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Different technological domains have significantly different rates of performance improvement. Prior theory indicates that such differing rates should influence the relative speed of diffusion of t...

HighlightsUsing an elevated platform with a manure catcher reduced litter moisture content and ammonia concentration.A robotic vehicle encouraged bird movement and use of the elevated platform.Using the elevated platform and robotic vehicle jointly improved broiler paw quality and plumage cleanliness.Abstract. Elevated platform (EP) and robotic vehicle (RV) are two emerging systems aiming to improve environment enrichment and bird activity in broiler housing systems. However, the impacts of these systems on broiler production, welfare, and housing environment have not been evaluated. The objective of this study was to evaluate the effects of using EP and RV individually or jointly on broiler feed conversion ratio (FCR), litter moisture content (LMC), ammonia (NH3) concentration, gait score (GS), paw quality (PQ), plumage cleanliness (PC), and bird activity index (AI). Broilers were reared for eight-week production cycles. Four experimental rooms (54 birds room-1) were randomly assigned four treatments: EP only, RV only, EP and RV (EP+RV), and neither EP nor RV (Ctrl). Broiler GS, PQ, and PC were assessed following welfare protocols. Bird AI was determined through image processing. The experiment was repeated three times. The results showed that overall FCR values were 1.806 for EP, 1.804 for RV, 1.797 for EP+RV, and 1.791 for Ctrl. The normalized LMC values were 23.2% ±4.1% for EP, 32.8% ±4.1% for RV, 23.4% ±2.5% for EP+RV, and 35.7% ±7.0% for Ctrl over the eight-week production cycles. NH3 concentrations were 40% lower in the rooms with EP than in the rooms without EP at the end of the production cycle. Broilers had better PQ in the rooms with EP than in the rooms without EP. Broiler PC seemed better in the rooms with RV compared to those without RV. Operation of RV increased bird AI; however, the benefits in activity encouragement diminished as the broilers grew. The number of broilers on the EP was higher in the EP+RV rooms than in the EP rooms. It is concluded that using EP and RV together may improve broiler welfare and activity without compromising their production performance. Keywords: Behavior, Broiler, Elevated platform, Robotic vehicle, Welfare.

The patent database is often used in searches of inspirational stimuli for innovative design opportunities because of its large size, extensive variety and rich design information in patent documents. However, most patent mining research only focuses on textual information and ignores visual information. Herein, we propose a convolutional neural network (CNN)-based patent image retrieval method. The core of this approach is a novel neural network architecture named Dual-VGG that is aimed to accomplish two tasks: visual material type prediction and international patent classification (IPC) class label prediction. In turn, the trained neural network provides the deep features in the image embedding vectors that can be utilized for patent image retrieval and visual mapping. The accuracy of both training tasks and patent image embedding space are evaluated to show the performance of our model. This approach is also illustrated in a case study of robot arm design retrieval. Compared to traditional keyword-based searching and Google image searching, the proposed method discovers more useful visual information for engineering design., 11 pages, 11 figures

Greenhouse gas emissions from anthropogenic sources are believed to be the main cause of global warming and climate change. Furthermore, fossil fuels are forecasted to remain the dominant source of energy in the near future. Therefore, capture and sequestration of greenhouse gases and in particular carbon dioxide is likely to be a major pathway toward environmental protection and energy sustainability. Such clarity has stimulated an intense and diverse range of research into various capture and mitigation technologies, which race with global warming in real-time. Quantification of the performance improvement rates of these technologies can inform decision-makers’ long-term investment strategies, and help researchers to identify technical bottlenecks and research potential. The present research estimates the yearly performance improvement rate of CO2 capture, non-CO2 GHG capture, and GHG mitigation technologies, using a novel method based on patent data and the corresponding citation network. Our findings suggest that membrane-based, condensation/rectification-based, and adsorption-based carbon capture are the most promising technologies. Furthermore, the average CO2 capture technologies are likely to improve slightly faster than solar, wind, and battery technologies, indicating their important role in future electrical grids. Unfortunately, subterranean or submarine CO2 storage was identified as a slow-growing technological domain and potentially a bottleneck in the future sustainable carbon chain, which requires further efforts.

The patent database is often used by designers to search for inspirational stimuli for innovative design opportunities because of the large size, extensive variety, and the massive quantity of design information contained in patent documents. Growing work on design-by-analogy has adopted various vectorization approaches for associating design documents. However, they only focused on text analysis and ignored visual information. Research in engineering design and cognitive psychology has shown that visual stimuli may benefit design ideation. In this study, we focus on visual design stimuli and automatically derive the vector space and the design feature vectors representing design images. The automatic vectorization approach uses a novel convolutional neural network architecture named Dual-Visual Geometry Group (VGG) aiming to accomplish two tasks: visual material-type prediction and international patent classification (IPC) section-label predictions. The derived feature vectors that embed both visual characteristics and technology-related knowledge can be potentially utilized to guide the retrieval and use of near-field and far-field design stimuli according to their vector distances. We report the accuracy of the training tasks and also use a case study to demonstrate the advantages of design image retrievals based on our model.

In this work, we attempt to provide a comprehensive granular account of the pace of technological change. More specifically, we survey estimated yearly performance improvement rates for nearly all definable technologies for the first time. We do this by creating a correspondence of all patents within the US patent system to a set of technology domains. A technology domain is a body of patented inventions achieving the same technological function using the same knowledge and scientific principles. We obtain a set of 1757 domains using an extension of the previously defined classification overlap method (COM). These domains contain 97.14% of all patents within the entire US patent system. From the identified patent sets, we calculated the average centrality of the patents in each domain to estimate their improvement rates, following a methodology tested in prior work. The estimated improvement rates vary from a low of 1.9% per year for the Mechanical Skin treatment - Hair Removal and wrinkles domain to a high of 228.8% per year for the Network management - client-server applications domain. We developed a one-line descriptor identifying the technological function achieved and the underlying knowledge base for the largest 50, fastest 20 as well as slowest 20 of these domains, which cover more than forty percent of the patent system. In general, the rates of improvement were not a strong function of the patent set size and the fastest improving domains are predominantly software-based. We make available an online system that allows for automated searching for domains and improvement rates corresponding to any technology of interest to researchers, strategists and policy formulators.

In this work, we attempt to provide a comprehensive granular account of the pace of technological change. More specifically, we survey estimated yearly performance improvement rates for nearly all definable technologies for the first time. We do this by creating a correspondence of all patents within the US patent system to a set of technology domains. A technology domain is a body of patented inventions achieving the same technological function using the same knowledge and scientific principles. We obtain a set of 1757 domains using an extension of the previously defined classification overlap method (COM). These domains contain 97.14% of all patents within the entire US patent system. From the identified patent sets, we calculated the average centrality of the patents in each domain to estimate their improvement rates, following a methodology tested in prior work. The estimated improvement rates vary from a low of 1.9% per year for the Mechanical Skin treatment- Hair Removal and wrinkles domain to a high of 228.8% per year for the Network management- client-server applications domain. We developed a one-line descriptor identifying the technological function achieved and the underlying knowledge base for the largest 50, fastest 20 as well as slowest 20 of these domains, which cover more than forty percent of the patent system. In general, the rates of improvement were not a strong function of the patent set size and the fastest improving domains are predominantly software-based. We make available an online system that allows for automated searching for domains and improvement rates corresponding to any technology of interest to researchers, strategists and policy formulators.

The shortening lifetime of technology requires companies to make intensive efforts to continuously explore new technology. Although many researchers have proposed visualization methods to find technology opportunities, little attention has been paid to present detailed directions of technology development with specified characteristics of technology. Thus, this research aims to suggest a systematic approach to conducting technology opportunity analysis by visualizing patent information, such as patent documents and citation relationships. First, keywords that explain core concepts, functions, and so on are extracted from collected patent documents by text mining. Second, patents are visualized in a two-dimensional space, and vacant cells are identified with their estimated keyword vectors by generative topographic mapping (GTM). Third, since many vacant cells will be potential candidates for developing new technologies, link prediction tools can choose promising vacant cells to connect existing cells with potential, but not yet existent, cells. Finally, the results of prediction are tested by comparing the predicted cells with the actual developed cells. The research reported in this paper is based in three technologies that have emerging, stable, and declining patterns, in order to illustrate the proposed approach, and investigate in which types it is relevant. It is found that the proposed approach provided a good prediction performance in the case of a technology that has a stable pattern. In addition, among link prediction methods, a semantic similarity-based approach showed better prediction results than a machine learning technique due to modest data availability for training. Thus, the results of this research can help R&D managers plan and evaluate R&D projects for technology development.

The relationship of scientific knowledge development to technological development is widely recognized as one of the most important and complex aspects of technological evolution. This paper adds to our understanding of the relationship through use of a more rigorous structure for differentiating among technologies based upon technological domains (defined as consisting of the artifacts over time that fulfill a specific generic function using a specific body of technical knowledge). The key findings of the work are: Firstly, a Pearson correlation of 0.564 is found between technological relatedness among technological domains based upon patents citing other patents and technological relatedness among technological domains based upon patents citing similar scientific papers. This result indicates that a large portion of technological relatedness is due to relatedness of the underlying scientific categories. Secondly, the overall structure of the links found between scientific categories and technological domains is many-to-many rather than focused indicating a science-fostered mechanism for fairly broad “spillover”: Specific technological domains cite a wide variety of scientific categories; some scientific categories are cited in a variety of domains. Thirdly, some evidence is found supporting the co-evolution of science and technology but the evidence is not strong. Prior research that identifies emerging patent clusters and independent prior research identifying emerging scientific topics show statistically significant but qualitatively weak inter-relationships between the clusters and topics. This work also offers evidence that patent cluster emergence can, but does not usually, precede the emergence of related scientific topics. The lack of clear evidence for co-evolution is interpreted as resulting from the documented complex many-to-many relationship of science categories and technological domains and is not considered evidence against co-evolution.

This paper proposes classification of the technology models used in environmental analysis into three categories: detailed description of a thoroughly specified technology; general time dependent specification for technological domains; and most broadly with technology as a residual after accounting for other known drivers of change in environmental impact. The essence of each model is explained further in the paper with the fundamental differences among the three modeling approaches emphasized. This paper especially reviews the relative strengths and weaknesses of each of the three categories. Applications are noted for each category with combined applications of two approaches suggested as potentially offering the most value but such combinations have not yet received much attention.

This paper develops a quantitative model for dematerialization and generalizes it to other types of environmental impacts similar to the well-known IPAT framework. The essential difference of this model from IPAT, STIRPAT and other models for incorporating technological change in socio-economic phenomenon is that we utilize a specific model for technological change beyond the residual definition generally employed. This model of technological change is theoretically realistic, includes rebound and generalizes Moore’s Law- a generalization that is empirically supported. This paper, distinct from an earlier paper of ours, puts the overall model in a wider environmental context than dematerialization and suggests that the model developed here applies to all environmental impacts that are extensive (for example energy consumption and waste generation in addition to materials consumption). For intensive environmental impacts (such as specific pollutants), rebound is not necessary to consider but modified technological substitution models may become useful.

Providing adequate feeder space in broiler production is important to ensure bird performance and well-being; however, the effect of feeder space on behavior responses of broilers remains unclear. The objective of this research was to investigate feeding behaviors of broilers provided with 4 feeder spaces, that are 2.3 cm/bird with one feeder (2.3FSO); and 2.3, 4.6, and 6.9 cm/bird with 3 feeders (2.3FST, 4.6FST, and 6.9FST, respectively). Number of feeder slots per feeder was 14 at 2.3FSO, 5 at 2.3FST, 9 at 4.6FST, and 14 at 6.9FST. Sixteen identical pens, each with 45 broilers (Ross 708, mixed sex), were used to accommodate the 4 feeder space treatments. Feeding behaviors were continuously monitored from weeks 4 to 8 using an ultra-high-frequency radio frequency identification system. The results show that the daily feeding time and number of feeder visits for broilers at 2.3FST were similar to those at 4.6FST and 6.9FST but higher than those at 2.3FSO (P < 0.01). The feeder utilization ratio was the highest at 2.3FST, indicating the feeder being used most efficiently among the 4 treatments (P < 0.01). Coefficient of variations (33.0–65.1%) of the feeding behavior responses was similar among the treatments (P ≥ 0.06), suggesting similar group uniformity of feeding behaviors of individual broilers. Feeders among all treatments may not be fully used because for most of the time, less than 6 birds chose to eat simultaneously at a more-than-five-slot feeder in all treatments. Given the same feeder space, increasing feeder number can accommodate more birds to eat simultaneously. The outcomes of this study provide insights into improvement of feeder design and management for broiler production.

Technology innovation in electric vehicles is of significant interest to researchers, companies and policy-makers of many countries. Electric vehicles integrate various kinds of distinct technologies and decomposing the overall electric vehicle field into several key domains allows determination of more detailed, valuable information. To provide both broader and more detailed information about technology development in the EV field, unlike most previous studies on electric vehicle innovation which analyzed this field as a whole, this research decomposed the electric vehicle field into domains, which are power electronics, battery, electric motor as well as charging and discharging subdomains and then further extracted the subdomains. Furthermore, In addition, the improvement rates, technology trajectories and major patent assignees in these domains and key subdomains are determined using patents extracted for each domain from the US patent system. The main findings are: (1) The estimated rates of performance improvement per year are 18.3% for power electronics, 7.7% for electric motors, 23.8% for charging and discharging and 11.7% for batteries. The relatively lower improvement rate for electric motors and batteries suggests their potential to hinder the popularization of electric vehicles. Besides, as for the subdomains, the relatively higher technology improvement rate of lithium-ion battery or permanent magnet motor in its domain supports the current trend of battery or motor type quantitively from a patent analysis view. A possible implication for the policy makers encouraging EV development is to issue more incentive plans for innovations in the battery and electric motor domains, especially for lithium-ion battery and permanent magnet motor. (2) The technology trajectories depict the development of four critical subdomains over time, which quantitively proves the focuses and emerging topics of the subdomains and thereby provide guidance to research topic selection. For example, the silicon negative electrode is a promising topic in the subdomain of lithium-ion battery. (3) The key players in the four critical subdomains appear to be Toyota and Honda in hybrid power electronics, E-One Moli Energy Corp in lithium-ion batteries, Panasonic in Permanent Magnet motors and Toyota in discharging. The key players found by the main path method from the view of innovation are also important players in EV from the market view. Other market participants should pay more attention to the adjustment of business strategy of these companies to monitor the market, and make effort to invent important EV related technologies.

This paper applies objective methods to explore the technological origins of the widely acclaimed CRISPR breakthrough in the technological domain of genome engineering. Previously developed patent search techniques are first used to recover a set of patents that well-represent the genome editing domain before CRISPR. Main paths are then determined from the citation network associated with this patent set allowing identification of the three major knowledge trajectories. The most significant of these trajectories for CRISPR involves the core of genome editing with less significant trajectories involving cloning and endonuclease specific developments. The major patents on the core trajectory are consistent with qualitative expert knowledge of the topical area. A second set of patents that we call the CRISPR roots are obtained by finding the patents directly cited by the recent CRISPR patents along with patents cited by that set of patents. We find that the CRISPR roots contain 8 key patents from the genome engineering main path associated with restriction endonucleases and the expected strong connection of CRISPR to prior genome editing technology such as Zn finger nucleases. Nonetheless, analysis of the full CRISPR roots shows that a very wide array of technological knowledge beyond genome engineering has contributed to achieving the CRISPR breakthrough. Such breadth in origins is not surprising since “spillover” is generally perceived as important and previous qualitative studies of CRISPR have shown not only technological breadth in origins but scientific breadth as well. In addition, we find that the estimated rate of functional performance improvement of the CRISPR roots set is about 9% per year compared to the genome engineering set (˜4 % per year). These estimates indicate below average rates of improvement and may indicate that CRISPR (and perhaps yet undiscovered) genome engineering developments could evolve in effectiveness over an upcoming long rather than short time period.

Battery electric vehicles (BEVs) are now clearly a promising candidate in addressing the environmental problems associated with conventional internal combustion engine vehicles (ICEVs). However, BEVs, unlike ICEVs, are still not widely accepted in the automobile market but continuing technological change could overcome this barrier. The aim of this study is to assess and forecast whether and when design changes and technological improvements related to major challenges in driving range and battery cost will make the user value of BEVs greater than the user value of ICEVs. Specifically, we estimate the relative user value of BEVs and ICEVs resulting after design modifications to achieve different driving ranges by considering the engineering trade-offs based on a vehicle simulation. Then, we analyze when the relative user value of BEVs is expected to exceed ICEVs as the energy density and cost of batteries improve because of ongoing technological change. Our analysis demonstrates that the relative value of BEVs is lower than that of ICEVs because BEVs have high battery cost and high cost of time spent recharging despite high torque, high fuel efficiency, and low fuel cost. Moreover, we found the relative value differences between BEVs and ICEVs are found to be less in high performance large cars than in low performance compact cars because BEVs can achieve high acceleration performance more easily than ICEVs. In addition, this study predicts that in approximately 2050, high performance large BEVs could have higher relative value than high performance large ICEVs because of technological improvements in batteries; however low performance compact BEVs are still very likely to have significantly lower user value than comparable ICEVs until well beyond 2050.

The aim of this paper is to develop and test the metrics to quantitatively identify technological discontinuities in a knowledge network. We first analyzed the various conceptual frameworks for defining such discontinuities and arrived at four metrics. We tested the four metrics: Metric 1 and 2 are the normalized versions of previously existing metrics and Metric 3 and 4 are newly developed from the innovation theories, by using a patent set representative of the magnetic information storage domain. The three representative patents associated with a well-known breakthrough technology in the domain, the giant magneto-resistance spin valve sensor, were selected based on qualitative studies, and the metrics were tested by how well each identifies the selected patents as top-ranked patents. The empirical results show that, first, global citation structure-based metrics clearly provide better performance in the identification of technological discontinuities than local citation count-based metrics which have not been shown as clearly before, second, non-continuous nodes on the major knowledge networks are not at all related to technological discontinuities, and, third, the two global metrics (Metric2: z-score of Persistence and Metric 4: z-score of Persistence times # of converging main paths) successfully identified the three selected patents as top-ranked patents out of over 30 000 patents.

The future direction of technology development depends on the relative yearly rate of functional performance improvement of different technologies. We use patent data to identify accurate and reliable predictors of this rate for 30 technologies. We illustrate how patent-based predictors should be normalized to correct for possible confounding factors introduced by changing patenting dynamics. We test the accuracy and reliability of various predictors by means of a Monte Carlo cross-validation exercise. We find that a measure of the centrality of domains’ patented inventions in the overall US patent citation network is an accurate and highly reliable predictor of improvement rates.

The dynamics of knowledge transfer is an important topic for engineering managers. In this paper, we study knowledge boundaries – barriers to knowledge transfer – in groups of experts, using topic modeling, a natural language processing technique, applied to transcript data from the U.S. Food and Drug Administration’s Circulatory Systems Advisory Panel. As predicted by prior theory, we find that knowledge boundaries emerge as the group faces increasingly challenging problems. Beyond this theory, we find that knowledge boundaries cease to structure communications between communities of practice when the group’s expert ability is insufficient to solve its task, such as in the presence of high novelty. We conjecture that the amount of expert knowledge that the group can collectively bring to bear is a determining factor in boundary formation. This implies that some of the factors underlying knowledge boundary formation may aid – rather than hinder – knowledge aggregation. We briefly explore this conjecture using qualitative exploration of several relevant meetings. Finally, we discuss implications of these results for organizations attempting to leverage their expertise given the state of their collective knowledge.

This paper empirically examines 13 technologies in which significant cost and performance improvements occurred even while no commercial production occurred. Since the literature emphasizes cost reductions through increases in cumulative production, this paper explores cost and performance improvements from a new perspective. The results demonstrate that learning in these pre-commercial production cases arises through mechanisms utilized in deliberate R&D efforts. We identity three mechanisms – materials creation, process changes, and reductions in feature scale – that enable these improvements to occur and use them to extend models of learning and invention. These mechanisms can also apply during post-commercial time periods and further research is needed to quantify the relative contributions of these three mechanisms and those of production-based learning in a variety of technologies.

Surface wetting on the textured surface is classically explained by the theories of Cassie-Baxter or Wenzel. However, in recent years, an increasing number of complex surface topographies with superhydrophobic properties have been achieved without prediction or simulation using these theories. One example is biomimetic surfaces. In many instances, theories were used to explain surface properties found in nature but have not led to or predicted the complex topographies. Although new wetting theories continue to emerge, there is not yet a set of design rules to guide the selection of surface topographies to achieve superhydrophobicity. By grouping known surface topographies into common geometrical descriptions and length scale, this paper suggests a set of surface topography classifications to provide selection guidelines for engineering superhydrophobic surfaces. Two key outcomes emerged from the design analysis: first, categorization of frequently reported surface patterns shows that there exists a set of commonly used descriptions among diverse designs; second, the degree of hydrophobicity improvement within a class of topography design can be used to predict the limit of improvement in superhydrophobicity for a given material. The presentation of topography descriptors by categories of design and performance may serve as a prologue to an eventually complete set of design guidelines for superhydrophobic performance. Refereed/Peer-reviewed

This paper surveys the worldwide production of a basket of 98 important industrial materials between 1960 and 2013, divided into 9 main groups. The objective was to look for an answer to the question if it is possible to keep the global economy growing while simultaneously reducing the amount of materials resources necessary to maintain today’s growth rate. Our results were analyzed within the framework of the dematerialization theory and the decoupling concept, checking the temporal unfolding in the past 50 years of the most widely used industrial materials, aiming to identify trends in dematerialization in the usage of this set of materials. One of the most striking patterns to be noted in our results is the spike-like aspect of the increasing consumption of some key materials in the first decade of the present century, a trend that seems to resume in most recent years, and is interpreted as a consequence of China’s modernization in the past three decades. Our results do not support the conclusion that human society is experiencing dematerialization of the global economy, but some patterns found show that there are reasons for optimism.

The purpose of this study is to investigate the structure and evolution of knowledge spillovers across technological domains. Specifically, dynamic patterns of knowledge flow among 29 technological domains, measured by patent citations for eight distinct periods, are identified and link prediction is tested for capability for forecasting the evolution in these cross-domain patent networks. The overall success of the predictions using the Katz metric implies that there is a tendency to generate increased knowledge flows mostly within the set of previously linked technological domains. This study contributes to innovation studies by characterizing the structural change and evolutionary behaviors in dynamic technology networks and by offering the basis for predicting the emergence of future technological knowledge flows.

This paper seeks to analyze how design creates economic value. The literature on knowledge-based economic development has primarily focused on innovation as the analytical lens, whereas design is the original action that leads to innovation. Despite the fundamental importance of design, existing design research has offered few insights and little guidance for national strategies due to the lack of focus on and analysis of design in an economic context. This paper addresses such gaps by linking design research and economic development theory. We first elaborate on the relationship among design, invention and innovation, describing the necessity of design activity for invention and innovation. Our analysis of the fundamental characteristics of design across contexts sheds light on the strategic importance of the accumulative nature of technology-based design for sustaining economic growth. Through the lens of technology-based design, we further quantitatively compare Singapore and three similarly-sized countries (South Korea, Finland and Taiwan). Based upon interview data, we also qualitatively examine Singapore's national strategy focusing on design. The quantitative and qualitative results align well with the Singaporean government's use of design as a strategic lever to pursue innovation-driven economic growth, and also reveal its achievements and shortfalls which indicate possible directions for strategic adjustment. Keywords: Technology-based design; Invention; Innovation; Design capability; Economic growth, SUTD-MIT International Design Centre (IDC)

An important issue in various domains of renewable energy is the use of technological improvement trends to project future capabilities of energy technologies. This paper analyzes two pairs of renewable energy technologies and finds that the annual improvement rate of cost/investment is quite different for the four technological domains: namely, solar photovoltaics (PV) (9.0% per year), wind turbines (2.9%), batteries (3.1%) and capacitors (21.1%). While these trends have been reasonably consistent over long time frames, projecting these trends into the future without a better understanding of the underlying causes of the improvements is not at all reliable. This paper establishes theoretical fundamentals for explaining the differences in such rates and a framework for empirically probing such explanations using patent data. Employing this framework, this study collects and analyzes a set of highly representative patents for each of the four domains, allowing measurement of: patenting rates, reliance on scientific literature and other characteristics of the different fields. Our study of the inventions, while not establishing an indisputable causal relationship for the differing rates, establishes a broader theoretical basis for why such rates differ so greatly and why they might be stable over time. Among many possible effects, this study indicates that the age of knowledge utilized in the patents and the percentage of very important inventions in the field are the most likely significant contributors to higher rates of advance.

This article proposes a new descriptive framework, which we label as the “ideation framework” (IF), of the design process from a dual cognitive-engineering perspective, partly based on existing frameworks from both fields and previous work by the author. The framework is for the ideation or front-end phase of the product development process, representing the interface between cognitive psychology and engineering design. Three domains – inspiration, decomposition, and integration – and three spaces – problem-space, idea-space, and concept-space – are the elements of the framework. The iterative flow of the engineering design process passes through the three domains in a semi-controlled way, through a sequence of specialization and generalization process loops in and between the spaces. An empirical descriptive examination of the ideation process is performed using designers with limited design experience. The designers were faced with a design problem that they had to solve in a limited period of time. The...

The aim of this paper is to propose a new method to identify main paths in a technological domain using patent citations. Previous approaches for using main path analysis have greatly improved our understanding of actual technological trajectories but nonetheless have some limitations. They have high potential to miss some dominant patents from the identified main paths; nonetheless, the high network complexity of their main paths makes qualitative tracing of trajectories problematic. The proposed method searches backward and forward paths from the high-persistence patents which are identified based on a standard genetic knowledge persistence algorithm. We tested the new method by applying it to the desalination and the solar photovoltaic domains and compared the results to output from the same domains using a prior method. The empirical results show that the proposed method overcomes the aforementioned drawbacks defining main paths that are almost 10x less complex while containing more of the relevant important knowledge than the main path networks defined by the existing method., 20 pages, 7 figures

Dematerialization is the reduction in the quantity of materials needed to produce something useful over time. Dematerialization fundamentally derives from ongoing increases in technical performance but it can be counteracted by demand rebound -increases in usage because of increased value (or decreased cost) that also results from increasing technical performance. A major question then is to what extent technological performance improvement can offset and is offsetting continuously increasing economic consumption. This paper contributes to answering this question by offering some simple quantitative extensions to the theory of dematerialization. The paper then empirically examines the materials consumption trends as well as cost trends for a large set of materials and a few modern artifacts over the past decades. In each of 57 cases examined, the particular combinations of demand elasticity and technical performance rate improvement are not consistent with dematerialization. Overall, the theory extension and empirical examination indicate that there is no dematerialization occurring even for cases of information technology with rapid technical progress. Thus, a fully passive policy stance that relies on unfettered technological change is not supported by our results.

Patents represent one of the most complete sources of information related to technological change, and they also contain much detailed information not available anywhere else. Thus, patents are the ‘big data’ source most closely related to future-oriented technology analysis (FTA). Not surprisingly, therefore, there is very significant practical and academic use of the patent database for understanding past technical change and attempting to forecast future change. This paper summarizes several new methods and demonstrates their combined effectiveness in establishing a cutting-edge capability for patent study not previously available. This capability can be stated as a link between the information in patents and the dynamics of technological change. The demonstrated capability relies upon the use of a database containing the rates of improvement for various technologies. We also specify the term we use for the analysed units of technology: a technological domain is a set of artefacts that meets a specific generic function while utilizing a specific set of engineering and scientific knowledge. This definition is unambiguous enough so technological domains can be linked with progress rates and are sufficiently flexible to accommodate the large scale and complexity of the patent database. The existence of an improvement rate database and its quality is a critical foundation for this paper. Establishing the overall capability also involves relating the rate of improvement of a technological domain to the patents in that domain. We show that a recently developed method called the classification overlap method (COM) provides a reliable and largely automated way to break the patent database into understandable technological domains where progress can be measured. In this paper, we show how this method overcomes the third limitation of the patent database. The major conclusion of the paper is that there is now an overall objective method named Patent Technology Rate Indicator (PTRI) for using just patent data to reliably estimate the rate of technological progress in a technological domain. Thus, the first link between the patent database information and the dynamics of technological change is now firmly established; robustness and back-casting tests have shown that the assertion of reliability is meaningful and that the estimate has predictive value. We demonstrate the key methodology of new elements (use of COM and rate estimation from the selected patent sets) for 15 technologies that some have thought have possible future importance. The 15 cases also demonstrate the usefulness of the overall method by estimating technological improvement rates that are significantly different for this group of technologies.

In Smith and Eppinger's pioneering research on coupled design processes, the dynamics of design iterations is modeled by a linear model, which implies that there is no overlap between redesign work and allows redesign workload to be more than the original design workload. Actually, this overlap often exists in practice and, therefore, reduces the total redesign workload. In this paper, we propose a nonlinear model for a coupled design process with overlap between redesign work and ensure that redesign workload is less than the original design workload. Based on the model, the sufficiency condition for the convergence of such a design process is proposed. A heuristic rule is also given to reduce the possibility of considering a design process that converges as one that does not converge. Furthermore, we develop a sufficiency condition for estimating the number of design iterations before converging as such an estimate is important for planning product development projects. Another heuristic rule is also introduced to increase the accuracy of estimating design iterations. Finally, numerical experiments are conducted to examine the correctness and performance of the proposed sufficiency conditions and heuristic rules.

This article presents a method for quantitatively assessing the role of materials innovation in overall technological development. The method involves classifying the technical changes underlying the overall innovation process first within a set of functional categories and then within each category as a hierarchical array of technical changes. It is specifically found that about 2/3 of the total progress in computation over the past 40 years has been due to materials/process innovations. More speculatively, materials/process innovation contributes at least 20% of the progress in all areas and the relative contribution of materials/process innovation to overall technological progress has grown in the past few decades., W. L. Gore & Associates

Many important technical and policy decisions are made by small groups, especially by deliberative committees of technical experts. Such committees are charged with fairly combining information from multiple perspectives to reach a decision that one person could not make alone. Committees are social entities and are therefore affected by any number of mechanisms recorded in the social sciences. Our challenge is to determine which of these mechanisms are likely to be encountered in the deliberative process and to evaluate how they might impact upon decision outcomes. In particular, we examine the role of committee deliberations on the U.S. Food and Drug Administration's (FDA's) advisory panels.

Many products are manufactured in networks of firms linked by transactions, but comparatively little is known about how or why such transaction networks differ. This article investigates the transaction networks of two large sectors in Japan at a single point in time. In characterizing these networks, our primary measure is "hierarchy," defined as the degree to which transactions flow in one direction, from "upstream" to "downstream." Our empirical results show that the electronics sector exhibits a much lower degree of hierarchy than the automotive sector because of the presence of numerous inter-firm transaction cycles. These cycles, in turn, reveal that a significant group of firms have two-way "vertically permeable boundaries": (i) they participate in multiple stages of an industry's value chain, hence are vertically integrated, but also (ii) they allow both downstream units to purchase intermediate inputs from and upstream units to sell intermediate goods to other sector firms. We demonstrate that the 10 largest electronics firms had two-way vertically permeable boundaries while almost no firms in the automotive sector had adopted that practice. Copyright 2012 The Author 2012. Published by Oxford University Press on behalf of Associazione ICC. All rights reserved., Oxford University Press.

This paper reviews a large number of approaches that have been used for considering technologically driven profound societal change. We agree with Vinge's suggestion for naming events that are “capable of rupturing the fabric of human history” (or leading to profound societal changes) as a “singularity”. This is a useful terminology especially since a mathematically rigorous singularity seems impossible for technological and related societal change. The overview of previous work is done within the context of a broader look at the role of technological change within human history. The review shows that a wide variety of methods have been used and almost all point to singularities in the present century particularly in the middle of the century. The diversity of the methods is reassuring about the potential robustness of these predictions. However, the subjectivity of labeling events as singularities (even well studied past events) is a concern about all of the methods and thus one must carefully pause when relying in any way on these predictions. The general lack of empirical research in this area is also a concern. Quantitative considerations (by proponents and opponents) about past singularities or future singularities often confound two types of metrics. The first type is essentially related to diffusion of technologies (or bundles of technologies) where the logistic curve is empirically well established as the proper time dependence. The second type of metric is for technological capability where hyper-exponentials are empirically well established for their time dependence. In this paper, we consider two past singularities (arguably with important enough social change to qualify) in which the basic metric is alternatively of one type or another. The globalization occurring under Portuguese leadership of maritime empire building and naval technological progress is characterized by a metric describing diffusion. The revolution in time keeping, on the other hand, is characterized by a technological capability metric. For these two cases (and thus robust to the choice of metric type), we find that: • People undergoing profound technologically-driven societal change do not sense a singularity. • The societal impacts depend in complicated ways on human needs, institutional variables and other more uncertain factors and thus are particularly hard to project; • The societal impact is apparently not determined by the rate of progress on either type of metric or by projections to mathematical points with either kind of metric. This finding supports the existing concept that social change due to technology is a more holistic phenomenon than can be characterized by any technical metric. In the final section, we use these empirical findings as the basis for exploring the possibilities for and nature of future singularities. In this we speculate that the potential for a future strong singularity based upon computational capability does not appear particularly probable but that one may already be occurring and is not fully noticed by those (us) going through it. Other possible 21st century singularities (life extension and fossil fuel elimination are two examples considered) may also be already underway rather than waiting for the predicted mid-century changes.

Hierarchies occur widely in evolving self-organizing ecological, biological, technological, and social networks, but detecting and comparing hierarchies is difficult. Here we present a metric and technique to quantitatively assess the extent to which self-organizing directed networks exhibit a flow hierarchy. Flow hierarchy is a commonly observed but theoretically overlooked form of hierarchy in networks. We show that the ecological, neurobiological, economic, and information processing networks are generally more hierarchical than their comparable random networks. We further discovered that hierarchy degree has increased over the course of the evolution of Linux kernels. Taken together, our results suggest that hierarchy is a central organizing feature of real-world evolving networks, and the measurement of hierarchy opens the way to understand the structural regimes and evolutionary patterns of self-organizing networks. Our measurement technique makes it possible to objectively compare hierarchies of different networks and of different evolutionary stages of a single network, and compare evolving patterns of different networks. It can be applied to various complex systems, which can be represented as directed networks. © 2011 Wiley Periodicals, Inc. Complexity, 2011 © 2011 Wiley Periodicals, Inc.

We present a new method for decomposing a social network into an optimal number of hierarchical subgroups. With a perfect hierarchical subgroup defined as one in which every member is automorphically equivalent to each other, the method uses the REGGE algorithm to measure the similarities among nodes and applies the k-means method to group the nodes that have congruent profiles of dissimilarities with other nodes into various numbers of hierarchical subgroups. The best number of subgroups is determined by minimizing the intra-cluster variance of dissimilarity subject to the constraint that the improvement in going to more subgroups is better than a network whose n nodes are maximally dispersed in the n-dimensional space would achieve. We also describe a decomposability metric that assesses the deviation of a real network from the ideal one that contains only perfect hierarchical subgroups. Four well known network data sets are used to demonstrate the method and metric. These demonstrations indicate the utility of our approach and suggest how it can be used in a complementary way to Generalized Blockmodeling for hierarchical decomposition.