Using patent information for designing new product and technology: keyword based technology roadmapping

With the rapid change in markets and technologies, it is becoming essential for firms to develop new products constantly. This can most successfully be achieved by using technology roadmaps (TRMs), which are effective tools for connecting product and technology planning. However, TRMs generally tend to overstate the qualitative and expert-dependent knowledge rather than incorporating quantitative and objective information. This paper proposes a new approach where patent data are used in a quantitative methodology to support reliable decision-making in roadmapping processes. In this study, text-mining techniques were utilized to extract the relevant information on which portfolio, co-word, and network analyses were carried out. The results were three types of product-technology maps that can be applied to specific roadmapping steps. The suggested approach is expected to yield useful information about roadmapping, and help improve the overall effectiveness and quality of the technique.     

Leveraging ideas from user innovation communities: using text‐mining and case‐based reasoning

User innovation communities, where end users voluntarily share their ideas about new products or services, have become an important source of innovation. While efforts have been made to extract and develop ideas from these sources, existing studies have largely focused on company‐led efforts to facilitate user participation, rather than on voluntary user discussions within communities themselves. As a remedy, this research proposes to directly target those voluntary ideas from user innovation communities for product/service innovation. Because quantities of textual information within these communities are rather massive, we propose a modified and integrated approach of text‐mining (TM) and case‐based reasoning (CBR). Specifically, by constructing two casebases on ideas and existing products using TM and checking for overlap between the two using CBR, the approach enables the identification of opportunities for innovation and reference products for adaptation. We demonstrate the approach through a case of mobile apps in Apple App Store, and our findings suggest that the approach can help firms and users/developers broaden the source of ideas and leverage them into new product concepts.     

Morphology analysis for technology roadmapping: application of text mining

The practice of technology roadmapping (TRM) has received much attention from researchers and practitioners, to support planning and forecasting in companies and sectors. However, little research has focused on the support of well-organized information for more effective roadmapping and the presentation of in-depth configurations of new products or technology. This paper proposes a roadmapping methodology to assist decision-making by applying a systematic approach based on quantitative data. To this end, key information is extracted from documents such as product manuals and patent documents by text mining, which is then used to identify the morphology of existing products and technology. Morphology analysis (MA) also plays a crucial role in deriving promising opportunities for new development of product or technology by matching product and technology morphology. Therefore, MA-based TRM can enable the effective exploitation of large quantities of significant information that might otherwise be left untapped, supporting innovation by generating a comprehensive set of detailed product and technology configurations. The proposed MA-based TRM approach can be applied to both incremental and radical innovation, supporting both market pull and technology push. The method is illustrated with a detailed example for mobile phones to demonstrate its practical application.     

Emotions and the spatialisation of social relations in text‐based computer‐mediated communication

This paper advances our knowledge of emotions in virtual teams using text‐based computer‐mediated communication. The literature's preoccupation with the absence of physical cues of emotion has meant we lack both an understanding of how emotions are co‐constructed through interaction and an explanation of their role in the social relations of virtual teams. Adopting a communicative view of emotion, we present the findings of a longitudinal study of a virtual team within a transnational collaborative project. We present three aspects of interaction that demonstrate how team members' experience and understanding of the emotions expressed through, and suppressed from, text‐based messages are influenced by the styles and patterns of interaction enabled by technology. Where our three aspects tend towards stasis, we argue that emotion provides a temporal dimension to a process of ‘spatialising’ social relations by connoting what should change, or what should endure, between people.     

基于数据挖掘技术的教学测评

学院为保障教学质量,每学期对教师教学情况进行测评,其中学生的测评结果占教师总测评成绩的70％.通过多年的实证性研究表明;学生教学评价问卷具有很高的可信度,较客观地反映了任课教师的教学效果.由于学生测评数据量较大,又没有分类标准,应用SPSS软件进行聚类分析,可以较好地进行教学效果的等次划分.用关联规则分析教学测评数据可...     

Identifying technology trends for R&D planning using TRIZ and text mining

The current pace of technological development has forced many companies to invest significant capital and resources in research and development (R&D) activities. A systematic and efficient method of identifying technology trends and their evolutionary potentials can help companies guide their R&D planning and wisely allocate their R&D resources. This study proposes a framework combining the evolutionary trends developed by the Theory of Inventive Problem Solving, or Teoriya Reshniya Izobretatelskikh Zadatch (TRIZ) in Russian, with the visualization technique of text mining to systematically identify technology trends from patent documents. As technological information in patent documents is stored almost entirely in text format, the text mining method allows R&D personnel to efficiently identify technology trends and effectively conduct R&D planning. Utilizing text mining method on patents of magnetic random access memory (MRAM) systems and the underlying principles of TRIZ evolutionary trends, this study shows that MRAM includes 10 important technology trends. These trends have almost reached the evolutionary limit phase defined by TRIZ, which means that MRAM is fast becoming a mature technology. Therefore, for businesses that intend to acquire MRAM technology they do not possess, a wise R&D plan may be licensing the technology, buying the technology from others, or participating in a joint venture rather than using in‐house R&D.     

Robust future‐oriented technology portfolios: Black–Litterman approach

We propose a new way of constructing more robust technology portfolios to overcome the weaknesses of previous technology portfolios based either on the judgments of experts or on quantitative data such as patents. Instead of using historical data, the method of nonlinear forecasting enables us to forecast the future number of patent citations and accordingly, to use the forecast as a quantitative proxy for future returns and risks of technologies. Using the Black–Litterman portfolio model, we improve the accuracy of inputs by combining the future views of experts with the future returns and risks of technologies. As a consequence of this, the portfolio becomes strongly future‐oriented. With our approach, corporate managers use both experts and data more effectively to build robust technology portfolios. In particular, our method is of great help for companies launching new businesses because the method avoids heavy dependency on internal experts with little knowledge about emerging technologies. A company entering the molecular amplification instrument market is exemplified herein.     

An integrative approach to information policy research

The decentralized nature of the evolution of information policy in the USA has resulted in a fragmented approach to both policy development and analysis. A significant problem for information policy research is therefore to provide an integrative outlook for policy analysis. Three models are used to construct a research framework which provides this integrative element. This article presents an example of this framework in a research agenda to examine privacy, software protection and transborder data flow.     

后现代工业化煤矿机械、电子、信息一体化的技术属性

对后现代工业化煤矿机械、电子、信息一体化的技术属性、设计属性、制造属性提出了新的看法。     

Towards an attention‐based view of technology decisions

The importance of technology decisions is widely acknowledged in both research and practice. However, we know little about how companies structure technology decisions from an organizational point of view and how attention is distributed in the course of the decision process in order to identify, process, and transfer information between the organizational units involved. Using the attention‐based view of the firm and 14 qualitative case studies, we present five approaches for organizing technology decisions: (1) centralized decision‐making, (2) busy information bee, (3) double‐blind analysis, (4) moderated expert panel, and (5) coterie approach. On this ground, this paper introduces a new, attention‐based view on technology decisions, which improves the theoretical understanding of organizations and provides guidelines for practitioners in choosing an appropriate organizational configuration in this regard.     

Occupational matching into science and technology jobs—gender‐based differences

Policy to remedy gender disparities in science, technology, engineering and mathematics (STEM) occupations in the US have typically focused on educational achievements. However, an analysis of mid‐career STEM workers reveals that significant gender‐based differences exist in the role that education and other factors play in occupational matching.     

Playing in between: patent brokers in markets for technology

Here we argue that patent brokers do not only stay in between supply and demand of innovation, but play in between executing complex transactions and taking entrepreneurial risk. In doing so, they serve a support function to R&D managers of firms adopting various approaches to technological change. We discuss how economic and sociological theories explain brokerage and its existence. Our qualitative analysis of the current practice of patent brokerage in the United States finds some evidence in support of such arguments, and moreover helps us reach a taxonomy of brokerage. We conclude with our own proposition, suggesting that even in very dense environments, the bridging role of intellectual property intermediaries is that of market makers, who leverage their specific investment to play in between technology demand and supply.     

Robust Testing of the Utility‐based High‐technology Product Sales Forecasting Models Proposed by Decker and Gnibba‐Yukawa (2010)

Decker and Gnibba‐Yukawa (2010) propose an elegant utility‐based model for forecasting the sales of high‐technology products and suggest that the model yields forecasts that are highly accurate. However, this finding is based on forecasts for a total of only six holdout observations shared across three products. This number of observations is insufficient for reliable inferences to be drawn about the accuracy of a method and the use of such a small data set runs counter to an accepted principle of forecast evaluation. The authors’ proposed model was tested on more extensive data and sensitivity analysis applied to the results. No evidence was found that the utility‐based model could outperform a relatively simple extrapolative model despite the much greater effort involved in applying the proposed model. In addition, the utility‐based model is only applicable for forecasting sales during a narrow interval in a product's life cycle and requires several periods of historic sales data before it can be implemented. It also depends heavily on the accurate estimates of parameters that are determined outside the model (and which may depend on difficult judgments by managers) and assumes that consumers or households will only purchase the product once between the launch date and the forecast horizon. In light of this, it is argued that the utility‐based model is likely to have limited usefulness as a sales forecasting tool.     

De‐escalation Mechanisms in High‐technology Product Innovation

Many decision‐makers struggle to reduce commitment to failing endeavors. While de‐escalation mechanisms have been documented and tested in information technology, accounting, psychology, and organizational behavior, little work has addressed de‐escalation in innovation. This study identifies and examines the applicability of de‐escalation mechanisms specifically in new product development (NPD) projects. Initially, we conducted an extensive literature review to identify de‐escalation mechanisms found in research across different academic disciplines. Subsequently, we conducted a qualitative study using semistructured interviews to gather primary data. In total, using a sample of organizations that compete in high‐technology industries, 31 managers and engineers in 15 NPD projects that were terminated prior to completion were interviewed regarding mechanisms used to de‐escalate commitment to failing new product innovation projects. Several mechanisms reportedly used for innovation projects parallel those identified in the previous literature. More importantly, the authors uncover novel and previously undocumented ways to discontinue or redirect poorly performing projects. Specifically, internal competitions, feature‐level de‐escalation, continual assumption assessment, benchmarking, roadmaps, and comprehensive product testing are particularly well suited for innovation projects. These findings extend the body of extant literature on de‐escalation of commitment to include innovation, notably in high‐technology settings. The study also highlights that organizations may want to accept or even encourage failure, thereby increasing the efficacy of resource use. Implications for further research and practice are offered.     

Resource‐based strategy and managerial power in networks of internationally dispersed technology units

A linking of the Resource Based View of the firm, Resource Dependency Theory and the Vroom‐Yetton model of leadership is used to show that when important technical (R&D) resources are located offshore for strategic and efficiency reasons, resource‐based power goes with them. The extra‐national technology units that embody those strategically important resources should be managed with inclusive methods that respect that power shift. Theoretical, empirical and managerial implications are drawn from this analysis. Copyright © 2001 John Wiley & Sons, Ltd.     

On the development and application of a self–organizing feature map–based patent map

Recently, the range of R&D management has expanded to include management of technological assets such as technology information, product/process data, and patents. Among others, patent map (PM) has been paid increasing attention by both practitioners and researchers alike in R&D management. However, the limitation of conventional PM has been recognized, as the size of patent database becomes voluminous and the relationship among attributes becomes complex. Thus, more sophisticated data–mining tools are required to make full use of potential information from patent databases. In this paper, we propose an exploratory process of developing a self–organizing feature map (SOFM)–based PM that visualizes the complex relationship among patents and the dynamic pattern of technological advancement. The utility of SOFM, vis–à–vis other tools, is highlighted as the size and complexity of the database increase since it can reduce the amount of data by clustering and visualize the reduced data onto a lower–dimensional display simultaneously. Specifically, three types of PM, technology vacuum map, claim point map, technology portfolio map, are suggested. The proposed maps may be used in monitoring technological change, developing new products, and managing intellectual property.     

Identification of intangible assets in knowledge‐based organizations using concept mapping techniques

This paper proposes a procedure for identifying the intangible assets that generate value to knowledge‐intensive organizations using concept mapping techniques. Concept mapping is a form of structured conceptualization that incorporates and processes the opinion of a set of experts. A double statistical treatment consisting of a multidimensional scaling analysis and a cluster analysis is applied to a set of data provided by experts to obtain the results, which are presented in the form of maps. As a case study, the social and legal departments in a Spanish university were analyzed. As a result, 60 items referring to different intangible assets of these departments were identified and grouped into 10 clusters, and they were in turn grouped in regions corresponding to the three basic components of intellectual capital: human capital, structural capital and relational capital. The evaluation of the relative importance of each of them leads to the preeminent position of the structural capital.