Health Concerns Versus Mobile Data Needs: Conjoint Measurement of Preferences for Mobile Communication Network Scenarios

Arning, Katrin; Kowalewski, Sylvia; Ziefle, Martina

doi:10.1080/10807039.2013.838127

Cited by 26 publications

(7 citation statements)

References 41 publications

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“…So far, we only separately assessed the levels of perceived benefits and barriers. However, acceptance studies (Arning et al., ; Zaunbrecher, Arning, Falke, & Ziefle, ) show that the overall acceptance in favor of or against a technology is a weighing of benefits and barriers, which thereby identifies individual tradeoffs in the risk decision. Future studies will therefore have to explore tradeoff decisions for novel driving technologies.…”

Section: Discussion and Future Research Dutiesmentioning

confidence: 99%

“…The risk adaptation process is not necessarily related to one specific technology, but applies to different (large‐scale) technologies that are directly influencing societies and peoples' lives, as, e.g., energy infrastructure technology (Kluge, Kowalewski, & Ziefle, ; Midden & Huijts, ; Zaunbrecher, Arning, Falke, & Ziefle, ) and mobile communication systems (Arning, Kowalewski, & Ziefle, ; Dohle, Keller, & Siegrist, ). Also, data sharing in the Internet and privacy protection (Horst, Kuttschreuter, & Gutteling, ; Miyazaki & Fernandez, ) are further examples.…”

Section: Introductionmentioning

confidence: 99%

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sCARy! Risk Perceptions in Autonomous Driving: The Influence of Experience on Perceived Benefits and Barriers

2018

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The increasing development of autonomous vehicles (AVs) influences the future of transportation. Beyond the potential benefits in terms of safety, efficiency, and comfort, also potential risks of novel driving technologies need to be addressed. In this article, we explore risk perceptions toward connected and autonomous driving in comparison to conventional driving. In order to gain a deeper understanding of individual risk perceptions, we adopted a two‐step empirical procedure. First, focus groups (N=17) were carried out to identify relevant risk factors for autonomous and connected driving. Further, a questionnaire was developed, which was answered by 516 German participants. In the questionnaire, three driving technologies (connected, autonomous, conventional) were evaluated via semantic differential (rating scale to identify connotative meaning of technologies). Second, participants rated perceived risk levels (for data, traffic environment, vehicle, and passenger) and perceived benefits and barriers of connected/autonomous driving. Since previous experience with automated functions of driver assistance systems can have an impact on the evaluation, three experience groups have been formed. The effect of experience on benefits and barrier perceptions was also analyzed. Risk perceptions were significantly smaller for conventional driving compared to connected/autonomous driving. With increasing experience, risk perception decreases for novel driving technologies with one exception: the perceived risk in handling data is not influenced by experience. The findings contribute to an understanding of risk perception in autonomous driving, which helps to foster a successful implementation of AVs on the market and to develop public information strategies.

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Section: Discussion and Future Research Dutiesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

sCARy! Risk Perceptions in Autonomous Driving: The Influence of Experience on Perceived Benefits and Barriers

2018

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“…Initially, the CA approach was used mainly in economic science and market research enabling the assessment of innovative products and respective specificities. Since the last years, CA has been increasingly used within the landscape of acceptance research as well-covering diverse contexts, such as the acceptance of information systems [ 31 ], decisions within the context of healthcare [ 32 , 33 ], or acceptance studies focusing on energy technologies, e.g., [ 34 , 35 ].…”

Section: Methodsmentioning

confidence: 99%

Let’s Talk about TEX—Understanding Consumer Preferences for Smart Interactive Textile Products Using a Conjoint Analysis Approach

Heek

Brauner

Ziefle

2018

Sensors

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Interactive textiles are reaching maturity. First technology augmented textiles in form of clothes and furnitures are becoming commercially available. In contrast to the close link between technological development and innovations, future users’ acceptance and usage of such interactive textiles has not been integrated sufficiently, yet. The current study investigates future users’ consumer behavior and acceptance of interactive textiles using a scenario-based conjoint analysis study, which was presented in an online questionnaire (n=324). Two prototypical interactive textiles were focused on: a smart jacket and a smart armchair. To assess the textile products, the participants had to choose the preferred product alternative consisting each of the acceptance-relevant factors “connectivity”, “input modality”, “feature range”, “usability”, and “ease of cleaning”and their respective levels. The results revealed that the “ease of cleaning” is the most important decision criterion for both textile devices (even more important for the smart jacket), followed by “feature range”, “connectivity”, and “usability”. In contrast, the “input modality” is perceived as least important. The study also identified user profiles based on the projected consumer behavior (“adopters”, “rejecters”, and “undecided”) for both products. Besides the differences in product evaluation and projected consumer behavior, the user groups are significantly influenced by the individual affinity to textiles (both products) and gender (smart jacket). The findings are used to derive design and communication guidelines referring to interactive textiles in order to incorporate users’ needs, wishes, and requirements into future products.

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“…Recent work (for example, [26] and [27]) has focused on improving the accuracy and validity of HRA methods. Recent work (for example, [26] and [27]) has focused on improving the accuracy and validity of HRA methods.…”

Section: Shortcomings Of Non-simulation Based Hramentioning

confidence: 99%

“…While the perceived risk for earthquakes, for example, is specifically related to geothermal energy technology, the broad aloofness towards economic or environmental related risks represent more unspecific fears that were also reported for other energy technologies [23,24], but appear in completely different contexts, such as V2X technologies [25], information and communication technologies [26,27], or, even medical technologies [28,29]. While the perceived risk for earthquakes, for example, is specifically related to geothermal energy technology, the broad aloofness towards economic or environmental related risks represent more unspecific fears that were also reported for other energy technologies [23,24], but appear in completely different contexts, such as V2X technologies [25], information and communication technologies [26,27], or, even medical technologies [28,29].…”

Section: Perceived Transparency In Communication About Geothermal Energymentioning

confidence: 99%

Digital Human Modeling. Applications in Health, Safety, Ergonomics and Risk Management: Human Modeling

Duffy¹

2015

Lecture Notes in Computer Science

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Health Concerns Versus Mobile Data Needs: Conjoint Measurement of Preferences for Mobile Communication Network Scenarios

Cited by 26 publications

References 41 publications

sCARy! Risk Perceptions in Autonomous Driving: The Influence of Experience on Perceived Benefits and Barriers

sCARy! Risk Perceptions in Autonomous Driving: The Influence of Experience on Perceived Benefits and Barriers

Let’s Talk about TEX—Understanding Consumer Preferences for Smart Interactive Textile Products Using a Conjoint Analysis Approach

Digital Human Modeling. Applications in Health, Safety, Ergonomics and Risk Management: Human Modeling

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