The Design of Wearable Smart Products Based on Big Data

Zhou, Donghong

doi:10.1109/ipec54454.2022.9777433

Cited by 2 publications

(1 citation statement)

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“…In recent years, smart wearable products have seen significant growth in consumption among electronic and digital products. Being a class of mobile smart devices combining modern mobile smart technology and daily wearable products, they often integrate into consumers' daily life in the form of glasses, bracelets, wristwatches, gloves, shoes, accessories, and other products [1]. The mainstream functions of these products are carried out around sports guidance, medical rehabilitation, health monitoring, and other areas, aligning with the mainstream demands and trends of modern consumers [2].…”

Section: Introductionmentioning

confidence: 99%

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

2024

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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: Introductionmentioning

confidence: 99%