Hype Cycle Research Articles

Technology hype: Dealing with bold expectations and overpromising

To date, the study of hype has become a productive but also eclectic field of research. This introduction provides an overview of the core characteristics of technology hype and distinguishes it from other future-oriented concepts. Further, the authors present promising approaches from various disciplines for studying, critiquing, and dealing with hype. The special issue assembles case studies, methodological and theoretical contributions that analyze tech hypes’ temporality, agency, and institutional dynamics. It provides insights into how hypes are triggered and fostered, but also how they can be deconstructed and anticipated.

Technology hypes: Practices, approaches and assessments

To date, the study of hype has become a productive but also eclectic field of research. This introduction provides an overview of the core characteristics of technology hype and distinguishes it from other future-oriented concepts. Further, the authors present promising approaches from various disciplines for studying, critiquing, and dealing with hype. The special issue assembles case studies, methodological and theoretical contributions that analyze tech hypes’ temporality, agency, and institutional dynamics. It provides insights into how hypes are triggered and fostered, but also how they can be deconstructed and anticipated.

Assessing the journey of technology hype in the field of quantum technology

The ‘second quantum revolution’ promises new technologies enabled by quantum physics and has been the subject of substantial hype. We show that while creating expectations has helped secure support for quantum research, their iterative effects can come to affect the field in concrete ways. These iterative impacts for quantum include emerging discussions about ethics and the delivery of promised outcomes. Such contestations could open up alternative quantum futures, but this will depend on how the ‘hype helix’ of iterative expectations unfolds.

Assessing generative A.I. through the lens of the 2023 Gartner Hype Cycle for Emerging Technologies: a collaborative autoethnography

This brief research report examines claims made across contemporary media channels that generative artificial intelligence can be used to develop educational materials, in an experiment to develop a new course for advertising, PR and branding professionals. A collaborative auto-ethnography is employed to examine the journey and unintended consequences experienced by a non-technology lecturer engaging with generative AI for the first-time and is examined under the lens of the 2023 Gartner Hype Cycle for Emerging Technologies. The researchers were able to map lived experiences to stages of the Gartner model, presenting evidence that this tool could have extended utility in the field of human resources for the support of technology integration projects. They also recorded several potential manifestations of symptoms related to the problematic use of Internet (PUI). The implications of the findings contribute to ongoing public discourse regarding the introduction of artificial intelligence within education, with insights for policy development and governance, as well as faculty and student wellbeing.

Artificial Intelligence: From Buzzword to Useful Tool in Clinical Pharmacology.

The advent of artificial intelligence (AI) in clinical pharmacology and drug development is akin to the dawning of a new era. Previously dismissed as merely technological hype, these approaches have emerged as promising tools in different domains, including health care, demonstrating their potential to empower clinical pharmacology decision making, revolutionize the drug development landscape, and advance patient care. Although challenges remain, the remarkable progress already made signals that the leap from hype to reality is well underway, and AI promises to offer clinical pharmacology new tools and possibilities for optimizing patient care is gradually coming to fruition. This review dives into the burgeoning world of AI and machine learning (ML), showcasing different applications of AI in clinical pharmacology and the impact of successful AI/ML implementation on drug development and/or regulatory decisions. This review also highlights recommendations for areas of opportunity in clinical pharmacology, including data analysis (e.g., handling large data sets, screening to identify important covariates, and optimizing patient population) and efficiencies (e.g., automation, translation, literature curation, and training). Realizing the benefits of AI in drug development and understanding its value will lead to the successful integration of AI tools in our clinical pharmacology and pharmacometrics armamentarium.

The relaxometry hype cycle.

Relaxometry is a field with a glorious and controversial history, and no review will ever do it justice. It is full of egos and inventions, patents and lawsuits, high expectations and deep disillusionments. Rather than a paragraph dedicated to each of these, we want to give it an impressionistic overview, painted over with a coat of personal opinions and ruminations about the future of the field. For those unfamiliar with the Gartner hype cycle, here's a brief recap. The cycle starts with a technology trigger and goes through a phase of unrealistically inflated expectations. Eventually the hype dies down as implementations fail to deliver on their promise, and disillusionment sets in. Technologies that manage to live through the trough reach the slope of enlightenment, when there is a flurry of second and third generation products that make the initial promise feel feasible again. Finally, we reach the slope of productivity, where mainstream adoption takes off, and more incremental progress is made, eventually reaching steady state in terms of the technology's visibility. The entire interactive timeline can be viewed at https://qmrlab.org/relaxometry/.

The Role of Business Model Innovation in the IT Services Sector: a Comprehensive Mapping Review

Purpose: The study analyzes the evolution of Business Model Innovation (BMI) in the IT sector, which is mentioned in many available scientific publications. The major output of this paper is concrete customer requirements that invite business model innovations to managed IT services and challenges to establish corresponding business model innovations.
 Design/Method/Approach: The study identified more than 200 journal articles and conference articles with BMI and IT service providers, and it conducted a mapping review of current research to identify relevant academic theories, implementation strategies, and BMI in the managed IT service sector while highlighting gaps in empirical research.
 Findings: Most applied are BMI and the framework of dynamic capabilities in business models of IT services. Early movers, who develop a comprehensive platform strategy, can achieve an invulnerable moat and establish a leading market position.
 Practical Implications: The insights of this study could be applied by large companies, small- and medium-sized companies and start-ups, researchers, etc. They can use the insights to innovate their current business models and improve tailored client solutions. 
 Originality/Value: The study concludes that business model innovations and IT service providers develop areas for future success.
 Research Limitations/Future Research: The design of the study is based on a systematic literature review and limited to the areas of BMI research in the IT service sector. For further research projects, individual articles can be chosen to perform in-depth analysis. Our trend analysis shows the focus on main technologies. However, this can be compared with the technologies mentioned in the Gartner Hype Cycle. Further research could be conducted to overcome limitations and cover the uncertain content of this research.
 Paper Type: Conceptual
 JEL Classification: M21, O14, O33

Artificial intelligence trend analysis on healthcare podcasts using topic modeling and sentiment analysis: a data-driven approach

Over the past few decades, the topic of artificial intelligence (AI) has gained considerable attention in both research and industry. In particular, the healthcare sector has witnessed a surge in the use of AI applications, as the maturity of these methods increased. However, as the use of machine learning (ML) in healthcare continues to grow, we believe it will become increasingly important to examine public perceptions of this trend to identify potential impediments and future directions. Current work focuses mainly on academic data sources and industrial applications of AI. However, to gain a comprehensive understanding of the increased societal interest in AI, digital media such as podcasts should be consulted, as they are accessible to a broader audience. In order to examine this hypothesis, we investigate the AI trend development in healthcare from 2015 until 2021. In this study, we propose a web mining approach to collect a novel data set consisting of 29 healthcare podcasts with 3449 episodes. We identify 102 AI-related buzzwords that were extracted from various glossaries and hype cycles. These buzzwords were used to conduct an extensive trend detection and analysis study on the collected data using machine learning-based approaches. We successfully detect an AI trend and follow its evolution in healthcare podcasts over several years. Besides the focus area of AI, we are able to detect 14 topic clusters and visualize the trending or decreasing dominant topics over the whole period under consideration. In addition, we analyze the sentiments in podcasts towards the identified topics and deliver further insights for trend detection in healthcare. Finally, the collected data set can be used for trend detection besides AI-related topics using topic clustering.

Researching models of innovation and adoption in health professions education.

Despite the constant presence of change and innovation in health professions education (HPE), there has been relatively little theoretical modelling of such change, the experiences of change, the ideology associated with change or the unexpected consequences of change. In this paper, the authors explore theoretical approaches to the adoption of innovations in HPE as a way of mapping a broader theoretical landscape of change. The authors, HPE researchers with an interest in technology adoption and systemic change, present a narrative review of the literature based on a series of thought experiments regarding how communities and individuals respond to the introduction of new ideas or methods. This research investigates the stages of innovation adoption, from the emergence and hype around new ideas to the concrete experiences of early adopters. When an innovation first emerges, there is often little concrete information available to inform potential adopters, leaving it susceptible to hype, both positive and negative. This can be described using the Gartner Hype Cycle model, albeit with important caveats. Once the adoption of an innovation gets underway, early adopter user experiences can inform those that follow. This can be described using Rogers' diffusion of innovation model, again with caveats. Notably, neither model goes beyond the point of single point-in-time, yes/no, individual adoption. Other approaches, such as learning curve theory, are needed to track uptake and maintenance by individuals over time. This expanded theoretical base, while still somewhat instrumentalist, combined with complementary theoretical perspectives can afford opportunities to better explore reasons for variance, volunteerism and resistance to change. In summary, change is complicated and nuanced, and better models and theories are needed to understand and work meaningfully with change in HPE. To that end, the authors seek to encourage richer and more thoughtful research and scholarly thinking about change and a more nuanced approach to the pursuit of change in HPE as a whole.

The strange resilience of the UK e-Borders programme: Technology hype, failure and lock-in in border control

The UK government’s e-Borders project presents an intriguing anomaly: despite repeated and acknowledged failings of the project over two decades, it has remained a core part of border strategy across successive administrations. This article seeks to explain the surprising resilience of this programme by developing the concept of political lock-in. We combine insights from critical security studies with science and technology studies concepts of ‘tech hype’ and lock-in. We apply these insights to trace how e-Borders was constructed as a compelling technological solution to pressing security issues. This created a form of political lock-in, whereby the project became impossible to abandon because of its political urgency, despite increasing awareness of its unfeasibility. With the project caught in a liminal state of non-completion, successive governments expanded the scope of the programme by attaching new security problems to it, thereby rendering it even more unviable. Our analysis thus throws up a paradox: rather than mobilizing resources to accomplish its tech vision, securitization created forms of lock-in and paralysis that made the programme more difficult to accomplish.

NATURE BASED INNOVATIONS IN THE DEVELOPMENT OF BIOECONOMY

The main purpose of the article was to present the benefits and challenges related to the bioeconomy as a subsector of the economy, as well as the impact of the biological revolution on the bioeconomy. The market readiness of various nature-based innovations in agriculture was also assessed. The bioeconomy was found to be a right path to sustainable development, addressing social and environmental challenges while supporting economic growth. Thus, it determines a more resilient and resource-efficient development. Nature-based innovations harness the power of natures resilience, efficiency and adaptability to meet societal challenges in a sustainable way. These innovations offer promising economic solutions while increasing the protection of biodiversity and the health of ecosystems. Based on feedback from key stakeholders, the Garther Hype Cycle model was developed. The productivity phase is reached by those technologies and products that have managed to break out of their niche and gain widespread acceptance. In the analysis, this level was achieved by biological control and the use of beneficial microorganisms. Biological control in particular has been identified as a nature-based technology that dominates todays agriculture and will increase in importance in the future.

Investigating how the public acceptance of autonomous vehicles evolve with the changes in the level of knowledge: A demographic analysis

Autonomous vehicles (AVs) are expected to provide various advantages such as improved mobility, increased comfort, and reduced traffic accidents. However, the deployment of AVs is contingent upon the public’s attitude, which in turn may affect their consequences. The relationship between public knowledge about AVs and attitude has been debated. While some studies indicate a positive correlation between knowledge and optimism, others suggest a negative association. The present study aims to evaluate the association between public knowledge, attitude, and AVs in the US. A questionnaire survey was conducted between June and November 2022, yielding 5778 complete responses from various regions of the US. Data were analyzed to estimate the public attitude and level of knowledge by region. Findings revealed a negative shift in public attitude towards AVs with increased knowledge. Specifically, a 1% increase in knowledge was associated with a 0.65% reduction in interest, a 0.68% decrease in trust, and a decline of $2466 USD in willingness to pay for AVs, as well as a 0.56% increase in concerns about traveling in AVs. In addition, further analysis was conducted to understand how the public attitude of different demographic groups evolves with the level of knowledge. Furthermore, the results of this study were discussed in light of the introduction of the automobiles showing a lot of similarities in the public attitude towards the introduction of both the automobiles (more than 100 years ago) and AVs (now). In addition, the results were discussed in light of the theory of diffusion of innovation and the Gartner Hype Cycle which are used to explain how the public reacts to innovations.

Hope or hype? Blockchain and accounting

Gartner’s hype cycle of technology famously progresses from the “peak of inflated expectations” to the “plateau of productivity” via the “trough of disillusionment”. Accounting researchers and practitioners—like researchers and practitioners in many other fields—have jumped onto the blockchain bandwagon for fear of missing out on what has been hailed as a world changing technology. Unfortunately, there is a pervasive lack of understanding of what blockchain is, and misconceptions about what it can do. A fundamental problem is that blockchain was derived from bitcoin and there is a great deal of difficulty in defining what blockchain is, and how suitable the methodology for a trustless, public cybercurrency application is to a public blockchain between trusted partners. It is time, we believe, to look at blockchain in accounting with more objectivity. We undertake a detailed exploration of blockchain and identify several key factors that will defines the uses of this technology, namely, the distinction between public and private blockchains and the importance of processing costs as a validating mechanism.

Discussion of “Is designed data collection still relevant in the big data era?”

Discussion of “Is designed data collection still relevant in the big data era?”

Онтологический подход к разработке единой базы знаний мультимодальных перевозок

Purpose: In the frames of ongoing digital transformation of transport complex in a whole and railway transport in particular, to give brief analytical characterization of being developed digital platforms and services. To consider promising technologies that are either at launch stage or on the way to the peak of overpriced expectations as to technological hype cycle of Gartner Research Company. To give an example of unified knowledge base as a basis of digital platform for multimodal transportation. Methods: Methods for visual structuring of information were used, in particular, mental maps (intellect-maps). To represent subject area ontology, a semantic network was used as a method for knowledge representation. Results: The pursued analysis of being developed and existing digital platforms and services has shown that besides data, there should lie at their basis more complex informational units — an active knowledge. This requires the method of data integration from disparate sources, their integration and circulation as within one industry as well as between various industries in order of knowledge generation and spread. In view of work specifics of transport various kinds, participating in multimodal transportations, the subject area, uniting all kinds of transport, should be chosen for this. The application of "cargo transportation" subject area has been justified by virtue of which, it is necessary to create management system of cargo flows on railway transport. Ontology fragment, describing "cargo transportation" domain for railway transport, has been worked out. Practical significance: The necessity of applying active knowledge to create autonomous intellectual productions on transport is shown. The use of knowledge bases, established on ontologies, will allow to raise the level of interaction of transport various kinds in "narrow" places during cargo transshipment as well as to expand the range of services, provided to customers.

Understanding Displays and Optics Requirements to Take AR/VR Mainstream

After laptops came tablets, which evolved to resemble laptops; then smartphones arrived, which evolved to be like tablets. So what is next for computing, entertainment, or any application that currently uses laptops, tablets, and smartphones? Virtual and augmented reality (VR/AR) devices could be contenders. Promoters of VR and AR technologies not only hope to create new applications in the metaverse, but to displace some existing devices with something better. As with many consumer electronics applications, new applications follow a hype cycle before reality sets in, and sometimes the reality is even better than what was imagined at the peak of the hype cycle. Irrespective of the curve that AR/VR devices could follow, they are here to stay. Virtually every major consumer electronics company, every major display company, and thousands of smaller companies have invested many years and billions of dollars in taking the idea of AR/VR down the path toward commercial reality. When people ask if it's there yet, our answer is that we have been shipping OLED microdisplays into these and other medical, industrial, and military applications for a long time. It's taking longer to achieve consumer mass market success, but we believe it will. To forecast where we are going, it is important to understand the current state of the industry and goals for the future. This requires a careful assessment of optics and display technologies as they stand today so we can understand the hurdles and focus on overcoming them. With this in mind, we invited an article, “Advanced VR and AR Displays: Improving the User Experience,” from Changhee Lee, corporate EVP and head of R&D at Samsung Display. Together with his colleagues, Lee examines the human visual system and highlights the goals and challenges of designing for AR and VR applications. Samsung's experience as an industry leader in display technology helps us provide our readers with a deeper look into this topic. We also are fortunate to have Karl Guttag, an industry expert with more than 40 years of experience, overview waveguide optics and display technologies that impact the world of AR, VR, and mixed reality (MR) in “Analyzing Optics’ Pivotal Role in Augmented and Mixed Reality Displays.” Guttag has studied all major waveguide and display technologies and provides descriptions and analyses of each along with informative graphics. There is not a single approach to optics. Each has its benefits and unique features for specific applications within AR and VR. Most waveguides used today aren't meeting industry's expectations in terms of light output. In most cases, more than 90 percent of the light is lost within the system. Similarly with display technologies, liquid crystal on silicon (LCoS) technology is well established but has not met expectations in terms of response time, weight, and power. Laser scanning results in inadequate image quality; while OLED technology has a faster response time, but high brightness demands are not quite met in production. Similarly, microLED is emerging with its own set of lab-to-fab challenges. Apart from optics and displays, the system itself is expected to be worn for long durations and needs to be light, ergonomically and aesthetically suitable, and work in untethered environments. It also should provide a variety of content—including both striking visual and high-quality audio. But the industry is not deterred by these challenges. Various industries and applications are eager to have high-quality AR and VR devices deployed to enable new markets and displace existing devices with those that offer greater value. The entertainment industry finds VR devices a natural fit that offer a much better viewing experience. Whether the user is watching a movie or the Super Bowl, the industry wants to immerse users, to provide an experience as if they are in a movie or had courtside seats at a basketball game. Meanwhile, the medical industry wants to use AR devices to aid surgeons, and VR devices could train nurses. Industrial applications also could use AR devices to enhance safety, while the military could use these devices to … well, let's just say the military wants these devices. From computing to communications, from brand experience to balloon rides, the applications are myriad, and these industries are waiting on our industry to fix the technical hurdles and deliver amazing products. And we will. Amal Ghosh is the COO at eMagin Corporation. He is a SID Fellow and received the Karl Ferdinand Braun Prize and SID Special Recognition Award. He earned a PhD degree in physics from the Massachusetts Institute of Technology. He may be reached at [email protected]. Sri Peruvemba is an associate editor for Information Display. He is the CEO of Marketer International in the Silicon Valley and works with high-tech companies in board and advisory roles. He may be reached at [email protected].

The rise and fall of the “Massively Open Online Courses”

The paper summarizes the actual debate about “massive open online courses” (MOOC), a concept that swept over like a “Tsunami” to European educators and universities since its first development in 2008. The definition of the so-called MOOCs, also referred to as a “disruptive educational innovation”, however, is not very precise and has led to some irritations and scepticism. Therefore, the ideas MOOCs rely on, will be described and the pedagogical and technological background will be explained by detailed descriptions of concrete examples. After setting the scene, the factors responsible for the initial hype about MOOCs will be analyzed as well as the upcoming criticism raised against the arguments of the MOOC proponents. The model of the Gartner hype cycle serves as a useful illustration of the ups and downs of expectations related to the introduction of educational innovations. The discussionwill be supplemented by a brief flash back on prior developments in distance education. Furthermore, some recent empirical data retrieved from Google Trends are presented to underline that MOOCs are already on the descent. Finally, the conditions for a survival of some specific applications of MOOCs at “the plateau of the cycle of expectations” will be outlined. In conclusion, MOOCs seem to have promoted, especially in the US, the use of online teaching and learning as well as the reflection about open educational resources. However, the blurred definition of the term MOOC combined with exaggerated expectations turned down the initial hype about a “disruptive innovative concept of teaching and learning” to a more modest consideration of its potential.

A Historical Analysis of Hydrogen Economy Research, Development, and Expectations, 1972 to 2020

Global climate change concerns have pushed international governmental actions to reduce greenhouse gas emissions by adopting cleaner technologies, hoping to transition to a more sustainable society. The hydrogen economy is one potential long-term option for enabling deep decarbonization for the future energy landscape. Progress towards an operating hydrogen economy is discouragingly slow despite global efforts to accelerate it. There are major mismatches between the present situation surrounding the hydrogen economy and previous proposed milestones that are far from being reached. The overall aim of this study is to understand whether there has been significant real progress in the achievement of a hydrogen economy, or whether the current interest is overly exaggerated (hype). This study uses bibliometric analysis and content analysis to historically map the hydrogen economy’s development from 1972 to 2020 by quantifying and analyzing three sets of interconnected data. Findings indicate that interest in the hydrogen economy has significantly progressed over the past five decades based on the growing numbers of academic publications, media coverage, and projects. However, various endogenous and exogenous factors have influenced the development of the hydrogen economy and created hype at different points in time. The consolidated results explore the changing trends and how specific events or actors have influenced the development of the hydrogen economy with their agendas, the emergence of hype cycles, and the expectations of a future hydrogen economy.

Qualitative Clustering of Software Repositories Based on Software Metrics

Software repositories contain a wealth of information about the aspects related to software development process. For this reason, many studies analyze software repositories using methods of data analytics with a focus on clustering. Software repository clustering has been applied in studying software ecosystems such as GitHub, defect and technical debt prediction, software remodularization. Although some interesting insights have been reported, the considered studies exhibited some limitations. The limitations are associated with the use of individual clustering methods and manifesting in the shortcomings of the obtained results. In this study, to alleviate the existing limitations we engage multiple cluster validity indices applied to multiple clustering methods and carry out consensus clustering. To our knowledge, this study is the first to apply the consensus clustering approach to analyze software repositories and one of the few to apply the consensus clustering to software metrics. Intensive experimental studies are reported for software repository metrics data consisting of a number of software repositories each described by software metrics.We revealed seven clusters of software repositories and relate them to developers’ activity. It is advocated that the proposed clustering environment could be useful for facilitating the decision making process for business investors and open-source community with the help of the Gartner’s hype cycle.

The Role of Network Slicing and Edge Computing in the Metaverse Realization

Metaverse is the latest technological hype in the modern world due to its potential for revolutionizing the digital visual perspective. With the COVID-19 pandemic, most industries have moved towards digitization, and the metaverse is identified as one of the most promising platforms for such a transition, as it provides a three-dimensional (3D) immersive experience for the users. Currently, most digital service providers and organizations are actively working on metaverse- based applications. In addition, there has been a rapid increase on research work involving metaverse realization. Launching a large scale metaverse in the real world is a challenging task. However, fifth-generation (5G) and beyond 5G (B5G) technologies are envisioned to improve the feasibility of pragmatic deployments. Although, there are several conceptual designs available, actual adaptations of the concepts are still limited. This survey focuses on providing a practical approach for metaverse realization using 5G and B5G technologies. Specifically, We discuss the importance of network slicing (NS) and multi-access edge computing (MEC) as emerging 5G technologies for enabling the realization of the metaverse. We first introduce the motivation behind metaverse for future envisaged technologies. Next, we present a holistic high-level framework for metaverse realization based on network slicing and edge computing. Moreover, we discuss the futuristic metaverse applications, their technical requirements, and methods to satisfy the requirements. Finally, we highlight the deployment challenges and possible approaches to overcome them for an actual metaverse realization.