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Together the hype level and business maturity equations form the hype cycle (see online version for colours)
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Abstract: We analyse longitudinal data of the 2008–2017 Gartner hype cycles
and key ICT technologies (151 technologies) in the world. In this study, we
have calculated six different index analyses, Our analyses use the following
index analyses: 1) ranking index analysis; 2) technology power index analysis;
3) better than other technology power inde...
Contexts in source publication
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... decision-makers may follow the trend, not even knowing the real potential of the technology. As we can see in Figure 1, the technology hype forms a sharp peak. The first generation of technology applications is a disappointment, and the hype suddenly drops. ...
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... Figure 1, the second equation is a classic technology S-curve and depicts technology maturity (see Fenn and Raskino, 2008;Steinert and Leifer, 2010). In the second equation, the S-curve shape of technology maturity is based on technology developing only slowly in the beginning. ...
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... investments into pilots and early adoptions are expensive (Steinert and Leifer, 2010). Together these two equations form the hype cycle (see Figure 1). In Figure 1, the GHC model combines the two curves (expectation hype and technology S-curve) seemingly in a mathematical way. ...
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... these two equations form the hype cycle (see Figure 1). In Figure 1, the GHC model combines the two curves (expectation hype and technology S-curve) seemingly in a mathematical way. However, Steinert and Leifer (2010) argue that Gartner does not provide a joint mathematical formula and the model has not been mathematically defined properly. ...
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... average technology power index was calculated based on yearly RIA data (sum of PI indices/number of yearly measurements). In Figure 10, the highest technology power index analysis is presented. In the figure, the largest power indexes (x-axis) are from 30 to 60, which gives the top 30 of a total of 151 IT technologies. ...
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... average technology power index is based on the average technology power index of the Gartner HC evaluations in 2008-2017. Figure 10 reveals which technologies have the highest technology power based on their rank. In these top 30 technologies, the power index is 60 at its highest and 30 at its lowest. ...
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... we can see that consumer-related services are becoming more popular, such as interactive TV, local-aware applications, internet micropayment stores, mobile application stores, mobile health monitoring, and consumer-generated media. In Figure 11, the technology power index analysis is presented for the section of technologies where the power index (x-axis) is from 24 to 30, giving a rank of 31-60 out of a total of 151 technologies based on the average technology power index of the Gartner HC evaluations in 2008 In this category, the difference is not large. The ten most powerful technologies in this category of the technologies ranked 31-60 are NFC, audio mining/speech analysis, electronic paper, enterprise taxonomy, activity streams, cognitive expert advisors, broadband over power lines, media tablets, content analysis, and wikis. ...
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... this category fall many consumer-related services and applications: media tablets, tablet PCs, consumer 3D printing, basic web services, wearables, home health monitoring, and application stores. In Figure 12, the technology power index analysis is presented. In the figure, the power index (x-axis) is from 15 to 23. ...
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... ten most powerful technologies in this category of the technologies ranked 61-90 are virtual assistants, wearable user interface, cloud computing, Web 2.0, public virtual words, online video, e-book readers, advanced analytics with self-service delivery, RFID, and gamification. In Figure 13, the lowest technology power index analysis is presented. In the figure, the power index (x-axis) is from 1 to 15. ...
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... will take from 5 to 10 years for them to become more powerful. In Figure 14, we present a histogram of the average technology power index evaluations in Gartner HC analyses in 2008. Figure 14 reveals that the differences between technology rankings are not very great. ...
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... Figure 14, we present a histogram of the average technology power index evaluations in Gartner HC analyses in 2008. Figure 14 reveals that the differences between technology rankings are not very great. We can observe that this average technology power index provides a slightly different kind of analysis and evaluation results compared to the previous RIA of the GHC technologies. ...
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... also calculated the average BTOTI index for our assessment (sum of BTOTI indices/number of yearly measurements). In Figure 15, the power index (x-axis) is from 30 to 57. If technology is better than other technology, it will get a higher index number. ...
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... technology is better than other technology, it will get a higher index number. In Figure 15, Figure 16 gives a better than other technology power index analysis for IT technologies ranked 31-60 in the Gartner HC reports in 2008-2017. The power index (x-axis) is from 23 to 29. ...
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... technology is better than other technology, it will get a higher index number. In Figure 15, Figure 16 gives a better than other technology power index analysis for IT technologies ranked 31-60 in the Gartner HC reports in 2008-2017. The power index (x-axis) is from 23 to 29. ...
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... Figure 17, the power index (x-axis) runs from 15 to 23. The following technologies have the highest BTOTI values in the 61-90 category: social network analysis, virtual assistants, wearable user interfaces, cloud computing, Web 2.0, public virtual words, online video, e-book readers, advanced analytics with self-service delivery, and RFID. ...
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... Figure 18, the lowest section of the better than other technology power index analysis is presented. In the figure, the power index (x-axis) is from 0 to 16. ...
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... 2017, Gartner forecast that those technologies would become popular after 5 to 10 years. In Figure 19, we present as a summary a histogram of the average BTOTI evaluations in Gartner HC analyses in 2008-2017. Again, Figure 19 reveals that the differences between technology rankings are not very big. ...
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... Figure 19, we present as a summary a histogram of the average BTOTI evaluations in Gartner HC analyses in 2008-2017. Again, Figure 19 reveals that the differences between technology rankings are not very big. We can observe that this average BTOTI provides a slightly different analysis and evaluation results compared to the previous RIA and TIA evaluations of the GHC technologies. ...
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... Table 3 we have reported our findings of the outlayer analysis I. We were able to find five outlayer ICT technologies. In Figure 21, we present the second outlayer analysis of 151 technologies in the GHC analyses. This analysis is based on the average technology power index (TIA) and the average BTOTI index of the GHC technologies. ...
Citations
... The literature on expectations about new technology suggest that early adopters have sometimes very high or exaggerated expectations [53]. Later expectations tend to decrease to a plateau value according to Gartner's hype cycle [54,55]. This concern is not plausible in this case because this survey was taken at a time that EMR systems were already widely used. ...
... Several waves of development followed, including mobile AR software, mobile AR hardware, tethering smart glasses, and standalone smart glasses. By consulting the Gartner Hype Cycle [32], we may note the hype phase of AR between 2010 and 2011, before the technology followed a downward trend. This curve characterizes most cutting-edge technologies and is mostly related to the commercial excitement produced by the media promotion conducted by big tech companies investing in development [33], which hits the contextual limit of society's capacity for technological adoption for that specific version at that moment in time. ...
This article presents the DEMOS prototype platform for creating and exploring multimodal extended-reality smart environments. Modular distributed event-driven applications are created with the help of visual codeless design tools for configuring and linking processing nodes in an oriented dataflow graph. We tested the conceptual logical templates by building two applications that tackle driver arousal state for safety and enhanced museum experiences for cultural purposes, and later by evaluating programmer and nonprogrammer students’ ability to use the design logic. The applications involve formula-based and decision-based processing of data coming from smart sensors, web services, and libraries. Interaction patterns within the distributed event-driven applications use elements of mixed reality and the Internet of Things, creating an intelligent environment based on near-field communication-triggering points. We discuss the platform as a solution to bridging the digital divide, analyzing novel technologies that support the development of a sustainable digital ecosystem.
... A görbe öt szakaszból áll, tengelyei a láthatóság és az idő (1. ábra) (KAIVO -OJA et al., 2020). Láthatóság tengelye a technológia pillanatnyi felkapottságát, idő tengelye az érettségét szemlélteti. ...
A koronavírus-járvány által okozott vészhelyzet következtében 2020 márciusától kezdve sorra zártak be a múzeumok világszerte, ami csak tovább erősítette a már jelenlévő igényt a kiállítások tárlatainak digitalizálására. Ez a radikális, kényszer szülte, ám a technológia fejlődésével egyre időszerűbb változás kihatott a virtuális múzeumok megítélésére, amelynek vizsgálata a jelen tanulmány fő témája. A virtuális múzeumok kialakításának felhasználói élmény központú vizsgálata kvalitatívan, feltáró jellegű használhatósági vizsgálat segítségével történt az egri Dobó István Vármúzeum és a Petőfi Irodalmi Múzeum virtuális tereiben. Ezt interjúkérdések követték az átélt élményekre vonatkozóan, majd a kapott adatok rendszerezése után hipotézisek kerültek megfogalmazásra, melyek kvantitatív alátámasztása vagy megcáfolása egy 550 fő által kitöltött kérdőív segítségével történt. Mindezen információk alapján lehetőség nyílt az ideális virtuális múzeum kialakítására és népszerűsítésére vonatkozó javaslatok megfogalmazására is, amely hasznos útmutató lehet a marketing szakemberek számára is.
Kulcsszavak: virtuális múzeumok, felhasználói élmény, használhatósági vizsgálat, kérdőíves megkérdezés
... A görbe öt szakaszból áll, tengelyei a láthatóság és az idő (1. ábra)(KAIVO -OJA et al., 2020). Láthatóság tengelye a technológia pillanatnyi felkapottságát, idő tengelye az érettségét szemlélteti. ...
With the dawn of the twenty-first century, the world has been in chaos, turmoil and a changing environment that is chaotic and difficult to predict. In the midst of rapid technological advancements, geopolitical shifts, dramatic demographic changes, ecological disasters and immigration, lives are being disrupted at a level of severity and frequency that seems to only increase. Most importantly, globalization and competitive market forces have created significant growth in the knowledge sector, a development that has a profound effect on society and higher education institutions. Together, these factors have accentuated a state of volatility, uncertainty, complexity and ambiguity that has been termed VUCA: volatility, uncertainty, complexity and ambiguity. The interaction between the four VUCA elements can lead to the breakdown of order in almost every organization, including the education and higher education sectors. Since students today have grown up with technology, they expect to have instant access all the time and anywhere to their learning materials. As opposed to this, a black swan event is an abnormal behaviour outside the normal expected behaviour, an event that has an extreme impact and a response that is rationalized retrospectively (Taleb, 2007). Black Swan events, like the COVID-19 pandemic that has just been reported, can throw a wrench in the works in a VUCA world. The twenty-first century has experienced some Black Swan events, such as 9/11, and the 2008 financial crisis; however, the COVID-19 pandemic, a global phenomenon occurring over the next few years, will be a unique blend of VUCA and Black Swan events (Hadar et al. in Rethinking teacher education in a VUCA world: student teachers' social-emotional competencies during the Covid-19 crisis. European Journal of Teacher Education, 1–14, 2020). Therefore, in the coming years and decades, higher education has entered uncharted territory that will require a great deal of agility and profound astuteness to progress. In reviewing the current situation and future challenges in the learning innovation space, we found that there is a need for a new set of tools and an updated framework that will help educators support innovative learning initiatives. It is for these reasons that in the following chapter we propose a two-pronged approach: Integration of the Disruptive Innovation Framework (Bower & Christensen, 1995) and the Transformative Strategic Framework for Learning Innovation (Salmon, European Journal of Open, Distance and E-Learning 17:220–236, 2014). In order to accomplish this, the Gartner hype cycle and Roger’s Diffusion of Innovation Model (Roger, 2010) are combined to create a framework for strategic planning and to provide educators with a practical framework to improve the implementation of interventions.
Die anhaltende Covid-19-Pandemie bestimmt das Geschehen der Weltwirtschaft. In Deutschland wird beispielsweise für das Jahr 2020 von einem Rückgang des preisbereinigten Bruttoinlandsprodukts von 5 % ausgegangen. Gleichzeitig ergeben sich aus den Herausforderungen, die derartige Krisen mit sich bringen, oftmals Anknüpfungspunkte für Innovationen. Die Blockchain-Technologie etwa stellt eine solche Innovation dar, deren Anfänge auf die Zeit der globalen Finanzkrise zurückgehen. Das im Rahmen der Finanzkrise verspielte systemische Vertrauen lieferte den Impuls für das Momentum der BCT, die auf einem fälschungssicheren Konsens-algorithmus aufbaut. Im energiewirtschaftlichen Kontext stieg das Interesse an der Blockchain-Technologie im Zusammenhang mit dem Projekt „Brooklyn Microgrid“ im Jahr 2016 sprunghaft an und mündete in einem „Hype“.
Seit der ersten Erwähnung im energiewirtschaftlichen Kontext ist mehr als ein halbes Jahrzehnt vergangen. In der Folge stellt sich daher die Frage: Blockchain, quo vadis? Der vorliegende Beitrag widmet sich dieser Fragestellung und liefert zwei Forschungs-beiträge. Der erste Forschungsbeitrag beinhaltet eine systematische Literatur- sowie Patentrecherche. Mit dem Ergebnis der bibliografischen Analyse der erhobenen Daten können die bisherigen Forschungsaktivitäten abgeschätzt und die Blockchain-Technologie in den Gartner Hype Cycle eingeordnet werden. Für den zweiten Forschungsbeitrag wird eine weitere bibliografische Analyse der Stichprobe im Hinblick auf acht Anwendungsbereiche der Blockchain-Technologie in der Energiewirtschaft durchgeführt und erlaubt einerseits bisherige Forschungsschwerpunkte zu
identifizieren und andererseits bisher nicht adressierte Forschungsbereiche aufzudecken.
Die Auswertung der Literatur- und Patentdaten zeigt, dass die ersten Ergebnisse der Blockchain-Forschung und -Entwicklung seit dem Jahr 2017 veröffentlicht werden und die Anzahl der Publikationen seither kontinuierlich ansteigt. Die Einordnung der Blockchain-Technologie in den Gartner Hype Cycle zwischen dem Gipfel der überzogenen Erwartung und dem Tal der Enttäuschung deckt sich mit bisherigen Veröffentlichungen des Forschungs- und Beratungsunternehmens Gartner. Nach einzelnen Anwendungsbereichen differenziert, zeigt sich, dass drei zentrale Forschungsschwerpunkte „P2P-Märkte & -Handel“; „Asset- & Netzmanagement“ sowie „Datenmanagement“ sind. Die Forschungsaktivitäten des Anwendungsbereichs „P2PMärkte und -Handel“ erscheinen vergleichsweise weit fortgeschritten und lassen auf Grund der Vielzahl an Pilotprojekten auf einen hohen Anwendungsbezug der Forschungsaktivitäten schließen.
In the present area, the outbreak of COVID-19, customer behavior have been seen toward their individual specific need, which encourages advanced-manufacturing industries to provide mass personalization of goods and services. The Covid-19 crises bring opportunities for industries and service providers to enhance their capability for a fault-free environment, zero failure, anti-fragile, and improve production capacity. The present paper provides an overview of the sustainability of Industry 6.0 in a global perspective with vision, objective, and transformation of Industrial Revolutions. The sole aim of industry 6.0 is to seizure the new technologies, which can be applied worldwide and deliver wealth, prosperity away from the job and provide growth to nations across all planetary boundaries. This revolution would promote living harmony with nature, support the principle of sustainability where technology would not be a thing, and promote the human virtual digital twin where all can simultaneously see physical goods and virtual product information.
