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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.

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.

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

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.

Many areas of academic and industrial work make use of the notion of a ‘technology’. This paper attempts to reduce the ambiguity around the definition of what constitutes a ‘technology’ by extension of a method described previously that finds highly relevant patent sets for specified technological fields. The method relies on a less ambiguous definition that includes both a functional component and a component consisting of the underlying knowledge in a technological field to form a two-component definition. These two components form a useful definition of a technology that allows for objective, repeatable and thus comparable analysis of specific technologies. 28 technological domains are investigated: the extension of an earlier technique is shown to be capable of finding highly relevant and complete patent sets for each of the technologies. Overall, about 500,000 patents from 1976 to 2012 are classified into these 28 domains. The patents in each of these sets are not only highly relevant to the domain of interest but there are relatively low numbers of patents classified into any two of these domains (total patents classified in two domains are 2.9 % of the total patents and the great majority of patent class pairs have zero overlap with a few of the 378 patent class pairs containing the bulk of the doubly listed patents). On the other hand, the patents within a given domain cite patents in other domains about 90 % of the time. These results suggest that technology can be usefully decomposed to distinct units but that the inventions in these relatively tightly contained units depend upon widely spread additional knowledge., SUTD-MIT International Design Centre (IDC)

Public policy requires public support, which in turn implies a need to enable the public not just to understand policy but also to be engaged in its development. Where complex science and technology issues are involved in policy making, this takes time, so it is important to identify emerging issues of this type and prepare engagement plans. In our horizon scanning exercise, we used a modified Delphi technique [1]. A wide group of people with interests in the science and policy interface (drawn from policy makers, policy adviser, practitioners, the private sector and academics) elicited a long list of emergent policy issues in which science and technology would feature strongly and which would also necessitate public engagement as policies are developed. This was then refined to a short list of top priorities for policy makers. Thirty issues were identified within broad areas of business and technology; energy and environment; government, politics and education; health, healthcare, population and aging; information, communication, infrastructure and transport; and public safety and national security.Public policy requires public support, which in turn implies a need to enable the public not just to understand policy but also to be engaged in its development. Where complex science and technology issues are involved in policy making, this takes time, so it is important to identify emerging issues of this type and prepare engagement plans. In our horizon scanning exercise, we used a modified Delphi technique [1]. A wide group of people with interests in the science and policy interface (drawn from policy makers, policy adviser, practitioners, the private sector and academics) elicited a long list of emergent policy issues in which science and technology would feature strongly and which would also necessitate public engagement as policies are developed. This was then refined to a short list of top priorities for policy makers. Thirty issues were identified within broad areas of business and technology; energy and environment; government, politics and education; health, healthcare, population and aging; information, communication, infrastructure and transport; and public safety and national security.

Enhancing the travel experience has become a crucial consideration for transportation companies to promote differentiation and customer loyalty. Therefore, transport planners, providers and manufacturers in general are becoming aware of the significance of understanding the passenger experience better, in order to improve transit policies, management and vehicles. The holistic perspective of the travel experience is conceptualized as involving: (1) a thorough set of passenger internal responses (e.g. cognitive and emotional) that are driven by experience factors, some of which are (2) aspects that are not in complete control of the transportation provider, such as waiting areas or the social environment, during (3) all the moments before, throughout and after the trip. Although transportation research has studied the different aspects of transportation quality, empirical studies with such a broad approach to the travel experience and its impact on loyalty are still scarce. This article takes a scale development approach to conceptualize, develop and test a multiple-item scale for measuring the travel experience from the defined holistic perspective, analyzing its perceptual dimensions and outcomes based on a quantitative study with 1226 passengers of a mid-distance bus transportation service. The travel experience scale demonstrates good psychometric properties and consists of 28 items aggregated into seven dimensions or experience factors: individual space, information provision, staff's skills, social environment, vehicle maintenance, off-board facilities, and ticket line service. The study shows that all seven experience factors have a significant impact on customer cognitive, emotional and behavioral responses to the transportation service, highlighting the importance of a broad approach to the study and management of the travel experience. The classical dimensions of individual comfort and vehicle maintenance are the ones with the strongest impact on experience outcomes, showing that transportation providers should maintain a strong focus on providing a good core service. However, other factors such as the social environment have an influence on emotions, which in turn affect loyalty to the transportation provider. These results show the need for a careful study and management of the different aspects of the travel experience, and an integrated design and management of the transport system as a whole.

In the original publication of the article, the data in Table 6 ‘‘Comparison of the different search methods including the adjusted HKC method’’ size and relevancy percentage of the cell in row ‘‘Electric capacitor’’ and column ‘‘Classification selection’’ has been published incorrectly as 9,472 (2 %). It should read as 69,277 (7 %). The correct version of Table 6 is provided below.

The customer experience is important for adding value to firms’ offerings but two challenges arise: the customer experience is increasingly created through interactions with product–service systems (PSSs) and it is formed through all moments of interaction with multiple firms. Incorporating customer experience requirements (ERs) into the design of PSSs is therefore a complex task. To address this challenge, this paper presents an extension of the Kansei engineering method consisting of two components. First, the extension includes an in-depth study of the customer experience from a holistic perspective that informs the design process. Second, it involves the active participation of multidisciplinary experts from the different partner companies that together enable the PSS offering. An application of this new extension is presented for mid-distance bus trips, involving passengers, a vehicle manufacturing and a transport provider company. The research followed design-science guidelines using an action resea...

This paper presents a relatively simple, objective and repeatable method for selecting sets of patents that are representative of a specific technological domain. The methodology consists of using search terms to locate the most representative international and US patent classes and determines the overlap of those classes to arrive at the final set of patents. Five different technological fields (computed tomography, solar photovoltaics, wind turbines, electric capacitors, electrochemical batteries) are used to test and demonstrate the proposed method. Comparison against traditional keyword searches and individual patent class searches shows that the method presented in this paper can find a set of patents with more relevance and completeness and no more effort than the other two methods. Follow on procedures to potentially improve the relevancy and completeness for specific domains are also defined and demonstrated. The method is compared to an expertly selected set of patents for an economic domain, and is shown to not be a suitable replacement for that particular use case. The paper also considers potential uses for this methodology and the underlying techniques as well as limitations of the methodology., SUTD-MIT International Design Center

Technological improvement trends such as Moore's law and experience curves have been widely used to understand how technologies change over time and to forecast the future through extrapolation. Such studies can also potentially provide a deeper understanding of R&D management and strategic issues associated with technical change. However, such uses of technical performance trends require further consideration of the relationships among possible independent variables — in particular between time and possible effort variables such as cumulative production, R&D spending, and patent production. The paper addresses this issue by analyzing performance trends and patent output over time for 28 technological domains. In addition to patent output, production and revenue data are analyzed for the integrated circuits domain. The key findings are:1.Sahal's equation is verified for additional effort variables (for patents and revenue in addition to cumulative production where it was first developed).2.Sahal's equation is quite accurate when all three relationships — (a) an exponential between performance and time, (b) an exponential between effort and time, (c) a power law between performance and the effort variable — have good data fits (r2>0.7).3.The power law and effort exponents determined are dependent upon the choice of effort variable but the time dependent exponent is not.4.All 28 domains have high quality fits (r2>0.7) between the log of performance and time whereas 9 domains have very low quality (r20.9), the exponential relationship is not perfect and it is thus best to consider these relationships as the foundation upon which more complex (but nearly exponential) relationships are based.Overall, the results are interpreted as indicating that Moore's law is a better description of longer-term technological change when the performance data come from various designs whereas experience curves may be more relevant when a singular design in a given factory is considered.