Disruptive Technology Research Articles

Age-related hearing loss and "hearables": An agenda for moral considerations.

Rapid advances in digital hearing technologies, also known as hearables, are expected to disrupt the direct-to-consumer health market. For older adults with higher incidence of hearing loss, such disruption could reduce hearing problems, increase accessibility to hearing aids, and mitigate related stigmas. This paper delves into the intersection of disruptive innovation and hearables within the realm of biomedical ethics. Through a comprehensive exploration, we shed light on the ethical implications surrounding hearables. By critically evaluating the key ethical advantages and drawbacks, we find that no single concern presents an insurmountable a priori objection to hearables. We conclude with some ideas to maximize the benefits of hearables and further promote opportunities for equitable hearing health.

Limits of bank regulation in financialised capitalism: lessons from the 2023 US banking crisis

ABSTRACT In this article I argue that banks continuously build new business models in financialised capitalism. Market value of these business models is regularly calculated and reported to the investors by investment banking expertise. What the US banking regulators, in their ex-post analysis, declared as unsustainable business models in the three failed banks – Silicon Valley Bank, Signature Bank, and First Republic Bank – in the Spring of 2023, had been promoted by equity analyst expertise as value-maximising ‘niche’ bank business models serving the disruptive technology start-ups after the Covid pandemic. The article argues that bank regulators’ power is severely constrained in financialised capitalism where stock market valuations of banks and equity-based remuneration of the executives are out of regulatory reach. Therefore financial stability mandate of central banks is undermined with significant risk to the society when business models of banks are legitimised by a financialised valuation regime that prioritises shareholder value creation.

A Decade in Blockchain: A Bibliometric Reflection on the Growth and Interdisciplinary Reach of a Disruptive Technology

This study seeks to deliver a comprehensive bibliometric analysis of blockchain research undertaken from 2013 to 2023. It seeks to map the field’s evolution, highlight emerging trends, and identify key contributors and thematic areas. Understanding these aspects is crucial for guiding future research and policymaking in the rapidly growing domain of blockchain technology. The study utilises a systematic bibliometric analysis approach and the Scopus database was used for collecting data. The analysis includes keyword trends, citation patterns, author productivity, and network analysis. The results reveal significant expansion and diversification in blockchain research, with 13,369 publications and 52,009 contributing authors. Key metrics include a total citation count of 266,483 and an average of 19.93 citations per paper, underscoring the field’s scholarly impact. The study identifies core research themes such as smart contracts, security, IoT integration, and emerging topics like AI and sustainability. The findings highlight the interdisciplinary nature of blockchain research and its global distribution, with notable contributions from China and the United States. The study’s reliance on selected databases and predefined keywords may exclude relevant grey literature and industry reports. Future research should integrate these sources for a more complete view. This study provides a panoramic view of blockchain research, offering valuable insights into its development, current state, and future directions. Identifying key trends, influential contributors, and emerging themes contributes to the academic discourse and supports strategic planning for researchers, practitioners, and policymakers engaged in blockchain technology.

An Analysis of Tesla's Disruptive Innovation Strategy

With the rapid development of new energy vehicles, governments and automobile manufacturers are generally aware that environmental protection is an important direction for the development of the future automotive industry, and Tesla, as a representative of the global new energy electric vehicles, has great research significance. In the fierce environment of the automobile market, Tesla has won the leadership position with many innovations. Therefore, the company is considered a disruptive innovation by the public. This paper focuses on whether Teslas innovation is disruptive innovation, and studies Teslas disruptive innovation strategy through literature reading and qualitative analysis. This paper discusses the definition of disruptive innovation, Teslas current innovation status and explores the difference between it and incremental innovation. This paper draws the conclusion that Tesla is a disruptive innovation by considering whether it creates a value network as a breakthrough point. Finally, the paper puts forward some suggestions, including extending the product line, adjusting its price to maintain its competitive advantage and innovation, adjusting the channel level based on local markets, provide more extreme and detailed experiential marketing and after-sales service, so as to promote Tesla's sustainable innovation.

The Impact of Intellectual Property Protection on Technological Innovation - A Literature Review Incorporating New Quality Productive Forces in the Chinese Economy

Abstract: This article explores the impact of intellectual property (IP) protection on technological innovation, particularly concerning Chinas recent emphasis on high-quality productivity. The paper reviews existing literature, discussing the differences in the effects of IP protection between developed and developing countries. This literature review shows that strengthened IP protection has a positive impact on technological innovation in China, but with a nonlinear relationship. The concept of new quality productive forces focuses on achieving high levels of quality and promoting disruptive technology innovation. Combining this concept, this article analyzes the influence of IP protection on its development and provides specific policy recommendations. Future studies should focus on empirical analysis to assess the actual effectiveness of IP protection within the existing policy framework. Appropriate evaluation systems are suggested to establish, and IP laws should be gradually improved so as to effectively facilitate Chinas technological innovation and industrial advancement.

Integration of blockchain with artificial intelligence technologies in the energy sector: a systematic review

Recently, artificial intelligence (AI) and blockchain have become two of the most trending and disruptive technologies. Blockchain technology can automate payment in cryptocurrency and provide access to a shared ledger of data, transactions, and logs in a decentralized, secure, and trusted manner. In addition, with smart contracts, blockchain has the ability to govern interactions among participants with no intermediary or a trusted third party. AI, on the other hand, offers intelligence and decision-making capabilities to machines similar to humans. This review presents a detailed survey on blockchain and AI basics and features. This paper provides a review of the literature and a brief on the integration of blockchain and AI applications in multiple areas. We also identify some sole cases of blockchain–AI integration in the energy sector with current use cases. Eventually, we discuss research advantages and challenges associated with integrating blockchain with AI in the energy domain.

How Artificial Intelligence (AI) Is Powering New Tourism Marketing and the Future Agenda for Smart Tourist Destinations

Artificial intelligence (AI) is a disruptive technology that is being used by smart tourist destinations (STDs) to develop new business models and marketing services to increase tourists’ experiences and sales, revenue, productivity, and efficiency and STDs. However, the adoption of AI applications and platforms requires a high economic budget for STDs that want to integrate this digital tool into their future agenda and tourism development plans, especially when they set them up for marketing plans and operational processes. This iterative technology needs regular maintenance as well, leading to recurring costs and specialised crews in advanced technologies and marketing activities. This study aims to show the impact of AI advancements on STDs’ tourism marketing to enhance the quality of services and illustrate their future agenda to improve tourists’ experiences. A comprehensive literature review on AI technology and STDs has been conducted to illustrate new tourism marketing in their future agenda. Moreover, this study presents real examples of AI technology in a tourism context to better understand the potential of this digital tool. The findings of the current study support the idea that AI is a multipurpose tool that helps manage, monitor, and analyse sales information; revenue management; minimise prediction errors; streamline operations; and develop better marketing strategies, optimising economic resources, reducing marketing costs, and responding dynamically to changing needs for tourists and residents in STDs. Furthermore, the investment in AI technologies by STDs helps enhance the quality of products and services, and attract new investments, which benefit the regional economies and population’s quality of life. This study is the first to address the use of AI to improve tourist marketing in STDs, which is its primary uniqueness. Also, this study identifies new opportunities and initiatives through AI that can be developed to help tourism marketing in STDs.

The window of opportunity: a case study of the battery electric vehicle in Thailand

Purpose Thailand, although a late entrant, has emerged as a significant center for the production and export of internal combustion engine (ICE) vehicles in Asia. With the arrival of a disruptive battery-electric vehicle (BEV), this study aims to investigate whether Thailand can exploit this window of opportunity to leapfrog. Design/methodology/approach This paper uses data sourced from Thailand’s Department of Intellectual Property to analyze electric vehicle (EV) patent applications. This paper collected qualitative data and conducted interviews with several EV manufacturers. Findings Although Japanese automakers dominate essential EV technology patents, they trail behind Chinese automakers, which benefited from the Free Trade Agreement (FTA) in EV sales. The incumbents, Japanese and Western, choose to expand their production of hybrid electric vehicles (HEVs) and plug-in hybrid vehicles. ICE technology does not constrain new entrants, such as Chinese automakers, Japanese newcomers and Thai newcomers. Compared to Japanese carmakers stuck with ICE and HEV technologies, they have been transitioning to BEVs at a faster pace. BEV has opened the door for large Thai indigenous energy corporations to enter the automotive industry by focusing on niche areas (nonfour-wheel vehicles) and supporting businesses like charging stations. In summary, Thailand has successfully attracted foreign direct investment (FDI) into the EV sector, but it has not yet succeeded in developing indigenous technologies related to EVs. The Thai automobile sector fails to leapfrog because it is too tied up with Japanese automotive production networks and has an unfavorable FTA with China. Originality/value This study sheds light on the limitations of an industrial development strategy relying on openness to trade and FDI without adequately strengthening indigenous technologies and firms, as the country adopting the strategy fails to leapfrog when the window of opportunities created by disruptive technologies arrives.

Protecting Human Creativity in AI-Generated Music with the Introduction of an AI-Royalty Fund

Abstract Artificial Intelligence (AI) is posited to revolutionise the creative industries, prompting global calls for legislative intervention to ensure human creativity remains at the centre of the copyright system. As AI systems gain prowess in analysing and generating content, they promise new levels of creativity and innovation at accelerated pace and reduced costs compared to human production. Alongside these benefits come concerns of displacement, particularly in fields like music, where AI-generated music could potentially supplant human-authored creative endeavours. Suggestions ranging from taxation to levies have been proposed to address this challenge. This paper, however, advocates for a novel perspective: evolving copyright law to not only compensate creators for income lost to technological disruption but also to foster sustainability aligned with the principles of the Council of Europe’s European Social Charter. Proposing an ‘AI-royalty fund’ represents a more optimal approach to this dilemma. Such a fund would acknowledge the intrinsic value of music and support a sustainable and inclusive creative industry ecosystem. Essential to this vision is the role of a national collective, entrusted with administering this fund to ensure equitable distribution and uphold the interests of human authors in an AI-driven landscape, contribute to regional and local plans of growth and foster cultural diversity and innovation. In essence, as AI redefines the boundaries of creativity, adapting the copyright paradigm becomes imperative to preserving the livelihoods of human creators while promoting a resilient and sustainable creative economy.

A novel integrated approach for quantifying the convergence of disruptive technologies from science to technology

With rapid developments in science and technology, knowledge transfer from science to technology and technology convergence from different fields are accelerating. Technology convergence has become a main source of disruptive technologies (DTs). To facilitate enterprise R&D strategic decision-making and government innovation policies formulation, it is necessary to quantify the convergence processes of DTs and understand the DTs' emergence characteristics from science to technology. Existing research on technology convergence measurement mainly used patent citation information, patent co-classification analysis, and text mining. However, since these studies have limited analysis of the sources and causes of technology convergence from the perspective of knowledge memes, resulting in insufficient revelation of the processes and characteristics of DTs' emergence. Knowledge meme theory helps to reveal the relationships between knowledge diffusion, knowledge convergence, and technology convergence. Therefore, in this paper, we proposed a research framework for quantifying the convergence of DTs from science to technology. In this framework, we analyzed the knowledge diffusion and technology convergence of DTs from science to technology based on knowledge meme theory. We also integrated patent citation analysis, text mining, and cascade network models to quantitatively measure knowledge diffusion and technology convergence characteristics. We tried to understand the generation mechanisms of DTs from the perspective of technology convergence. We took smartphones as a case study to verify the framework's validity and flexibility. This paper provides a novel approach for quantifying the convergence of DTs from science to technology, which can help us to understand the emergence and development trends of DTs. This paper will also be of interest to smartphone technology R&D experts.

Scooting into place: How comfort on different infrastructure types influences shared e-scooter trip making

Shared e-scooters are a growing disruptive micro-mobility technology. Several Canadian cities, including Calgary, have launched pilot programs to test these micro-mobility options. As part of the Calgarian pilot, a public engagement survey was launched to collect information about the public’s perception of shared e-scooters. The survey includes a set of questions related to users’ perception of comfort using shared e-scooters on various infrastructure types: roads, bike lanes, sidewalks and dedicated pathways, as well as a question related to the frequency of use of the e-scooters. Comfort in general and specific comfort on the type of infrastructure most used is expected to have a high degree of correlation with the frequency of use. We present a joint ordered choice model examining how different sociodemographic characteristics and typical travel patterns of the survey respondents influence perceptions of comfort on these different infrastructure types and their frequency of e-scooter use. The model estimation results show that e-scooter use is not uniform across age and gender demographics and that infrastructure, riding comfort, and e-scooter use are linked. E-scooter riding comfort was negatively associated with infrastructure types that led to more potential interactions with motor vehicles and pedestrians. These results will allow decision makers to tailor new policies and prioritize infrastructure to improve the overall usage of e-scooters and maximize the benefits these new technologies will provide.

Disclosure, Patenting, and Trade Secrecy

AbstractPatent applications often reveal proprietary information to competitors, but does such disclosure harm firms or also benefit them? We develop and empirically support a theory showing that when firms patent enhancements to incumbent, nondisruptive technologies, they can cooperate more easily on these technologies, increasing their profitability. The downside of cooperating on nondisruptive technologies is that the investment in and commitment to disruptive technologies decline. To improve their commitment to disruptive technologies, some firms rely more on trade secrecy. We provide empirical support for these predictions. We document that after a patent reform that made information about patent applications widely accessible, firms cooperate more and charge higher markups. Furthermore, the nature of patented innovation has changed, with the proportion of nondisruptive patents increasing substantially. Finally, while some firms start patenting more, others patent less and rely more on trade secrecy, with the response depending on the attractiveness of firms' innovation prospects.

A review of Artificial Intelligence methods in bladder cancer: segmentation, classification, and detection

Artificial intelligence (AI) and other disruptive technologies can potentially improve healthcare across various disciplines. Its subclasses, artificial neural networks, deep learning, and machine learning, excel in extracting insights from large datasets and improving predictive models to boost their utility and accuracy. Though research in this area is still in its early phases, it holds enormous potential for the diagnosis, prognosis, and treatment of urological diseases, such as bladder cancer. The long-used nomograms and other classic forecasting approaches are being reconsidered considering AI’s capabilities. This review emphasizes the coming integration of artificial intelligence into healthcare settings while critically examining the most recent and significant literature on the subject. This study seeks to define the status of AI and its potential for the future, with a special emphasis on how AI can transform bladder cancer diagnosis and treatment.

ChatGPT in Pharmacy Practice: Disruptive or Destructive Innovation? A Scoping Review

ChatGPT has emerged as a promising tool for enhancing clinical practice. However, its implementation raises critical questions about its impact on this field. In this scoping review, we explored the utility of ChatGPT in pharmacy practice. A search was conducted in five databases up to 23 May 2024. Studies analyzing the use of ChatGPT with direct or potential applications in pharmacy practice were included. A total of 839 records were identified, of which 14 studies were included: six tested ChatGPT version 3.5, three tested version 4.0, three tested both versions, one used version 3.0, and one did not specify the version. Only half of the studies evaluated ChatGPT in real-world scenarios. A reasonable number of papers analyzed the use of ChatGPT in pharmacy practice, highlighting both benefits and limitations. The studies indicated that ChatGPT is not fully prepared for use in pharmacy practice due to significant limitations. However, there is great potential for its application in this context in the near future, following further improvements to the tool. Further exploration of its use in pharmacy practice is required, along with proposing its conscious and appropriate utilization.

The dual role of blockchain in mediating credence attributes and moderating sensing capabilities in the wine sector

Purpose This study aims to investigate the dynamic capabilities of wineries, focusing on sensing and its role in enabling digital innovation. Furthermore, it explores the role of blockchain technology (BCT) in validating credence attributes of wine, emphasising blockchain as a strategic asset that enhances the ability of wineries to innovate and respond to changing market conditions. Design/methodology/approach The study adopts an exploratory approach based on a longitudinal, single-case study of the Argentinian Costaflores Organic Winery. Findings Findings reveal that integrating digital disruptive innovations such as blockchain can strategically position wineries to better meet emerging consumer preferences and market trends. Blockchain simultaneously acts as both a mediator and a moderator. As a mediator, it facilitates the validation of credence attributes of wine such as authenticity and sustainability, enhancing customer trust and loyalty. As a moderator, it influences the strength and effectiveness of the relationship between sensing and innovation capabilities. This enables wineries to more effectively respond to changing consumer requirements and market trends and improve operational performance. Research limitations/implications The study was limited by its focus on a single case study of the Argentinian Costaflores Organic Winery, which may affect the generalisability of the findings. However, the study provides valuable insights into the strategic adaptation and competitive positioning of wineries in response to the continuing market challenges. It significantly contributes to the understanding of integrating digital disruptive innovations as strategic assets in the agri-food sector, particularly in the wine sector. Originality/value This study addresses a significant research gap by exploring how BCT facilitates the organisation of sensing capabilities. It contributes to the understanding of how the wineries’ sensing capabilities both influence and are influenced by the adoption of BCT, particularly in the context of innovation enabling and improved operational performance.

The integral role of high‐entropy alloys in advancing solid‐state hydrogen storage

AbstractHigh‐entropy alloys (HEAs) have emerged as a groundbreaking class of materials poised to revolutionize solid‐state hydrogen storage technology. This comprehensive review delves into the intricate interplay between the unique compositional and structural attributes of HEAs and their remarkable hydrogen storage performance. By meticulously exploring the design strategies and synthesis techniques, encompassing experimental procedures, thermodynamic calculations, and machine learning approaches, this work illuminates the vast potential of HEAs in surmounting the challenges faced by conventional hydrogen storage materials. The review underscores the pivotal role of HEAs' diverse elemental landscape and phase dynamics in tailoring their hydrogen storage properties. It elucidates the complex mechanisms governing hydrogen absorption, diffusion, and desorption within these novel alloys, offering insights into enhancing their reversibility, cycling stability, and safety characteristics. Moreover, it highlights the transformative impact of advanced characterization techniques and computational modeling in unraveling the structure–property relationships and guiding the rational design of high‐performance HEAs for hydrogen storage applications. By bridging the gap between fundamental science and practical implementation, this review sets the stage for the development of next‐generation solid‐state hydrogen storage solutions. It identifies key research directions and strategies to accelerate the deployment of HEAs in hydrogen storage systems, including the optimization of synthesis routes, the integration of multiscale characterization, and the harnessing of data‐driven approaches. Ultimately, this comprehensive analysis serves as a roadmap for the scientific community, paving the way for the widespread adoption of HEAs as a disruptive technology in the pursuit of sustainable and efficient hydrogen storage for a clean energy future.

Truth & Information? Preparing Information Organization & Retrieval Students for an AI Future

Artificial intelligence (AI) is not a new concept or technology, but has taken the world by storm with the recent advancement of generative AI, such as ChatGPT and Bard. The metadata, cataloging, collections, and retrieval areas of library and information studies (LIS) are already experiencing disruption and soul-searching because of generative AI, but it remains to be seen to what extent the technology can benefit, or even harm, these areas of LIS. The Metadata, Cataloging, & Collections SIG session will include a panel of three educators who will discuss the use of artificial intelligence in information retrieval and cataloging courses, and provide ideas for educators hoping to learn more about the impact of AI and how to incorporate activities and discussions of AI in their courses. Priya Kizhakkethil will report on student perceptions of AI in the LIS curriculum, with a focus on Information Retrieval courses. With the emergence of Generative Artificial Intelligence (Gen AI) tools like ChatGPT, there has been much discussion about its impact on libraries and the work of librarianship. But there is a gap in the literature that addresses how such disruptive technologies should be addressed in the LIS curriculum. This presentation covers a work in progress pilot study seeking to understand LIS student perceptions on the use of generative AI tools as part of their course work. Themes relating to student perceptions on the use of Gen AI tools for an Information Retrieval course will be discussed, which includes the potential ways of using these tools as noted by the students. Vyacheslav (Slava) Zavalin will discuss the critical need for understanding the AI landscape and its application to information organization within LIS. He will demonstrate using Google Gemini, the AI-powered assistant, to create bibliographic examples and then analyze and discuss the accuracy of the records. Karen Snow recently assigned advanced cataloging students an exercise that required them to create a basic MARC/RDA bibliographic record using ChatGPT. The resulting transcripts of their conversations with ChatGPT, and their reflections on the experience, were a fascinating demonstration of the benefits/drawbacks of AI in cataloging work, but also of the importance of educating students on how to effectively use AI. After the presentations, audience members will be encouraged to ask questions and offer their own experiences and ideas concerning this area of LIS education. These presentations align well with the ALISE 2024 conference theme of “The Ethics and Evolution of Truth and Information.”

Predicting the emergence of disruptive technologies by comparing with references via soft prompt-aware shared BERT

The exponential increase in the annual volume of publications places a significant challenge in assessing the disruptive potential of technologies in new papers. Prior approaches to identifying disruptive technologies based on the accumulation of paper citations are characterized by their limited prospective and time-consuming nature. Moreover, the total citation count fails to capture the intricate network of citations associated with the focal papers. Consequently, we advocate for the utilization of the disruption index instead of depending on citation counts. Particularly, we devise a novel neural network, called Soft Prompt-aware Shared BERT (SPS-BERT), to predict the potential technological disruption index of immediately published papers. It incorporates separate soft prompts to enable BERT examining comparative details within a paper's abstract and its references. Additionally, a tailored attention mechanism is employed to intensify the semantic comparison. Based on the enhanced representation derived from BERT, we utilize a linear layer to estimate potential disruption index. Experimental results demonstrate that SPS-BERT outperforms existing state-of-the-art methods in predicting five-year disruption index across the DBLP and PubMed datasets. Additionally, we conduct an evaluation of our model to predict the ten-year disruption index and five-year citation increments, demonstrating its robustness and scalability. Notably, our model's predictions of disruptive technologies, based on papers published in 2022, align with the expert assessments released by MIT, highlighting its practical significance. The code is available at https://github.com/ECNU-Text-Computing/SPS-BERT.

Are we ready? Generative AI and the LIS curriculum

The US Department of Education’s 2023 report highlights the importance of AI literacy for educators and other stakeholders (Cardona, Rodriguez & Ishmael, 2023). Analyzing this report, Lo (2023) notes that “for librarians, AI literacy could involve understanding how AI tools work, how they can be used to enhance library services, and how to navigate potential ethical issues related to AI” (p. 2). Southworth et al (2023) observe that technical aspects of AI are covered in the traditional STEM curricula but are largely absent outside of it. While there are efforts currently to provide education and training opportunities for librarians in addressing AI in their work, as well as literature that talks about how AI will impact various aspects of work in libraries, few have touched on the need for curriculum development to effectively address such disruptive technologies by identifying the competencies or threshold concepts that will be affected by them. The ubiquitous impact of AI has included applications in medical research as well as law, design, economics, and humanities, to name just a few. Agile practice and improved dissemination of best practices are called for, moving forward. How should LIS curriculum address AI and related issues to prepare future librarians and information professionals? This poster covers an in-progress scoping review of literature and a content analysis of the publicly available course descriptions of ALA accredited LIS programs, as well as their current mission statements and objectives to provide a snapshot of extant integration of this new and challenging technology.

Application of Internet of Things and Artificial Intelligence for Risk Mitigation of Accidents in Construction Sites: A Case Study of Brazilian Construction Companies

The construction industry constantly faces challenges related to workplace safety. Managing work safety is crucial to ensuring worker protection and successful project completion. In this context, this study investigates the applicability of Internet of Things technologies and Artificial Intelligence models, such as YOLO, to enhance safety on construction sites. The research identifies significant cultural resistance to the adoption of disruptive technologies in the Brazilian construction sector, and interviews with industry professionals reveal a low level of awareness and interest in these technological innovations. Through case studies and quantitative analyses, the study demonstrates YOLO's potential in identifying risks, such as detecting PPE and structural hazards. The results highlight the need to overcome conservative barriers and invest in technological solutions to increase safety and efficiency in construction.