A Patent Analysis for Sustainable Technology Management

Recently, sustainable growth and development has become an important issue for governments and corporations. However, maintaining sustainable development is very difficult. These difficulties can be attributed to sociocultural and political backgrounds that change over time [1]. Because of these changes, the technologies for sustainability also change, so governments and companies attempt to predict and manage technology using patent analyses, but it is very difficult to predict the rapidly changing technology markets. The best way to achieve insight into technology management in this rapidly changing market is to build a technology management direction and strategy that is flexible and adaptable to the volatile market environment through continuous monitoring and analysis. Quantitative patent analysis using text mining is an effective method for sustainable technology management. There have been many studies that have used text mining and word-based patent analyses to extract keywords and remove noise words. Because the extracted keywords are considered to have a significant effect on the further analysis, researchers need to carefully check out whether they are valid or not. However, most prior studies assume that the extracted keywords are appropriate, without evaluating their validity. Therefore, the criteria used to extract keywords needs to change. Until now, these criteria have focused on how well a patent can be classified according to its technical characteristics in the collected patent data set, typically using term frequency–inverse document frequency weights that are calculated by comparing the words in patents. However, this is not suitable when analyzing a single patent. Therefore, we need keyword selection criteria and an extraction method capable of representing the technical characteristics of a single patent without comparing them with other patents. In this study, we proposed a methodology to extract valid keywords from single patent documents using relevant papers and their authors’ keywords. We evaluated the validity of the proposed method and its practical performance using a statistical verification experiment. First, by comparing the document similarity between papers and patents containing the same search terms in their titles, we verified the validity of the proposed method of extracting patent keywords using authors’ keywords and the paper. We also confirmed that the proposed method improves the precision by about 17.4% over the existing method. It is expected that the outcome of this study will contribute to increasing the reliability and the validity of the research on patent analyses based on text mining and improving the quality of such studies.

PurposeApple is a representative company of technological innovation (TI) and management. It has launched new and innovative products since 1977, and many companies and business schools around the world have attempted to learn about the success story of Apple's innovation. However, most previous research works on Apple's innovation have been based on qualitative approaches such as experts' opinions. Such studies offer a subjective point of view. By contrast, in this paper the authors aim to study the TI and forecasting of Apple by analyzing its patent applications, which is an objective approach to examining the innovation of Apple from a technological perspective.Design/methodology/approachTI is an important issue concerning technology management for companies and governments. To examine Apple's TI, the authors analyze all applied patents and construct analytical models according to three approaches. First, they build statistical models using the time series regression and multiple linear regression methods to create a technology map. Second, they cluster all Apple's patents to find its vacant technology domain. Lastly, they use social network analysis to search for technologies central to Apple's future.FindingsThe authors' study shows the technological trends and relations between Apple's technologies. This research finds vacant technology areas and central technologies for Apple's TI.Practical implicationsUsing statistical and machine learning methods, the authors analyze all Apple's patents in order to predict the firm's future technologies. This research contributes to examining the TI of Apple. Therefore, the results of the patent analysis can highlight the technological opportunities for Apple's TI.Originality/valueTraditional TI models have been based on qualitative methods. Previous investigations of Apple's TI have also relied on traditional analytical approaches. In this paper, however, the authors develop a quantitative and objective approach for examining Apple's TI.

In a connected world, where successful technological development depends increasingly on collaboration between different partners, effectively utilizing patent data analytics has huge, yet unexploited potential. Given suitable analytics solutions, this high-quality data can be used for decision making on a strategic level in all kind of organizations. The paper contributes to expanding the field of patent analytics for more effective exploitation of the worldwide largest repository of technological information. We do this by developing a domain level technology roadmap following a three-stage technology roadmapping and problem-solving approach. Firstly, from desk research and expert discussions, we identified five main problem themes in the patent analytics field (patent data, database interconnectedness, data analysis, data visualisation, and patent quality). Secondly, we verified and expanded these problem themes through an online survey with 70 respondents. Thirdly, we explored the future direction of the field through a workshop, with inputs from the preparatory stages above, with 28 leading experts. The approach served to develop a technology roadmap to facilitate collaboration and coordinated action within the patent analytics community. We identify thirteen priority technologies, such as artificial intelligence and neural networks, fifteen complementary technologies, such as block chain, and five new technologies, such as technologies for linking databases, to be adopted in the field and are important in overcoming the problems. We also identify twenty-one enablers for potential breakthrough progress of the field that cluster around four themes: technology development cycles and methodologies; legislation and standardisation for patent data quality; continuous professional development; and cooperation between industry and academia. Key next actions include the generation of use cases for different users, the standardization and harmonization of patent ontologies and the implementation of reporting standards.

Technology developments change society, and society demands new and innovative technology developments. We analyze technology to understand society and technology itself. Much research related to technology analysis has been introduced in various fields. Most of it has been on patent analysis. This is because detailed and accurate results of research and development are patented. In this paper, we study a new patent analysis method based on the count data model and Bayesian regression analysis. Using the count data model, we analyzed the technological keywords extracted from the collected patent documents. We used the prior distribution of Bayesian statistics to reflect the experience and knowledge of the relevant technological experts in the analysis model. Moreover, we applied the proposed model to find sustainable technologies. Finding and developing sustainable technologies is an important activity for companies and research institutes to maintain their technological competitiveness. To illustrate how our modeling could be applied to real domains, we carried out a case study using the patent documents related to artificial intelligence.

Notes from the Editors: Restructuring the Journal of Operations Management

This paper utilizes a technology road-mapping approach to demonstrate how a traditional technology management process can be applied to improve planning practices for technology-driven service innovations. With location based services (LBS) as the focus, the paper explores business, market, product and services drivers in developing the technology roadmap. Thus, the study demonstrates that technology management theory and processes from the product domain may be usefully applied to the management of technology-driven service innovations. The case study analysis identified service drivers including security, privacy and mobility as important factors for LBS success. Potentially disruptive service innovations resulting from the convergence of the computer and wireless industries are explored.

In today’s era of increasing environmental awareness, organizations need to consider the environmental economics and management perspective in addition to quality performance. Recent societal changes have led to a significant digital revolution that has made it challenging for industrialized nations to manage technology transfer. Organizations must integrate digitalization, technology, culture, and environmental sustainability to survive in this highly competitive climate. This study examines the relationship between digitalization and technology management and their impact on Total Quality Management (TQM) performance in Pakistani businesses, considering the environmental economics and management perspective. A quantitative approach was taken, and senior executives from the public and private sectors were surveyed to obtain information. The data was analyzed using SMART PLS 3, which utilized Partial Least Squares Structural Equation Modeling (PLS-SEM). The study found that digitalization and technology management significantly enhanced TQM performance, with organizational agility mediating and organizational culture moderating. The organizational agility also played a crucial role in mediating the relationship between technology management and TQM performance. The findings of this study offer valuable insights for quality management practitioners and policymakers, highlighting the importance of incorporating environmental economics and management practices into an overall quality performance.

A technology roadmap (TRM) links technologies with a company's strategic objectives and so supports acquisition of required technologies in advance of needs. It is a powerful tool for strategic planning and technology management. Because technology is changing rapidly and market competition is fierce, the role of aTRMis becoming increasingly important. To support the role of aTRM, many firms and governments that use roadmapping are becoming interested in reducing costs while retaining objectivity duringTRMdevelopment. One suggestion to achieve these goals is to use the keyword‐based quantitative approach to creating aTRM, but the information provided by the approach is limited because of the characteristics of keyword information. To solve this limitation, this research uses the concept of ‘function’ to support quantitative analysis for developing aTRM. The concept of function can provide information on the uses and purposes of a technology. To represent a function, a subject–action–object structure is commonly used. The suggested approach allows research and development (R&D) managers to extend the views of product and technology during development of aTRM. In addition, by reducing the time required to develop aTRM, the proposed approach supports quick and accurate decision‐making byR&Dmanagers.

Today, there is much concern about the effect of our computers on the environment. In addition, the issue of power and cooling is a mounting anxiety. These concerns would not seem so important if there were only a few computers in our campuses, but today there are millions of computers in use at the data centers, offices, and computer laboratories across campuses. To put this in perspective: a typical desktop computer can consume 200-300W of power. This results in emission of about 220Kg of CO2/annum. By using more efficient systems, the level of CO2 produced by a typical desktop computer could be reduced by 75%. Moreover, a computer laboratory with 50 computers can generate about 10KW of heat requiring extra cooling. Rapid growth in energy costs and increasing dependency on sustainable computing increasingly require 3R (Reduce, Reuse, Recycle) endeavors in our information technology operations and management of our information technology resources. From the viewpoints of environmental preservation and resource utilization, managing e-waste and eco-computing is becoming an important target for higher education institutions worldwide. Furthermore, tackling eco-friendly solutions on campus environments takes a group effort and starts at the Information Technology division. In this report we review major eco-responsible initiatives and detail moves towards more efficient and sustainable technologies. In addition, we look at ways to assess the environmental impact of our data centers and eco-friendly solutions.

Technological progress exerts a decisive influence on corporate strategic decision-making, particularly within the rapidly evolving domain of science and technology. Early identification and adoption of emerging technological trends are pivotal for enterprises to sustain competitive advantage and market position. However, many innovative companies fail to fully leverage the potential of their products and technologies due to the absence of a systematic approach. To counter this challenge, large corporations have established forward-looking departments dedicated to forecasting future trends and innovation. Despite this, the current predictive process integrates human intelligence with machine learning methods, and the visual analysis that combines these two forms of intelligence holds immense potential. This paper introduces an integrated method that combines information visualization, trend mining, and interactive design, aimed at supporting users in exploring, detecting, and identifying emerging technological trends within complex datasets. The method facilitates in-depth trend analysis and extraction of meaningful insights from data through an interactive visual representation system. Moreover, the integration of interactive design throughout the analytical process is crucial for supporting the analytical process in technology and innovation management [8]. A literature review, trend visualization, interactive visualization, and interactive design methods are essential for understanding the context of technology management and visualization analysis systems. The interactive design approach places special emphasis on the central role of users in the design process, ensuring that the system meets user needs and supports effective identification and utilization of emerging technological trends.The research findings indicate that the integration of human intelligence and machine learning methods can enhance the accuracy and efficiency of predicting future technological trends. The interactive design-based method proposed in this paper not only augments and expands previous methods of technology and design management trend analysis but also introduces novel interactive designs, providing more suitable interactive methods for technology foresight and innovation detection. These methods and tools enable enterprises to more effectively respond to market changes, grasp technological trends, and make informed strategic decisions.

Patents, which are public documents organized in standard formats, are regarded as a valuable source of technical and commercial knowledge about innovative technical processes and activities. Putting roadmapping techniques together with patent analysis can increase the objectivity and reliability of a technology roadmap, while using patent analysis restricted to technological information together with roadmapping techniques can ensure that a more valuable breadth of strategic information is extracted from patents. The two techniques can complement each other in the strategic planning process. This chapter describes how to apply patent analysis for roadmapping so that the patent analysis supports decision making at various points in the roadmapping process.

Introduction A mobile application has the potential to involve people with chronic NSLBP in their rehabilitation. To refine the design of a smartphone application for people with chronic NSLBP using mixed quantitative and qualitative approaches. Methods We used a user-centred design approach involving people with chronic NSLBP and healthcare professionals (HCPs). We used a three-step methodology: developing consensus on the features, content, and design of the app; developing a user interface; and usability testing of the app and assessing users’ experience. Transcripts of interviews of users were analyzed by qualitative content analysis. Results A total of 18 people (aged 45 [23–53] years old) with chronic NSLBP, and 7 HCPs (aged 29.5 [25–55] years old) involved in NSLBP management were interviewed. The overall experience of using the smartphone eLombactif app was initially assessed. Then, with close-ended questions we evaluated users’ judgements on the content, its presentation and navigation. Finally, we asked for suggestions: “application content and functionality” and “content presentation” from participants regarding the use and development of the app analyzed by a qualitative methodology. Conclusions This study described how we refined the design of our application for people with chronic NSLBP using a qualitative and quantitative approaches. This methodology allows for deepening the knowledge of the needs and expectations of potential users by measuring their user experience. IMPLICATIONS FOR REHABILITATION Non-specific low back pain (NSLBP) is a major global public health issue leading to considerable economic cost and is primarily responsible for pain and disability. Mobile application has the potential to involve people with chronic NSLBP in their rehabilitation. This study described how we refined the design of our application for people with chronic NSLBP using a qualitative and quantitative approaches.

Objective: This study aims to investigate the challenges faced by University Publishers in the Northeast of Brazil in keeping up with technological advancements in the publishing market. It proposes a technological roadmap (2007–2022) to guide the adoption of an appropriate business model for these institutions. Design/Method/Approach: A qualitative and exploratory research approach was adopted, based on the analysis of patents from international and national databases, along with scientific articles. Boolean searches were conducted using platforms such as Espacenet, Questel Orbit, IEEE Xplore, and iSys. The findings were organized into a technological roadmap structured by timeframes (short, medium, and long term) to identify future trends. Originality/Relevance: The research provides an original contribution by applying technological foresight to the editorial sector, focusing on University Publishers in the Brazilian Northeast. The proposal of an on-demand digital platform aligns technological innovation with academic missions and market needs. Main Results/Findings: The roadmap results from 2007 to 2022 indicate significant development of digital book sales services, virtual libraries, and electronic shelves. Key trends include self-publishing platforms, app-based access, and integration with mobile devices—revealing a clear shift toward expanding the digital ecosystem for book consumption. Theoretical and Methodological Contributions: The roadmap methodology proved effective for mapping the technological landscape in publishing, offering a structured framework for strategic planning. The study also demonstrates the value of patent analysis as a data source in applied research on innovation. Contributions to Society and Organizations: This research supports the development of viable digital solutions for University Publishers, promoting broader access to academic knowledge and scientific production. It responds to the growing societal need for inclusive, innovative, and accessible publishing practices.

Technology roadmapping: Industrial roots, forgotten history and unknown origins

It is argued that universities in South Africa should, in addition to compensating for the global trend of accelerated change, analyze the demands that will be placed on engineers in the South Africa of the future and adjust their curricula accordingly. It is suggested that the management of technology and technological innovation in particular should be stressed. It is concluded that, in order to produce engineers who can contribute towards building and sustaining a competitive technology base, it is necessary to produce engineers who have a sense of social and environmental responsibility and a wealth-creating mindset.