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The existence of a learning curve in which a firm's costs decline with cumulative experience suggests that early entry provides learning opportunities that create an advantage by reducing future costs relative to later entrants. While prior strategy research has often assumed that learning curves are deterministic and known ex ante to firms, substantial evidence suggests that learning curves are inherently uncertain. If there is uncertainty in the learning curve, then the taken-for-granted wisdom regarding the strategic implications of learning curves may over- or under-emphasize the value of early entry. We consider two forms of uncertainty—prospective (future costs) and contemporaneous (current costs). We demonstrate computationally that while prospective uncertainty in the learning curve enhances the benefits of early entry, contemporaneous uncertainty reduces these benefits. Further, we examine the implications of these findings for competition and learning curve spillovers between leader and laggard firms. Recognizing learning curve uncertainty highlights a novel form of spillovers that do not affect expected cost but rather affect uncertainty about cost. Our core insight is that when learning curve uncertainty is large relative to the expected learning rate, it is uncertainty, rather than expectations about this rate, that determines the extent of early-mover advantage. [ABSTRACT FROM AUTHOR]

Background: The volume-outcome relationship is well-known in health care. The Experience Curve, initially developed by the Boston Consulting Group for manufacturing, offers insight on this relationship and has never before been applied to health care. Objectives: The purpose of this study was to determine the effect of experience on cost and resource utilization for the Cone procedure. Methods: We performed a retrospective review of patients who underwent Cone reconstruction for Ebstein’s anomaly at Boston Children’s Hospital between October 2010 and October 2021. Cardiopulmonary bypass time and aortic cross clamp time over time were evaluated using exponential regression to assess the surgeon-level learning curve. At the hospital level, length of stay and cost over time were assessed using exponential regression. Results: There were 115 patients included in the study. Median hospital length of stay was 7.9 days (IQR: 6.4-10.2 days) with a decline of 3.3% per year. Median intensive care unit [ICU] length of stay was 3.2 days (IQR: 2-5.7 days) with a decline of 10.5% per year. Adjusted direct costs indexed to 2020 prices fell by 4% per year. There was no statistically significant change in cardiopulmonary bypass or aortic cross clamp time. In mediation analysis, the reduction in cost was completely accounted for in the decline in ICU length of stay. ICU length of stay was correlated with duration of intubation. Conclusions: Increasing familiarity with Ebstein’s anomaly and Cone reconstruction led to a reduction in resource utilization.

Mathematical learning curve models have been widely used in strategic and production planning. In some emerging industries, the learning curve effect may be delayed or inhibited by various factors. This study proposes a new mathematical learning curve model—the squiggly learning curve model—for these emerging industries. The model incorporates any potential impeding factors in learning. It can present all the learning curve shapes in a single formula, from traditional log-linear learning curves to the S-curve learning curve and squiggly or sawtooth-shaped learning curves. This study adopts a mixed methods approach that combines mathematical modeling, nonparametric regression analysis using smoothed spline methods, questionnaire surveys, interviews, and case studies. The findings confirm that the model suitably represents the shape of sharing economy companies’ learning curve; this learning curve is affected by several factors, including the increase in site-patrol costs to prevent users from violating rules and regulations, site modification costs, and salaries for customer service and sales employees, which occur as the number of sharing economy platform users increases. Thus, the model can be a useful analytical tool for operations and strategic management in the growth phase of emerging industries, such as the sharing economy industry, where learning impediments exist.

A certain type of civil aircraft made in China is delivered and operated successively since 2015,and a large number of continuous airworthiness events and data are accumulated,but there is a lack of quantitative evaluation mechanism for economic analysis of continuous airworthiness events.Through the collection and analysis of continuous airworthiness events and data of civil aircraft,combined with the calculation of costs and benefits loss of main manufacturers and airlines,the cost structure of continuous airworthiness events is proposed.On this basis,the cost model of a single event and the experience curve model of continuous airworthiness events are established.And the cost prediction model of continuous airworthiness events for predicting the maturity of aircraft models is further proposed and verified.The results show that,in the using process of the proposed prediction model of aircraft fleet continuous airworthiness cost,the number of aircraft parking days,time interval between receiving events and determining actions,measure implementation time are highly sensitive.In the operation process of subsequent aircraft fleet,the values of these three parameters should be reduced as much as possible to reduce the cost of continuous airworthiness events.

• The transition to renewable energies is a multidimensional process. • Experience curves illustrate the need for an initial market to reduce costs. • Regulatory measures and economic instruments are necessary in the initial stages. • Legal and institutional framework is of great importance in the transition process. • Social acceptance is a very prominent factor in the renewable energy diffusion process. Fossil fuels are dominating the market and presenting a serious peril to the climate and the ecosystem. Hence, achieving sustainable development requires the development of new sources of energy that are clean and non-exhaustible. However, the transition to green energies is a gradual, complicated, and onerous proceeding that encompasses multiple stakeholders and dimensions. Therefore, it is necessary to analyze how the transition to renewable energies was addressed in the literature in order to identify all aspects and features of this complicated process. This analysis will be of great interest by allowing the comprehension and the concretization of such a complicated and multi-dimensional process. Although technical factors are prominent, the economic, institutional, social, and even psychological aspects of the transition to renewable energies should not be neglected. All these aspects are at the heart of environmental economics, institutional economics, and the psychosocial approach which will be detailed in the current review paper. We will present a different and new classification that encompasses almost all existing studies. In fact, we will classify research studies into five categories: the experience curve approach, the innovation diffusion approach, the environmental economics approach, the institutional economics approach, and the psychosocial approach. Moreover, we will try to analyze in-depth the advantages and limitations of each approach. [ABSTRACT FROM AUTHOR]

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Aim: There are few studies in the literature evaluating the robotic assisted unicondylar knee arthroplasty (rUKA) learning curve. This study aimed to evaluate the learning curve in robotic assisted unicondylar knee arthroplasty in terms of operation time. Materials and Methods: The data of patients who underwent rUKA between October 2016 and December 2019 were retrospectively analyzed. Age, gender, side, and body mass index (BMI) values of the patients were obtained from the patient files. To compare the operation times, the patients were divided into two groups. The first group represented patients who had surgery in the first half of the follow-up period (n=27), while the last group represented patients who had surgery in the second half of the follow-up period (n=28). Results: During the study period, rUKA was performed on 55 patients (42 females, 13 males) with a mean age of 64.1 years. The demographic data of the two groups were similar. The mean operative times of the first (n=27) and the last groups (n=28) were 101.816.1 minutes, and 84.89.9 minutes, respectively (p <0.001). Conclusion: The mean duration of operation was significantly shorter in the last group who underwent rUKA, compared to the first group. Our findings showed that there is a significant learning curve in rUKA surgery in terms of operation time. [ABSTRACT FROM AUTHOR]

Background: The volume-outcome relationship is well-known in health care. The Experience Curve, initially developed by the Boston Consulting Group for manufacturing, offers insight on this relationship and has never before been applied to health care., Objectives: The purpose of this study was to determine the effect of experience on cost and resource utilization for the Cone procedure., Methods: We performed a retrospective review of patients who underwent Cone reconstruction for Ebstein's anomaly at Boston Children's Hospital between October 2010 and October 2021. Cardiopulmonary bypass time and aortic cross clamp time over time were evaluated using exponential regression to assess the surgeon-level learning curve. At the hospital level, length of stay and cost over time were assessed using exponential regression., Results: There were 115 patients included in the study. Median hospital length of stay was 7.9 days (IQR: 6.4-10.2 days) with a decline of 3.3% per year. Median intensive care unit [ICU] length of stay was 3.2 days (IQR: 2-5.7 days) with a decline of 10.5% per year. Adjusted direct costs indexed to 2020 prices fell by 4% per year. There was no statistically significant change in cardiopulmonary bypass or aortic cross clamp time. In mediation analysis, the reduction in cost was completely accounted for in the decline in ICU length of stay. ICU length of stay was correlated with duration of intubation., Conclusions: Increasing familiarity with Ebstein's anomaly and Cone reconstruction led to a reduction in resource utilization., Competing Interests: The authors have reported that they have no relationships relevant to the contents of this paper to disclose., (© 2024 The Authors.)

Over the last decade, the levelized cost of electricity (LCOE) of solar and wind energy dropped extraordinary. Within this context, this paper aims to project the capital expenditures (CAPEX) of photovoltaic plants, onshore and offshore wind turbines for 2030 and 2050 by using the experience curve theory. Based on these, LCOE for 2020, 2030 and 2050 are estimated, investigated regarding their sensitivities and compared to fossil fuel based power plants. CAPEX projections amount to 250 to 430 € 2020 /kW el (2030) and 170 to 330 € 2020 /kW el (2050) for photovoltaic plants, 940 to 1,210 € 2020 /kW el (2030) and 820 to 970 € 2020 /kW el (2050) for onshore wind turbines and 1,730 to 2,570 € 2020 /kW el (2030) and 1,420 to 2,360 € 2020 /kW el (2050) for offshore wind turbines. Based on these results the LCOE of photovoltaic plants are estimated to drop up to more than 70 % (2050), while for wind turbines reductions up to 50 % (2050) are calculated. The highest sensitivity of the LCOE was identified for a variation of the CAPEX and annual full load hours. The comparison of the LCOE with fossil fuel operated power plants showed that the considered renewable options can obtain significant lower LCOE. • CAPEX for photovoltaic drop up to 75%. • CAPEX for wind turbines decreases up to 40% (onshore) and 50% (offshore). • Photovoltaic LCOE will be the lowest in the future. • LCOE shows highest sensitivity to annual full load hours and system CAPEX. • Future LCOE based on fossil fuels will be higher than based on solar or wind. [ABSTRACT FROM AUTHOR]

Research Summary: Research emphasizes the value of disaster preparation and the importance of experience in doing so, yet most companies fail to prepare. The antecedents of preparation are poorly understood, in part, because experience by itself only partly explains the story. To address these concerns, we developed two unique surveys: one from an international survey in 18 disaster‐prone countries and another from a U.S. survey in New York City and Miami. We find that organizational experience with natural disasters increases preparedness for future hazards. Also, organizational learning from other businesses and organiztions positively mediates this relationship. Managers are more willing to learn from others in locations characterized by high‐impact, low‐frequency disasters. In areas with low impact, high frequency disasters, managers more likely misjudge the severity of natural disasters. Managerial Summary: Despite the increasing frequency and severity of floods, storms, wildfires and other natural hazards, why do some firms in disaster‐prone areas prepare while others do not? To investigate, we conducted two studies: an international survey in 18 disaster‐prone countries and a U.S. survey in New York City and Miami. In both surveys, managers are more likely to prepare when their companies experienced prior disasters. Managers operating in locations characterized by high‐impact, low‐frequency disasters are more willing to learn from others. In contrast, managers in areas characterized by low impact, high frequency disasters, are more likely to prepare alone. Since effective disaster preparation typically entails working with, and learning from others, those companies that choose a go‐it‐alone strategy may misjudge disaster risk. [ABSTRACT FROM AUTHOR]

Purpose: The purpose is to present how a product feature, as determinant, affects selection of the appropriate buying method. The correct buying method choice provides companies with many advantages in terms of cost savings achieved within the organisation. Design/methodology/approach: The main method used is case study. The measurement of the result is based on target achievement set by a company. In addition the article reveals a new mathematical analysis of learning curve using integral calculation. Findings: Two determinants are presented – vulnerability to engineering changes and high labour intensity. Analyses show that choosing adequate buying method to a certain purchasing situation influences cost performance. There is also deliberation of new mathematical analysis of learning curve as supportive tool for industrial buyer. Research limitations/implications: The main limitation of this research is impossibility to test effectiveness of using different buying methods scenarios under the same conditions. Practical implications: For practitioners, buying method should be carefully chosen in relation to certain purchasing situation, e.g. product feature should be considered as one of the determinants. The article also provides supportive tool for price negotiations using learning curve phenomenon. Originality/value: The article presents how two determinants, frequent engineering changes and high labour intensity, affecting optimal industrial buying method selection in order to achieve better cost performance. In addition the article revealed new mathematical analysis of learning curve as supportive tool for professional buyers to be used during direct negotiations with suppliers. [ABSTRACT FROM AUTHOR]

Technological learning is a major aspect in the assessment of potential cost reductions for emerging energy technologies. Since the evaluation of experience curves requires the observation of production costs over several magnitudes of produced units, an early estimation of potential future technology implementation costs often presumes a certain degree of maturity. In this paper, we propose a calculation model for learning curves on the component or production process level, which allows to incorporate experience and knowledge on cost reduction potentials on a low level. This allows interchangeability between similar technologies, which is less feasible on a macro level. Additionally, the model is able to consider spill-over effects from concurrent technology usages for the inclusion of peripheral standard components for the assessment in an overall system view. The application of the model to the power-to-gas technology, especially water electrolysis, has shown, that the results are comparable to conventional approaches at the stack level, while providing transferability between different cell designs. In addition, the investigations made at the system level illustrate that the consideration of spill-over effects can be a relevant factor in the evaluation of cost reduction potentials, especially for technologies in an early commercial state with low numbers of cumulative productions. • Approach to evaluate learning curves for technologies at low TRL. • Analysis of learning effects on component level. • Consideration of spill-over learning effects from concurrent technologies. • Estimation on future costs of water electrolysis based on production volumes. • Enabling interchangeability of learning rates. [ABSTRACT FROM AUTHOR]

Assigning work to human resources is an important and common task for companies with high labour intensities. It is particularly complex if the human resources have multiple skills and if their efficiencies change due to learning and depreciation of knowledge depending on the tasks they are assigned to. In this context, up to now, only little work has considered strategic targets for company skill levels. Hence, we present an optimisation model to address the problem of assigning project work to multi-skilled internal and external human resources while considering learning, depreciation of knowledge and company skill level targets. This constrained nonlinear continuous model is solved using COIN-OR's Ipopt. We assess the computation time and the impacts of problem parameters such as the shape of the learning curve, company skill level targets, depreciation of knowledge and cost parameters. Amongst other findings, our results show that faster learning of human resources leads to more specialised individuals while at the same time the whole company's knowledge is broadened. [ABSTRACT FROM AUTHOR]

In this paper we investigate cross-training policies in a dual resource constraint (DRC) parallel job shop where new part types are frequently introduced into the system. Each new part type introduction induces the need for workers to go through a learning curve. A cross-training policy relates to the level of multi-functionality, the pattern of skill overlaps, and the distribution of skills among workers. Our results show that the frequency of new part type introduction needs to be considered when selecting a cross-training policy. The frequency of new part type introduction has impact on the optimal level of cross-training, the relative advantage of skill overlaps, and the extent to which a cross-training policy should incorporate differences between workers. These findings are important for many DRC job shops, especially for manufacturing cells in which all changes, associated with a part type introduction, are concentrated in one cell. [ABSTRACT FROM AUTHOR]

Cellulosic ethanol has great potential to displace fossil fuels and reduce greenhouse gas emissions, but supply is low due to high cost. Learning-by-doing is a strategy to reduce cost with increases in capacity. This study attempts to understand how learning-by-doing affects the growth of cellulosic ethanol in synergy with plant capacity. We modeled a three-phase learning effect using a hybrid general equilibrium model to project the U.S cellulosic ethanol production. The reference case projects an annual production of 5.49 million gallons (MG) from 2030 to 2040. With strong policy support of a high mandate, the U.S. is projected to produce 171 MG of cellulosic ethanol in 2040. However, the learning-by-doing effect cannot be initiated because only 4 large-scale centralized plants will be built. When plant size reduces, learning-by-doing is enabled, and 2040 cellulosic ethanol production can reach 3.27 billion gallons. Similar result is predicted for the cases representing an actual biorefinery. Fast and widespread learning is estimated to greatly increase production when plants have lower capital cost. The findings show that policy incentives are critical to technology development when cost is a significant barrier. Additionally, building small-size plants is a strategy that will enable and facilitate the learning-by-doing effect. • The U.S. annual cellulosic ethanol production is projected to be 5.49 MG in 2030. • A high mandate will drive the U.S. cellulosic ethanol production to 171 MG in 2030. • Learning is not observed for a few large-size plants, thus no reduction in cost. • When cost is a limiting factor, building small plants will facilitate learning. • Building plants at half- and quarter- sizes will boost production by 1.1–19 times. [ABSTRACT FROM AUTHOR]

The article discusses the management of learning curves in factories through the creation and transfer of knowledge. Studies show that productivity and quality improvement occurs at a decreasing rate in organizations as they gain experience with production. The author mentions that the logarithm of unit cost decreases with the logarithm of cumulative number of units produced at a uniform rate equal to that of learning. Multinational corporation, N.V. Bekaert, S.A., is discussed for its production process and efforts towards improving organizational learning curves. The author considers the global impact of conceptual and operation learning.

In industries characterized by network externalities, a single technology standard often rises to dominance, locking out competing technologies. This research demonstrates that despite 'path dependency,' it is possible to model the technology selection process and predict likely outcomes. This work extends previous work in network externalities by demonstrating that in addition to its 'installed base' and the availability of complementary goods, a firm's learning orientation and timing of entry also play significant roles in its success. [ABSTRACT FROM AUTHOR]

Cost reductions in nascent forms of Renewable Energy Technology (RET) are essential for them to contribute to the energy mix. Policy intervention can facilitate this cost reduction; however, this may require a significant investment from the public sector. These cost reductions fall into two broad categories: (1) incremental cost reductions through continual improvements to existing technologies, and (2) radical innovation where technologies that significantly differ from the incumbents are developed. This study presents a modelling methodology to integrate radical innovation in RET experience curve and learning investment analysis, using wave energy as an example nascent RET. This aims to quantify the potential effects of radical innovation on the learning investment, allowing the value of successful innovation to be better analysed. The study highlights the value offered by radical innovations in long-term deployment scenarios for wave energy. This suggests that high-risk R&D efforts in nascent RET sectors, even with low success rates, could still present significant expected value in offsetting future revenue support.

Intranets are a recent development in groupware technology based on the same open format as the Internet. The literature on computer aided communication suggests that groupware can facilitate information sharing and inter-functional coordination within firms. Inter-functional coordination is a significant component of a market orientation and is associated with marketing performance. This paper reports the results of a survey of Intranet adoption by New Zealand firms and the effect of Intranets on inter-functional coordination. The level of Intranet adoption is shown to be moderate (38% of responding firms) and independent of characteristics such as company resources or objectives. The presence of an Intranet is not significantly associated with the level of inter-functional coordination. There is, however, evidence of a learning curve, indicating that companies begin to experience coordination benefits from an Intranet after one year or more. [ABSTRACT FROM AUTHOR]

This article addresses the issues of competitive advantage and competitor imitation. It is argued that tacitness, complexity, and specificity in a firm's skills and resources can generate causal ambiguity in competency-based advantage, and thus raise barriers to imitation. Reinvestment in causally ambiguous competencies is necessary to protect the advantage. Without reinvestment, attritional effects of continued competitive action will cause decay in the barriers to imitation. From this theorizing, research propositions are suggested, which, ultimately, will lead to an improved understanding of competitive advantage sustainability. [ABSTRACT FROM AUTHOR]

Smith and Mick identify four basic problems with the theory the present writers developed to explain organizational responses (in this case the behavior of hospitals) to regulation. They challenge the basic assumption regarding autonomy, disagree with the implied cause and effect relations between organizational response and regu-lation, criticize the omission of goals, and claim that the theory has only limited generality. In so doing they state that their primary concern is with "improving our understanding of the limitations and benefits of the theory." Each of the four topics they raise for consideration will receive comment. [ABSTRACT FROM AUTHOR]

The article presents an analysis of sales personnel performance and seeks to explain the learning curve concept. In the process of training sales employees, they reportedly go through times of progress and times of stagnation. A mathematical model for evaluating the learning pattern of an employee is presented. The learning pattern calls for measuring total sales to date, and taking the average monthly sales volume. This method will enable an easier evaluation of performance. Concepts for interpreting the learning curve are provided and remedies for assisting employees are provided. This model is intended for commission based sales employees.

Experience curves are widely used to predict the cost benefits of increasing the deployment of a technology. But how good are such forecasts? Can one predict their accuracy a priori? In this paper we answer these questions by developing a method to make distributional forecasts for experience curves. We test our method using a dataset with proxies for cost and experience for 51 products and technologies and show that it works reasonably well. The framework that we develop helps clarify why the experience curve method often gives similar results to simply assuming that costs decrease exponentially. To illustrate our method we make a distributional forecast for prices of solar photovoltaic modules. [ABSTRACT FROM AUTHOR]

The experience curve theory assumes that technology costs decline as experience of a technology is gained through production and use. This article reviews the literature on the experience curve theory and its empirical evidence in the field of electricity generation technologies. Differences in the characteristics of experience curves found in the literature are systematically presented and the limitations of the experience curve theory, as well as its use in energy models, are discussed. The article finds that for some electricity generation technologies, especially small-scale modular technologies, there has been a remarkably strong (negative) relationship between experience and cost for several decades. Conversely, for other technologies, especially large-scale and highly complex technologies, the experience curve does not appear to be a useful tool for explaining cost changes over time. The literature review suggests that when analysing past cost developments and projecting future cost developments, researchers should be aware that factors other than experience may have significant influence. It may be worthwhile trying to incorporate some of these additional factors into energy system models, although considerable uncertainties remain in quantifying the relevance of some of these factors. [ABSTRACT FROM AUTHOR]

Although learning is an essential part of life, traditional scheduling techniques cannot efficiently handle this effect. Considering the effects of the learning curve, it is possible to make a better prediction of project duration thus saving time and money. In this paper, a learning curve (or experience curve) effect on project duration is shown and calculated with calendar days. In the literature, project scheduling has been studied; however, only a few papers take the learning effect on project duration into consideration. The learning effect on project duration with the help of test problems and real problems was investigated. In test problems learning curve effect can occur between two consecutive activities. These pairs are chosen randomly. After calculating project duration, these pairs are allocated to be closer to each other using the predecessor's total float time. It is assumed that the duration of impending repetitive activities is shorter due to the learning curve effect if the gap between consecutive activities is small enough. This iteration is carried out until it is not possible to shorten the successor's activity time in a pair. It is shown that this effect brings a 1-3% shorter project duration. This “Calendar Days” calculation led to an integer programming problem that was solved by Matlab Parallel Computing Toolbox. 2. [ABSTRACT FROM AUTHOR]

Background: Management theories of learning and experience curve effects state that greater levels of scale produce learnings and improved performance. In cardiovascular care, guidelines suggest that high-volume facilities produce better patient outcomes; yet, there are contradictory findings from the few studies conducted. Our goals were to assess the volume-outcome relationship for interventional cardiovascular care. Methods:We examined 9360 patients with ST-segment elevationmyocardial infarction who underwent percutaneous intervention (PCI).We analyzed 6 years of data (2010-2015) using systematic extracts provided by 33 PCI-capable hospitals in the Dallas Texas region from the National Cardiovascular Data Registry.We stratified hospitals into 3 procedural volume categories (low, intermediate, and high) to identify changes in 2 key outcome metrics (ie, door-to-balloon times and mortality). Multivariate analyses and tests of differences were utilized. Results: Door-to-balloon performance outcome was significantly different between volume categories, with the highest-volume hospitals performing significantly better than intermediate- and low-volume hospitals (47, 60, and 75 minutes, respectively; P< .001). Mortality followed a similar pattern, with a 3.3% unadjusted absolute lower mortality rate for the high-volume hospitals. Multivariate regressions confirm that volume is statistically significant in both mortality and treatment times. Conclusions: Higher-volume PCI hospitals have 37% shorter treatment times and 53% lower mortality rates than smaller facilities. This study provides evidence of a positive volume-outcome relationship in interventional cardiovascular care. [ABSTRACT FROM AUTHOR]

Intensive longitudinal and cluster-correlated data (ILCCD) can be generated in any situation where numerical or categorical characteristics of multiple individuals or study units are observed and measured at tens, hundreds, or thousands of occasions. The spacing of measurements in time for each individual can be regular or irregular, fixed or random, and the number of characteristics measured at each occasion may be few or many. Such data can also arise in situations involving continuous-time measurements of recurrent events. Generalized linear models (GLMs) are usually considered for the analysis of correlated non-normal data, while multivariate analysis of variance (MANOVA) is another option. In the paper, both GLMs and MANOVA are applied to ASSISTments online teaching system via the Wald test in order to estimate and predict the learning effects of the students after taking an Algebra course for three months in the system. Three case studies based on these two methodologies are presented in a mathematical and statistical manner. [ABSTRACT FROM AUTHOR]

Technology learning rates can be dynamic quantities as a technology moves from early development to piloting and from low volume manufacturing to high volume manufacturing. This work describes a generalizable technology analysis approach for disaggregating observed technology cost reductions and presents results of this approach for one specific case study (micro-combined heat and power fuel cell systems in Japan). We build upon earlier reports that combine discussion of fuel cell experience curves and qualitative discussion of cost components by providing greater detail on the contributing mechanisms to observed cost reductions, which were not quantified in earlier reports. Greater standardization is added to the analysis approach, which can be applied to other technologies. This paper thus provides a key linkage that has been missing from earlier literature on energy-related technologies by integrating the output of earlier manufacturing cost studies with observed learning rates to quantitatively estimate the different components of cost reduction including economies of scale and cost reductions due to product performance and product design improvements. This work also provides updated fuel cell technology price versus volume trends from the California Self-Generation Incentive Program, including extensive data for solid-oxide fuel cells (SOFC) reported here for the first time. The Japanese micro-CHP market is found to have a learning rate of 18% from 2005 to 2015, while larger SOFC fuel cell systems (200 kW and above) in the California market are found to have a flat (near-zero) learning rate, and these are attributed to a combination of exogenous, market, and policy factors. [ABSTRACT FROM AUTHOR]

In most studies on technology change, the analysis of cost reductions of new energy technologies has been narrow and has often neglected essential processes related to the deployment of new technologies, such as photovoltaics (PV). However, in the case of distributed PV systems, other costs than for the PV modules – aka the deployment or balance-of-system costs – are significant. This review study identifies the long-term dynamics of “hard” and “soft” costs associated with the deployment of building-sited PV systems in Germany since the early 1990s. The results show that the costs for central hardware components such as inverters and mounting systems have decreased by 70–87% since the 1990s. Results also show that "soft deployment costs" such as planning and installation decreased by 65–85%, and the corresponding experience curve has a progress ratio of 88–90%. The results imply that both hard and soft deployment costs have decreased with cumulative experience. Generally speaking, deployment processes, and support for such processes, are essential for the assessment of the overall cost dynamics related to the implementation of new energy technologies such as PV. [ABSTRACT FROM AUTHOR]

The strategic analysis tools are an invention researchers in terms of strategic management. The strength of curves, matrices and models is concretized in their power to schematize the general state of the enterprise from a huge quantity of information to make a final decision-making. The aim of this study is to explain how to make these theoretical tools practical in the Algerian enterprise. Taking the Dairy of Edough Annaba as an example, we realized that despite their strategic and analytic approach which helps for the decision-making, these tools are means of transfer and data storage device in the enterprise. [ABSTRACT FROM AUTHOR]

The learning curve depicts a decrease in production cost per unit as cumulative volume increases. However, a learning curve does not realize even if the history of production translates into an increase of cumulative volume. It is major premises for cost reduction to change technology in expectation of increasing scale of production. For example, new machinery and equipment are installed in preparation for commercial manufacturing, or product designs are modified for mass production. In other words, the first step to realize the learning curve is the management decision to mass-produce without falling victim to ceiling psychology. When building a prototype, you would use the unique building method suitable for it. If you were producing 10 units, you would naturally use a manufacturing method suited for 10 units. Similarly, for 100 units you would use a method for 100 units. For manufacturing 10,000 units, a mass production methodology for efficiently producing 10,000 units is best suited. Only forecasting of gargantuan cumulative volume from the very beginning enables the factory to adopt appropriate methods and technology for mass production. The learning curve could emerge only if the management has an unwavering conviction on a gigantic scale perspective. As a major premise for technological options, management’s scale perspective is the secret of the learning curve.

The “experience curve” used to be treated as a rule of thumb in strategic management theory. However, it would be hasty to conclude that an approximately 80% log-linear experience curve is a rule of thumb regardless of the industry, company, or product. According to the fundamental research on learning curves, generally, the new model of a product is partly composed of old model parts and we cannot observe the progress of these parts from the beginning of the processes. Therefore, in the first product of the new model, the learning rates of old model parts cannot be identical logically, even if the parts’ learning rates are identical at the beginning. In fact, empirical data repeatedly deny identical learning rates for all products. Applying search theory, we obtain an approximate log-linear learning curve and show the curve’s initial concavity, that is, if we started observing the progress midstream, and not from the beginning of the process. Thus, both varied learning rate proper to each product and initial concavity of the learning curve are phenomena induced by observing the progress midstream.