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How do radical technological fields become naturalized and taken for granted? This is a fundamental question given both the positive and negative hype surrounding the emergence of many new technologies. In this chapter, we study the emergence of the US nanotechnology field, focusing on uncovering the mechanisms by which leaders of the National Nanotechnology Initiative managed hype and its concomitant legitimacy challenges which threatened the commercial viability of nanotechnology. Drawing on the cultural entrepreneurship literature at the interface of strategy and organization theory, we argue that the construction of a naturalizing frame – a frame that focuses attention and practice on mundane, “rationalized” activity – is key to legitimating a novel and uncertain technological field. Leveraging the insights from our case study, we further develop a staged process model of how a naturalizing frame may be constructed, thereby paving the way for a decrease in hype and the institutionalization of new technologies.

This paper provides evidence based quantification of both “actual” disruption of industries as well as a measure of disruption “hype”. The data cover a seven-year period from 2012 to 2018 across 12 industries. The authors’ complemented the research with a survey of 2000 business executives. Whereas there has been some measures of disruption in the past, no research to the authors’ knowledge has been conducted that measure both actual disruption and disruption hype.

The current fascination with disruption hides an awkward truth, we assume it is happening, but do we really know for sure? Disruption is rarely defined and almost never measured. Equally, the influence of the hype around disruption is hard to gauge. The authors do not know to what extent hype is driving management action. This is worrisome as the disruption “noise level” can lead to unhealthy collective thinking and bad business decision-making. Some rigour is required. To craft winning strategies, executives should take a more evidence-based approach for managing disruption.

The authors’ failed to find evidence of any correlation between the hype around an industry disruption and actual disruption within that industry. So the important conclusion for executives is “do not believe the hype”. We found some surprising differences by industry between actual disruption and the hype by industry.

Disruption is one of the most talked about subject in the field of strategy, yet there is little quantification. With this research, the authors’ aim is to advance the fact-based understanding of disruption. Disruption hype is never measured but has a strong influence on executives. The authors have quantified hype using online, search, social media and survey sources. Much more is needed to be able to measure hype more accurately.

The authors’ recommend a set of practical guidelines for executives to support fact-based strategy formulation: analysis of actual disruption, scenario planning and strategic responses.

The “noise” around industry disruption is so high that it is assumed to happen. Much of what is written is quasi-fake news. The authors need to rebalance the debate with fact-based analysis.

To authors’ knowledge, there has never been any fact-based analysis of both actual and hype disruption levels.

Research into the emergence of a hype requires a mixed methods approach that takes into account both the evolution over time and mutual influences across different types of media. The purpose of this paper is to present a methodological approach to detect an emerging hype in online communications.

The paper combines Auto Regressive Integrated Moving Average (ARIMA) time series modelling and semantic co-word networks, and this combination of methods provides a view on the emergence and development of a hype at the level of mutual influences across a heterogeneous set of newspaper and blog data. The subject scope of the paper is the climategate hype. The climategate hype was triggered by the online publication of a set of hacked e-mails belonging to climate researchers at the East Anglia University in November 2009.

The main findings show that the climategate hype was initiated in the blogs, and the newspapers were reacting to the blogs. At the level of semantics, the blogs and the newspapers framed the issue from opposite perspectives.

The combination of methods contributes theoretical insights to how blogs interact with more traditional media on hype generation and methodological insights to internet researchers investigating emergent online hypes. The method calls for further validation.

Investigating the emergence and evolution of a hype, and the interaction of the two media is relevant for journalists in becoming more reflexive in their practices and the cues from the outside world.

The paper is novel in its combination of the two specific methods, ARIMA time series modelling and co-word networks and its attempt to identify the media origins of a hype, and especially the interaction between blogs and newspapers.

The primary objective of this research is to provide a precise interpretation of the constructed machine learning model and produce definitive summaries that can evaluate the influence of investor sentiment on the overall sales of non-fungible token (NFT) assets. To achieve this objective, the NFT hype index was constructed as well as several approaches of XAI were employed to interpret Black Box models and assess the magnitude and direction of the impact of the features used.

The research paper involved the construction of a sentiment index termed the NFT hype index, which aims to measure the influence of market actors within the NFT industry. This index was created by analyzing written content posted by 62 high-profile individuals and opinion leaders on the social media platform Twitter. The authors collected posts from the Twitter accounts that were afterward classified by tonality with a help of natural language processing model VADER. Then the machine learning methods and XAI approaches (feature importance, permutation importance and SHAP) were applied to explain the obtained results.

The built index was subjected to rigorous analysis using the gradient boosting regressor model and explainable AI techniques, which confirmed its significant explanatory power. Remarkably, the NFT hype index exhibited a higher degree of predictive accuracy compared to the well-known sentiment indices.

The NFT hype index, constructed from Twitter textual data, functions as an innovative, sentiment-based indicator for investment decision-making in the NFT market. It offers investors unique insights into the market sentiment that can be used alongside conventional financial analysis techniques to enhance risk management, portfolio optimization and overall investment outcomes within the rapidly evolving NFT ecosystem. Thus, the index plays a crucial role in facilitating well-informed, data-driven investment decisions and ensuring a competitive edge in the digital assets market.

The authors developed a novel index of investor interest for NFT assets (NFT hype index) based on text messages posted by market influencers and compared it to conventional sentiment indices in terms of their explanatory power. With the application of explainable AI, it was shown that sentiment indices may perform as significant predictors for NFT sales and that the NFT hype index works best among all sentiment indices considered.

This paper aims to focus on 11 digital technologies (i.e. building information modeling, artificial intelligence and machine learning, 3D scanning, sensors, robots/automation, digital twin, virtual reality, 3D printing, drones, cloud computing and self-driving vehicles) that are portrayed in future trend reports and hype curves. The study concentrates on the current usage and knowledge of digital technologies in the Swedish architecture, engineering and construction (AEC) industry to gain an insight in the possible expectations and future trajectory of these digital technologies.

The study applies an abductive approach which is based on three different types of methods. These methods are a literature and document study which focused on 11 digital technologies, two workshops with industry (13 participants) and an online survey (N = 84).

The paper contributes to a current state analysis of the Swedish AEC industry concerning digital technologies and discusses the trajectory of these technologies for the AEC industry. The paper identifies hype factors, in which the knowledge of a digital technology is related to its usage. From the hype factors, four zones that show different stages of digital technology usage and maturity in the industry are induced.

The contribution of the paper is twofold. The paper shows insight into opportunities, the current barriers, use and knowledge of digital technologies for the different actors in the AEC industry. Furthermore, the study shows that the AEC industry is behind the traditional Gartner hype curves and contributes with defining four zones for digital technologies for the Swedish AEC industry: confusion, excitement, experimentation and integration.

Under current market conditions of corporate foresight, turbulence is a key element of the business landscape. Turbulence can be summarised using the trendy managerial acronym “VUCA”: volatility, uncertainty, complexity and ambiguity. This paper aims to combine, for the first time, scientific discussion of technological disruption with the VUCA approach. Gartner Hype Cycle is used as a case example of technological turbulence and “vucability”.

First, the authors present the key concepts of technological disruption and radical innovation. Both these concepts are highly relevant for modern corporate foresight. Second, the authors discuss the key elements of current technological transformation and summarise it to create a bigger picture. Third, the authors link this discussion to the VUCA approach. Fourth, the authors present the new corporate foresight framework, which is highly relevant for corporations and takes current technological transformation more seriously than previous proposals, which expect more stable business and a technological landscape.

Key issues in modern VUCA management are agility (response to volatility), information and knowledge management (response to uncertainty), restructuring (response to complexity) and experimentation (response to ambiguity). Useful foresight tools are challenging tools, decision-making tools, aligning tools, learning tools and the ability to combine these management tools in the practices of corporate foresight and management systems. The VUCA approach is a key solution concept to technological disruption.

The authors present the new corporate foresight framework and management tool based on foresight, which help leaders to manage VUCA – especially under the conditions of hyper-competition and technological disruption.

Corporate leaders should reinvent the strategic planning framework and adjust it to the VUCA conditions and simply be more strategic. Traps and typical failures of foresight are adopting it too early, giving up too soon, adapting too late and hanging on too long. In particular, technological transformation with disruptive technologies is changing and challenging many basic assumptions of business management and strategic planning. Our comparative analysis with Gartner Hype Cycle (fast technological changes from 2008 to 2016) verifies this important aspect of technological disruption.

This interview study examines Hungarian journalists' and copywriters' expectations of generative AI’s impact on their professions and factors influencing these views during a period of hype.

While acknowledging the specialized knowledge of journalists and copywriters relative to the general public, the study employs the sociology of expectations framework to interpret their anticipations not as objective forecasts of the future, but rather as phenomena shaped by diverse influences. The research comprises 30 semi-structured interviews conducted in spring 2023 to explore these expectations and their contributing factors.

Results reveal ChatGPT’s media coverage as pivotal, encouraging the professionals interviewed to experiment with AI, reassess their roles, and cause a shift in their job expectations. At the same time, this shift was limited. Skepticism about hyperbolic media formulations, their own experiences with ChatGPT and projecting its constraints into the future, contextual factors, and optimism bias contributed to moderating their expectations. They perceived AI as an enhancer of efficiency and quality, not as a radical disruptor. Copywriters were more open to integrating AI in their work, than journalists.

The results underscore the importance of further research to explore subjective experiences associated with technological change, particularly considering their complex social, psychological, and cultural influences.

The study uniquely contributes to the sociology of expectations by highlighting how a complex interplay of factors can shape professionals' anticipation of the impact of AI on their careers, including optimism bias and media hype.

For some years, it has been claimed that Building Information Modelling (BIM) will bring about major improvements to the productivity of the building industry. Yet, productivity has declined while claims for BIM have expanded. Often, BIM descriptions comprise the naïve framing and multiple fallacies of hype. The purpose of this paper is to present critical realist descriptions and explain their advantages compared to BIM hype descriptions.

A longitudinal critical realist case study of BIM causal mechanism and causal context.

Critical realist analysis reveals that hype about BIM underplays many inter-related causal requirements: all of which are needed to bring project business outcome from management action.

Many inter-related non-trivial causal factors need to be taken into account to achieve business outcome from BIM implementation action. Further, factors claimed at the outset to be adequate to achieve outcome from action may be less than adequate.

The originality of this paper is that critical realism analysis across six years is presented. This longitudinal data reveals that claims for BIM can be more future goals than current certainties. The value of this paper is that detailed analysis of hype descriptions is provided alongside critical realist descriptions.

An emerging application of Big Data is the addition of sensors and other micro‐electronic devices to engineer‐to‐order (ETO) goods such as one‐of‐a‐kind buildings and ships. The addition of micro‐electronic devices can enable the setting up and operation of smart buildings and smart ships. The purpose of this paper is to provide a critical realist analysis of Big Data hype. This is necessary to determine what challenges will need to be met before project businesses can achieve informational effects and transformational effects from Big Data technologies.

A critical realist study informed by reference to predictive theory and findings from action research. The predictive theory is concerned with the three different types of business effects that can come from information and communication technologies (ICTs): automational, informational, and transformational.

Critical realist analysis reveals that hype about Big Data underplays many challenges in achieving informational and transformational effects.

Many inter‐related non‐trivial factors need to be taken into account when considering investing in Big Data initiatives. These factors range from the planning of data sampling rates, through the robust fixing of sensors, to the implementation of data mining algorithms and signal models.

The originality of this paper is that critical realism is used in analysis of Big Data hype. The value of this paper is that it reveals a causal mechanism and causal context for project business Big Data application. This type of critical realist analysis can be applied to enable better understanding of necessary causal mechanisms and causal contexts for other ICT innovations.

Information vacuums (IVs) arise from organizational failure to satisfy the stakeholders’ informational demands during crises. The purpose of this paper is to expand Pang’s (2013) study of the phenomenon of IV by investigating its nature, stages, intensifying factors and resolution.

Print and social media data of five recent international crises with apparent IVs were analyzed.

Poor crisis communications are intensifying factors that induce media hijacks and hypes, distancing, and public confusion. A four-stage model maps the phenomenon into a flow chart describing its development. IV termination begins when organizations either respond with information or provide solutions, results, and/or compensation. Natural and strategic silence were observed and defined.

The study lays the foundation for future examination of how media literacy, governments, and culture, both societal and organizational, induce or exacerbate the phenomenon.

Immediate, adequate, transparent, credible, and consistent crisis responses manage the IV and crisis, diminish the intensification of subsequent crises, and potentially reduce image and reputational damages.

The knowledge of the phenomenon is further developed and new theoretical models are conceptualized to provide researchers and practitioners a clearer understanding of how an IV can develop, persist, deepen, and resolve.