes two extensions to classic learning curve theory. First, the model includes a required output level for the individual. Second, the model includes a budget constraint on time that forces a choice between an old and a new way to achieve the output. Doing work the new way builds experience, increasing productivity and thus favoring continued use of the new skill, but model analysis demonstrates that this reinforcing process works to favor the new skill only at relatively high levels of productivity. Otherwise, the same process is a vicious cycle, driving out the new skill. The model exhibits a mode of behavior in which learning begins and then stalls and another mode in which the new skill becomes the preferred one. The paper identifies the tipping point between these two modes and characterizes the transition problem: Learning by doing is a dynamic process, a transition from use of an old way to a new way that requires accumulating experience beyond a threshold.

Learning - the only way to improve health-care outcomes

Attempts to improve health care have generally failed. Systems analysis urges addressing processes, such as learning, rather than isolated parts of a system. We apply learning curve theory to health care and then explicate the process of learning. Specific recommendations involve how we learn (and unlearn), who should learn, and what should be learned.

Independence, Low Balling, and Learning Effects

Independent auditors serve as gatekeepers of public securities markets, but ongoing competition among audit firms could harm auditors’ independence. For instance, a Green Paper of the European Union finds that especially audits of large and prestigious clients are hard-fought in terms of price competition. Major concerns are related to a pricing behavior called low balling. Here, the auditor sets the first period’s fee below the audit costs-incurring a loss for the initial audit- in order to win the client. However, as a quasimonopoly emerges for the incumbent auditor, he expects to offset this loss in the future. Mainly, this offset occurs due to reduced audit costs in subsequent periods. Recent management publications highlight that learning effects influence the cost behavior over time in two ways. On the one hand, cost reductions emerge from experience due to performing jobs repeatedly. Thus, learning is supposed to be an important strategic factor in lowautomation industries, like auditing. On the other hand, learning effects can be fostered by investments in learning, i.e., learning is manageable. Bundling non-audit services, like risk advisory- or performance measurement-related assurance services, with audits could be interpreted as audit-quality improving investments in learning about a client’s business. Accordingly, the goal of our paper is to analyze how learning effects according to the theory of learning curves affect competition on the audit market and thus the low-balling problem. Our analysis proceeds in several steps: In the first step, we model-endogenously identify conditions for the existence of price competition in audit markets. This step of analysis is important, because in most low-balling models competition is assumed to exist, although empirical evidence is mixed. In the second step, we analyze how different types of learning influence fee setting over time. Here, we assume auditors to have identical learning rates. This means competition in a given segment is considered, e.g., between Big-4 auditors or between National Majors. In the third step, we regard auditors with different learning abilities. Thus, auditors of different size -measured in number of clients- occur. In this step we capture the fact that empirically size is an important competition factor. Our results give hints to regulators under which conditions low balling might be a threat to auditor independence. Further, some recently introduced regulations, which aim at improving auditor independence, can be evaluated using the framework of our analysis.

Cost Accounting Implications of Surgical Learning in the DRG Era — Data Evidence from a German Hospital

On January 1st 2004, Germany introduced a prospective payment system for the reimbursement of almost all inpatient hospital cases. The new system, which is based on Diagnosis Related Groups (DRGs), is now mandatory for all hospitals that treat patients insured under Germany's statutory health insurance system (GKV). Although most German hospitals are currently exerting great efforts to calculate their individual DRG-costs, concerns have been raised whether such a system of administered fixed prices will be able to cope with medical innovation or quickly become obsolete. To gain insights into this question, an analysis of the dynamic properties of medical process innovations and their possible impact on the DRG system which is based on actual German data seems clearly merited. For two important medical innovations of the last two decades, a new method of knee replacement surgery and minimally invasive gall bladder removal (laparoscopic cholecystectomy), we empirically explore the question of whether the important cost driver "procedure time" displays a learning effect that accords with classical learning curve theory. Our principal results suggest that for these two high-cost, high-volume procedures, individual and organizational learning does indeed take place in the operating room. Based on these empirical results, we discuss our findings' implications for hospital cost accounting in the era of DRGs.

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

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.

Does Learning Matter for Knee Replacement Surgeries? Data Evidence from a German Hospital

In 2003, Germany will be the first country in the world to adopt a fully prospective payment system for the reimbursement of all inpatient hospital services. To face the increasing competition, hospitals can pursue either a specialization or a cost and quality leadership strategy. It stands to reason that organizational and individual learning will play an important role for both strategies. This paper raises the question, whether results from traditional learning curve theory can be applied to surgical procedures despite the latter's heterogeneity. We develop a theoretical model of surgical learning and test it using detailed operating room data from the first 601 total knee replacement surgeries of a small German hospital between 1994–2000. Our results suggest that classical learning curve theory can indeed be applied to this high cost high volume procedure.

Composition laws for learning curves of industrial manufacturing processes

The theory of learning curves is widely investigated in many fields related to production planning, quality improvement and cost analysis. Many different approaches to describe the learning mechanism of a process are reported in the academic literature. The aim is to analyse the behaviour of complex systems composed of a network of elementary processes whose learning curve is known. Composition laws of two basic aggregation structures, series and parallel, are discussed and analysed. The effects of these composition laws are shown in a series of practical examples.

Learning curves in health care.

This article explores the uses of learning curve theory in medicine. Though effective application of learning curve theory in health care can result in higher quality and lower cost, it is seldom methodically applied in clinical practice. Fundamental changes are necessary in the corporate culture of medicine in order to capitalize maximally on the benefits of learning.

Using a learning curve approach to reduce laboratory errors

Hospital laboratories have error rates that are too high and in some cases may be responsible for adverse patient treatment. This paper introduces reliability growth management (RGM), which is based on learning curve theory, as a method to improve laboratory error rates. RGM is widely used in the defense and automotive industry to solve problems when resources are limited and knowledge about the product and/or process is incomplete. An example of RGM, which was used to improve the reliability of instrument assay systems in the medical diagnostics industry is presented. RGM is a closed-loop process that entails creating a goal and event model, classifying events with failure review and corrective action system (FRACAS), tracking progress and predicting completion with Duane analysis. Results achieved by RGM were far better than those obtained by previously used methods. RGM techniques can be transferred to hospital laboratories to reduce laboratory error rates. The advantages of RGM compared to other quality initiatives such as ISO 9000 and Six Sigma are discussed.

Improving continuing medical education for surgical techniques: applying the lessons learned in the first decade of minimal access surgery.

To examine the first decade of experience with minimal access surgery, with particular attention to issues of training surgeons already in practice, and to provide a set of recommendations to improve technical training for surgeons in practice. Concerns about the adequacy of training in new techniques for practicing surgeons began almost immediately after the introduction of laparoscopic cholecystectomy. The concern was restated throughout the following decade with seemingly little progress in addressing it. A preliminary search of the medical literature revealed no systematic review of continuing medical education for technical skills. The search was broadened to include educational, medical, and psychological databases in four general areas: surgical training curricula, continuing medical education, learning curve, and general motor skills theory. The introduction and the evolution of minimal access surgery have helped to focus attention on technical skills training. The experience in the first decade has provided evidence that surgical skills training shares many characteristics with general motor skills training, thus suggesting several ways of improving continuing medical education in technical skills. The educational effectiveness of the short-course type of continuing medical education currently offered for training in new surgical techniques should be established, or this type of training should be abandoned. At present, short courses offer a means of introducing technical innovation, and so recommendations for improving the educational effectiveness of the short-course format are offered. These recommendations are followed by suggestions for research.

Exponential or polynomial learning Curves? - case-based studies

Learning curves exhibit a diversity of behaviors such as phase transition. However, the understanding of learning curves is still extremely limited, and existing theories can give the impression that without empirical studies (e.g., cross validation), one can probably do nothing more than qualitative interpretations. In this note, we propose a theory of learning curves based on the idea of reducing learning problems to hypothesis-testing ones. This theory provides a simple approach that is potentially useful for predicting and interpreting (a diversity of) learning curve behaviors qualitatively and quantitatively, and it applies to finite training sample size and finite learning machine and for learning situations not necessarily within the Bayesian framework. We illustrate the results by examining some exponential learning curve behaviors observed in Cohn and Tesauro (1992)'s experiment.

Relearning the Learning Curve: A Review of the Derivation and Applications of Learning-Curve Theory

Many contemporary reference works that address learning-curve theory incorrectly apply the basic equation established by Dr. T.P. Wright in 1936 incorrectly. The result is that estimates based on these texts overstate project time requirements by as much as 30%! By means of a worked example using recent data, this paper redevelops the theory from first principles. Interested readers may use the step-by-step method described within to establish the correct rate of learning applicable to their own organizations, thereby improving their productivity.

Incorporating the impact of learning in assessing the effectiveness of cellular manufacturing

Previous studies suggest that despite their intuitive appeal, cellular manufacturing systems are only effective in a batch production environment under a limited set of conditions. However, these studies have not taken into account the potential for productivity improvements unique to shops organized around product and work groups. Improvements that yield processing time reductions and rapid movement down the learning curve may offset the limited flexibility that typically compromises the performance of cellular shops. This paper demonstrates that if a cellular shop can yield even marginally greater reductions in processing times than a job shop, it can outperform the job shop under conditions previously thought to be unfavourable to a cellular shop. Learning curve theory is used to show that this can be achieved at modest levels of output and also under conditions not typically associated with cellular shop configurations.

The impact of learning rate and constraints on production line performance

Learning curve theory has been an important consideration for capacity planning and bid preparation since the 1940's. Constraint theory is a relatively new approach to managing manufacturing systems. This paper examines the implications each of these theories has for the other. Several important relationships are identified using a deterministic simulation of a simple production line which is influenced by learning and the presence of a system constraint. The rate of improvement of several measures of system performance follows the learning rate, but because of the role played by the constraint, other measures of performance actually get worse.

Estimating the effects of parameter variability on learning curve model predictions

The learning curve concept has proven to be a valuable management tool. However, regardless of which learning curve model is used, uncertainty is inherent in the forecast due to the empirical nature of learning curve theory and complications with establishing model parameters. Such variability is often ignored but can greatly affect the reliability of the model's predictions. Thus, as a means of approximating the effects of such uncertainty on model predictions, this paper proposes an analytical stochastic approach to estimating the precision of learning curve forecasts and provides an illustration of the technique with actual product cost data. The example shows that this analytical stochastic approach can provide accurate cost predictions with reliable prediction interval estimates.

Statistical Theory of Learning Curves under Entropic Loss Criterion

The present paper elucidates a universal property of learning curves, which shows how the generalization error, training error, and the complexity of the underlying stochastic machine are related and how the behavior of a stochastic machine is improved as the number of training examples increases. The error is measured by the entropic loss. It is proved that the generalization error converges to H0, the entropy of the conditional distribution of the true machine, as H0 + m*/(2t), while the training error converges as H0 - m*/(2t), where t is the number of examples and m* shows the complexity of the network. When the model is faithful, implying that the true machine is in the model, m* is reduced to m, the number of modifiable parameters. This is a universal law because it holds for any regular machine irrespective of its structure under the maximum likelihood estimator. Similar relations are obtained for the Bayes and Gibbs learning algorithms. These learning curves show the relation among the accuracy of learning, the complexity of a model, and the number of training examples.

Entry order, market share, and competitive advantage: A study of their relationships in new corporate ventures

This research explored the extent to which entry order (the decision to enter a market early as a “pioneer,” or to wait and follow) determines not only market share, but other competitive factors such as position and promotion that late entrants might hope to employ to overcome a pioneer's advantages. The study analyzed data on 119 nonservice new corporate ventures (consumer and industrial) from the Profit Impact of Marketing Strategy (PIMS) research data base, STR4. Based on a review of the strategic management and marketing literatures, three hypotheses on the effects of entry order were generated and subsequently tested. The first hypothesis states that pioneers achieve higher market shares than followers. Since, a priori, the market share for the pioneer has to be larger than the market share split among later entrants, the issue is the rate at which the early entrant's market share will decrease as additional businesses enter, what we term the “degree of lateness effect.” Later entrants have the choice of being an early follower, that is entering the industry soon after the pioneers, or waiting until the industry matures (late entrants). A high degree of lateness effect would indicate that early followers would gain higher market shares than late entrants. An analysis of the data indicated that pioneers have significantly higher market shares than followers and that little degree of lateness effect existed between early and late entrants. The second hypothesis states that pioneers will achieve differentiation advantages (in such areas as product and service quality, promotion, and technological positioning) greater than followers. There is considerable theoretical and empirical evidence that pioneers are able to generate competitive advantages through name recognition, image leadership, the establishment of technical standards which make switching to other products difficult, and superior consumer information advantages due to market lead times. An analysis of the data indicated that pioneers have significant competitive advantages in product/service quality and technology over followers. The one area where pioneers did not have a competitive advantage over followers was in advertising and promotion. The third hypothesis states that followers will achieve cost advantages greater than pioneers. While learning curve theory suggests that pioneers will enjoy cost/price advantages, contrasting arguments can be made that followers can enjoy lower costs by “coattailing” on the pioneer's efforts to educate consumers, develop a dominant design, and create an infrastructure to span the gap from raw material suppliers to finished good deliveries. We suggest that because pioneers are likely to have attained differentiation advantages, followers will have only one alternative left: compete on the basis of price and become the lowest-cost producer. An analysis of the data indicates that while followers do appear to have lower prices than pioneers, followers do not have significantly lower cost structures. This result implies a lower level of profitability for a follower strategy. Overall, the results of this study advance the notion that new corporate ventures should enter as pioneers, rather than as followers. Pioneers had higher market shares and stronger competitive positions (higher quality, more differentiated products, and better service) than followers. Followers appear to have few successful competitive options available outside of promotion for gaining market share.

The unit learning curve approximation of total cost

Learning curve theory has been integrated into mathematical models which previously did not take learning into account. Researchers have in general used one of two approximations of total cost based on the integral of the unit learning curve when developing larger models. An error analysis of the two approximations is presented.

A NOTE ON LEARNING CURVE PARAMETERS

AbstractThis note describes differences in the feasible range of values that the learning curve parameter may take when a unit learning approach is used as opposed to a cumulative‐average learning curve. Clarification of this point is important because learning curve theory now is used in a variety of areas.