Tag Archives: Technology Roadmapping

Technology Roadmapping Using Text Mining: A Foresight Study for the Retail Industry (FULL-TEXT)

Technology roadmapping is a widely accepted method for offering industry foresight as it supports strategic innovation management and identifies the potential application of emerging technologies. While roadmapping applications have been implemented across different technologies and industries, prior studies have not addressed the potential application of emerging technologies in the retail industry. Furthermore, few studies have examined service-oriented technologies by a roadmapping method. Methodologically, there are limited roadmapping studies that implement both quantitative and qualitative approaches. Hence, this article aims to offer a foresight for future technologies in the retailing industry using an integrated roadmapping method. To achieve this, we used a sequential method that consisted of both text mining and an expert review process. Our results show clear directions for the future of emerging technologies as the industry moves toward unmanned retail operations. We generate eight clusters of technologies and integrate them into a roadmapping model, illustrating their links to the market and business requirements. Our study has a number of implications and identifies potential bottlenecks between the integration of front- and back-end solutions for the future of unmanned retailing.

10.1109/TEM.2021.3068310 or FULL-TEXT found HERE

Author(s): Sercan Ozcan; Amir Homayounfard; Christopher Simms; Jahangir Wasim
Organization(s): University of Portsmouth, University of Essex, Robert Gordon University
Source: IEEE Transactions on Engineering Management
Year: 2021

Tech mining to validate and refine a technology roadmap

This study uses ‘tech mining’ (extracting intelligence from R&D data) to validate and refine the content of a particular section of a landmark roadmap of nanotechnology for aeronautics. We utilize topical content from publications and patents to analyze the developmental status of nanocomposite coating technologies. This enables us to validate predictions made by specialists, as presented in the target technology roadmap section. Moreover, we augment that roadmap section by providing additional information on nanocomposite-related emerging technologies. This study supports use of tech mining as a means to inform technology roadmapping, both when creating a new roadmap and to check progress.

https://doi.org/10.1016/j.wpi.2018.07.003

Author(s): Geet Lahoti, Alan L. Porter, Chuck Zhang, Jan Youtie, Ben Wang
Organization(s): Georgia Institute of Technology
Source: World Patent Information
Year: 2018

Tracing the system transformations and innovation pathways of an emerging technology: Solid lipid nanoparticles

Accurately evaluating opportunities in new and emerging science and technologies is a growing concern. This study proposes an integrated framework for identifying a range of potential innovation pathways and commercial applications for solid lipid nanoparticles – one particularly promising contender within the field of nano-enabled drug delivery. Several text mining techniques – term clumping, SAO technique, and net effect analysis – as well as technology roadmapping, are combined with expert judgment to identify the main areas of R&D in this field, and to track their evolution over time. Through analysis, data from multiple sources, including research publications, patents, and commercial press, reveal possible future applications and commercialization opportunities for this emerging technology. We find that research is moving away from materials and delivery outcomes toward clinical applications. The most promising markets are pharmaceuticals and cosmetics; however, the “time-to-market” is much shorter for cosmetics than it is for pharmaceuticals.

The most significant contributions of this paper have been highlighted as follows. One innovation is extracting the intelligence from three kinds of data sources after in-depth considering their characteristics and matching with the features of different technology development stages to identify innovative research topics. The second one is combining SAO technique with net effect analysis to identify what the evolutionary links between research topics are, and then to use TRM to visualize the evolution of the main areas of R&D over time.

https://doi.org/10.1016/j.techfore.2018.04.026

Author(s):Xiao Zhou, Lu Huang, Alan Porter, Jose M.Vicente-Gomila
Organization(s): Xidian University, Beijing Institute or Technology
Source: Technological Forecasting and Social Change
Year: 2018

A nanotechnology roadmapping study for the Turkish defense industry

Technologies are constantly developed to address new demands and provide further opportunities. Owing to a number of potential application areas of nanotechnologies within this sector, the purpose of this study is to take defense as a case and propose a strategic roadmap for the use of nanotechnologies in the Turkish Defense Industry.

The study presented in this paper uses a bibliometric analysis of the most cited publications in the past decade with the aim of identifying the trends in the development of nanotechnology. Interviews were carried out with experts based on the featured words of bibliometric analysis (nanoparticles, nanostructure, self-assembly, drug delivery, graphene, etc.) to reveal the commercialization time of nanotechnology products and applications. After that, a survey was carried out with engineers for determining the possible emergence time of nanotechnology applications and/or products used in military up to year 2035. Finally, a roadmap was created based on the obtained data from bibliometric analysis, interviews and survey results.

Research limitations/implications
Because of the chosen research approach, the research results may lack generalizability. Therefore, researchers are encouraged to test the proposed propositions further. Interviews and surveys have limitation with the bounded rationality of corresponders.

Practical implications
The paper proposed a nanotechnology roadmap for the defense sector with a data-led foresight practice.

Originality/value
Performing such a study is considered to be crucial for the armies of developed and developing countries, so that the military sector also avails benefits from this revolutionary technology. Quantitative and qualitative methods were mixed for developing the roadmap.

http://www.emeraldinsight.com/doi/pdfplus/10.1108/FS-06-2017-0020

Author(s): Ayhan Aydogdu, Serhat Burmaoglu, Ozcan Saritas, Serhat Cakir
Organization(s): Turkish Armed Forces Foundation, Defense Sciences Institute, Higher School of Economics, Orta Dogu Teknik Universitesi
Source: Foresight
Year: 2017

TeknoRoadmap, an approach for depicting emerging technologies

One of the biggest challenges for current enterprises is the adoption of emerging technologies as soon as these provide competitive improvements. In this sense, several types of technology forecasting and surveillance activities are present in their daily activity. From the academic point of view, technology forecasting activities involve the combination of methods of a diverse nature, with which the technology is depicted and its potential future paths are discussed. Within this conceptual framework, the present work aims at describing a novel approach, known as TeknoRoadmap, which combines bibliometrics and technology forecasting methods to depict emerging technologies. Thus, this contribution aims to widen the scope compared to those provided by previous works within the field, and to that end, the depiction of emerging technologies is provided based on two main elements, namely: the profile of the research activity; and a complete technology roadmap. The approach combines consolidated methods such as text mining and roadmapping, and novel ones such as web content mining, with special attention given to forecasting activities. The work provides a detailed description of the steps on which the approach is structured, as well as the results of one specific application to a cutting edge emerging technology: cloud computing.

http://www.sciencedirect.com/science/article/pii/S0040162516304310

Author(s): Iñaki Bildosola,Rosa María Río-Bélver, Gaizka Garechana, Ernesto Cilleruelo
Organization(s): University of the Basque Country (UPV/EHU))
Source: Technology Forecasting & Social Change
Year: 2017

Technology roadmapping for competitive technical intelligence

Understanding the evolution and emergence of technology domains remains a challenge, particularly so for potentially breakthrough technologies. Though it is well recognized that emergence of new fields is complex and uncertain, to make decisions amidst such uncertainty, one needs to mobilize various sources of intelligence to identify known–knowns and known–unknowns to be able to choose appropriate strategies and policies. This competitive technical intelligence cannot rely on simple trend analyses because breakthrough technologies have little past to inform such trends, and positing the directions of evolution is challenging. Neither do qualitative tools, embracing the complexities, provide all the solutions, since transparent and repeatable techniques need to be employed to create best practices and evaluate the intelligence that comes from such exercises. In this paper, we present a hybrid roadmapping technique that draws on a number of approaches and integrates them into a multi-level approach (individual activities, industry evolutions and broader global changes) that can be applied to breakthrough technologies. We describe this approach in deeper detail through a case study on dye-sensitized solar cells. Our contribution to this special issue is to showcase the technique as part of a family of approaches that are emerging around the world to inform strategy and policy.d to inform strategy and policy.

Author(s): Yi Zhang, Douglas KR Robinson, Alan L Porter, Donghua Zhu, Guangquan Zhang, Jie Lu
Organization(s): Beijing Institute of Technology,  Université de Paris-Est
Source: Technological Forecasting and Social Change
Year: 2015

Topic analysis and forecasting for science, technology and innovation: Methodology with a case study focusing on big data research

Highlights

  • Data-driven clustering approach to group topics with high accuracy
  • Similarity measure approach to trace the interaction between topics in time series
  • Analyzing changes of TFIDF values of related topics to predict future trends
  • Technology Roadmapping to blend historical analysis and expert-based forecasting

The number and extent of current Science, Technology & Innovation topics are changing all the time, and their induced accumulative innovation, or even disruptive revolution, will heavily influence the whole of society in the near future. By addressing and predicting these changes, this paper proposes an analytic method to (1) cluster associated terms and phrases to constitute meaningful technological topics and their interactions, and (2) identify changing topical emphases. Our results are carried forward to present mechanisms that forecast prospective developments using Technology Roadmapping, combining qualitative and quantitative methodologies. An empirical case study of Awards data from the United States National Science Foundation, Division of Computer and Communication Foundation, is performed to demonstrate the proposed method. The resulting knowledge may hold interest for R&D management and science policy in practice.

http://www.sciencedirect.com/science/article/pii/S0040162516000160

Author(s): Yi Zhang, Guangquan Zhang, Hongshu Chen, Alan L. Porter, Donghua Zhu, Jie Lu
Organization(s): University of Technology Sydney, Georgia Institute of Technology, Beijing Institute of Technology
Source: Technological Forecasting and Social Change
Year: 2016

Identification of technology development trends based on subject-action-object analysis: The case of dye-sensitized solar cells

Identification of technology development trends is essential for supporting decision makers in forecasting and identifying related innovation activities and industrial growth. Different from the traditional technology development trends based on keyword-based quantitative methods, which usually predict trends by finding key technologies without showing how to develop them, our method allows the identification of future direction and industry goal for the technology domain and shows detailed paths for achieving them. Thus, our method has constructed technology roadmapping (TRM) with seven layers (material, technology, influencing factor, component, product, goal, and future direction) on the basis of subject–action–object analysis. The detailed paths for developing this as a trend can be shown by the interaction among these TRM elements. In addition, the method also sets three indicators as a discriminating standard to find key players that can support the trend by engaging technological innovation scenarios. The case of a dye-sensitized solar cell (DSSC) is exemplified to illustrate the detailed procedure of our method. The results reveal the development trends in the field of DSSCs, the detailed paths to achieve them, and key countries that support them.

http://www.sciencedirect.com/science/article/pii/S004016251500133X

Author(s):  Xuefeng Wang, Pengjun Qiu, Donghua Zhu, Liliana Mitkova, Ming Lei, Alan L. Porter
Organization(s): Beijing Institute of Technology, Georgia Tech
Source: Technological Forecasting and Social Change
Year: 2015

Identification of technology development trends based on subject–action–object analysis: The case of dye-sensitized solar cells

Identification of technology development trends is essential for supporting decision makers in forecasting and identifying related innovation activities and industrial growth. Different from the traditional technology development trends based on keyword-based quantitative methods, which usually predict trends by finding key technologies without showing how to develop them, our method allows the identification of future direction and industry goal for the technology domain and shows detailed paths for achieving them. Thus, our method has constructed technology roadmapping (TRM) with seven layers (material, technology, influencing factor, component, product, goal, and future direction) on the basis of subject–action–object analysis. The detailed paths for developing this as a trend can be shown by the interaction among these TRM elements. In addition, the method also sets three indicators as a discriminating standard to find key players that can support the trend by engaging technological innovation scenarios. The case of a dye-sensitized solar cell (DSSC) is exemplified to illustrate the detailed procedure of our method. The results reveal the development trends in the field of DSSCs, the detailed paths to achieve them, and key countries that support them.

http://www.sciencedirect.com/science/article/pii/S004016251500133X

Author(s): Xuefeng Wang, Pengjun Qiu, Donghua Zhu, Liliana Mitkova, Ming Lei, and Alan L. Porter
Organization(s): Beijing Institute of Technology, University Paris-Est Marne la Vallée, and Georgia Institute of Technology
Source: Technological Forecasting and Social Change
Year: 2015

Forecasting the Big Services Era: Novel Approach Combining Statistical Methods, Expertise and Technology Roadmapping

This paper aims at proposing a novel approach to gathering and structuring information concerning an emerging technology, generating a relevant profile, identifying its past evolution, forecasting the short and medium-term evolution and integrating all of the elements graphically into a hybrid roadmap. The approach combines four families of technological forecasting methods, namely: Statistical Methods in terms of Bibliometrics and Data Mining; Trend Analysis; Descriptive Methods in terms of Technological Roadmapping; and Expertise. Its future application to forecast the evolution of emerging IT trends in current entities, which are creating the Big Services era, is proposed as future work.

http://link.springer.com/chapter/10.1007/978-3-319-14078-0_42#

Author(s): Iñaki Bildosola, Rosa Rio-Bélver, Ernesto Cilleruelo
Organization(s): University of the Basque Country UPV/EHU
Source: Enhancing Synergies in a Collaborative Environment [Springer International Publishing] Lecture Notes in Management and Industrial Engineering
Year: 2015