Influence of Extrinsic and Intrinsic Attributes on Consumers’ Attitude and Intention of Using Wearable Technology

Bakhshian, Sonia; Lee, Young‐A

doi:10.1080/10447318.2022.2041904

Cited by 12 publications

(5 citation statements)

References 57 publications

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“…Consumers have diverse product demands for smart wearable products, which have considerable market value [13,14,19,29]. Attention to consumer demands can foster a favorable user experience and stimulate sustainable consumer behavior [24,25]. KANO analysis can be a reliable method for analyzing consumer demand in design research [12,41,42,43,44].…”

Section: Resultsmentioning

confidence: 99%

“…pointed out that for smart wearable products, objectively understanding consumer demand types is beneficial for accurately grasping demands during product design, enabling users to achieve both psychological and physiological satisfaction [23]. Product design centered on demands can become a reliable means to enhance the added value of smart wearable products, boost consumer satisfaction, and promote market growth [24,25]. Overall, product design can serve as an effective way to meet the consumer demands of ecommerce products.…”

Section: Research Backgroundmentioning

confidence: 99%

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Identification of Demand Type Differences and Their Impact on Consumer Behavior: A Case Study Based on Smart Wearable Product Design

2024

KSII TIIS

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Thorough understanding of user demands and formulation of product development strategies are crucial in product design, and can effectively stimulate consumer behavior. Scientific categorization and classification of demands contribute to accurate design development, design efficiency, and success rates. In recent years, e-commerce has become important consumption platforms for smart wearable products. However, there are few studies on product design and development among those related to promoting platform product services and sales. Meanwhile, design strategies focusing on real consumer needs are scarce among smart wearable product design studies. Therefore, an empirical consumer demand analysis method is proposed and design development strategies are formulated based on a categorized interpretation of demands. Using representative smart bracelets from wearable smart products as a case, this paper classifies consumer demands with three methods: big data semantic analysis, KANO model analysis, and satisfaction analysis. The results reveal that analysis methods proposed herein can effectively classify consumer demands and confirm that differences in consumer demand categories have varying impacts on consumer behavior. On this basis, corresponding design strategies are proposed based on four categories of consumer demands, aiming to make product design the leading factor and promote consumer behavior on e-commerce platforms. This research further enriches demand research on smart wearable products on e-commerce platforms, and optimizes products from a design perspective, thereby promoting consumption. In future research, different data analysis methods will be tried to compare and analyze changes in consumer demands and influencing factors, thus improving research on impact factors of product design in e-commerce.

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Section: Resultsmentioning

confidence: 99%

Section: Research Backgroundmentioning

confidence: 99%

Identification of Demand Type Differences and Their Impact on Consumer Behavior: A Case Study Based on Smart Wearable Product Design

2024

KSII TIIS

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“…It is possible that wearables were the least well tolerated as they are the only sensors that require direct participant interaction-increasing the intrusion on free-living compared with ambient sensors-and that further work toward a more seamless transition between digital sensing and physical wearable use [57] could help improve wearable acceptability in PD. The inclusion of health-tracking features in wearables has been found to improve their acceptability related to passive sensing [58,59]. This is possibly related to moving away from a reliance upon, or conversely, a suspicion of, technology and toward a relationship of trust through confidence in technology as a helpful instrument with which to visualize symptoms and therefore better understand our bodies [60].…”

Section: Multimodal Sensor Acceptability Including Privacy-preserving...mentioning

confidence: 99%

Acceptability of an In-home Multimodal Sensor Platform for Parkinson Disease: Nonrandomized Qualitative Study

Morgan¹,

Tonkin²,

Craddock³

et al. 2022

JMIR Hum Factors

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Background Parkinson disease (PD) symptoms are complex, gradually progressive, and fluctuate hour by hour. Home-based technological sensors are being investigated to measure symptoms and track disease progression. A smart home sensor platform, with cameras and wearable devices, could be a useful tool to use to get a fuller picture of what someone’s symptoms are like. High-resolution video can capture the ground truth of symptoms and activities. There is a paucity of information about the acceptability of such sensors in PD. Objective The primary objective of our study was to explore the acceptability of living with a multimodal sensor platform in a naturalistic setting in PD. Two subobjectives are to identify any suggested limitations and to explore the sensors’ impact on participant behaviors. Methods A qualitative study was conducted with an inductive approach using semistructured interviews with a cohort of PD and control participants who lived freely for several days in a home-like environment while continuously being sensed. Results This study of 24 participants (12 with PD) found that it is broadly acceptable to use multimodal sensors including wrist-worn wearables, cameras, and other ambient sensors passively in free-living in PD. The sensor that was found to be the least acceptable was the wearable device. Suggested limitations on the platform for home deployment included camera-free time and space. Behavior changes were noted by the study participants, which may have related to being passively sensed. Recording high-resolution video in the home setting for limited periods of time was felt to be acceptable to all participants. Conclusions The results broaden the knowledge of what types of sensors are acceptable for use in research in PD and what potential limitations on these sensors should be considered in future work. The participants’ reported behavior change in this study should inform future similar research design to take this factor into account. Collaborative research study design, involving people living with PD at every stage, is important to ensure that the technology is acceptable and that the data outcomes produced are ecologically valid and accurate. International Registered Report Identifier (IRRID) RR2-10.1136/bmjopen-2020-041303

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“…However, prevailing research has focused on one specific area of flexible electronics-wearable technologies. Wearable technology refers to a category of smart electronic devices that feature biological and physiological data analysis [5] and are worn by users. The technology finds applications in household wearables such as clothes, smart-watches, shoes, and jewelry.…”

Section: Introductionmentioning

confidence: 99%

Key factors and performance criteria of wearable strain sensors based on polymer nanocomposites

Zhagiparova¹,

Kalimuldina²,

Diaby³

et al. 2023

Nano Futures

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Recently, there has been a growing demand for wearable electronic devices/strain sensors in soft robotics body-health monitoring, human-machine interfaces and human motion detection. Wearable strain sensors feature fast and multi-stimuli sensitivity, high flexibility, ultra-stretchability and biocompatibility. Although the progress in flexible strain sensors is exponential, the production of wearable sensors undergoes several challenges, such as reliability and reproducibility. An in-depth understanding of the sensing mechanism of the flexible strain sensors based-polymeric nanocomposites is needed to fabricate reliable and reproducible sensors and move from the prototype phase into the industry phase. In this review, types of strain sensors and key parameters such as linearity, gauge factor (sensitivity), hysteresis and durability are explained in the context of the recently published work. In addition, current challenges and perspectives in relation to the wearable strain sensors are delineated.

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Influence of Extrinsic and Intrinsic Attributes on Consumers’ Attitude and Intention of Using Wearable Technology

Cited by 12 publications

References 57 publications

Identification of Demand Type Differences and Their Impact on Consumer Behavior: A Case Study Based on Smart Wearable Product Design

Identification of Demand Type Differences and Their Impact on Consumer Behavior: A Case Study Based on Smart Wearable Product Design

Acceptability of an In-home Multimodal Sensor Platform for Parkinson Disease: Nonrandomized Qualitative Study

Key factors and performance criteria of wearable strain sensors based on polymer nanocomposites

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