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1 – 10 of over 2000
Article
Publication date: 22 July 2022

Bushan Mathavan, Ali Vafaei-Zadeh, Haniruzila Hanifah, T. Ramayah and Sherah Kurnia

This paper aims to investigate the key enablers and inhibitors that influence the intention to use fitness wearables using the value-based adoption model (VAM).

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Abstract

Purpose

This paper aims to investigate the key enablers and inhibitors that influence the intention to use fitness wearables using the value-based adoption model (VAM).

Design/methodology/approach

Data were collected using a structured online questionnaire from 323 respondents who had never used fitness wearables. A purposive sampling technique was used in this study. Smart PLS was employed to test the research framework and hypotheses using a two-step approach.

Findings

The findings support some of the hypotheses developed with R2 values of 0.622 for perceived value (PV) and 0.567 for intention to use fitness wearable. Perceived enjoyment, perceived social image and perceived usefulness had a positive effect on PV. In addition, health information sensitivity (HIS) was positively related to perceived privacy risk and health information accuracy was positively related to perceived usefulness. Surprisingly, this study did not find any significant relationship between perceived fee, perceived privacy risk, perceived health increase and perceived design aesthetics with PV.

Practical implications

This study's findings can help designers and manufacturers design fitness wearables by considering factors that users find valuable, thus satisfying consumers' needs.

Originality/value

This study tries to model behavioural intention of fitness wearable usage of individual users by using the VAM with the addition of two new antecedences, HSI and health information accuracy, to better explain the behaviour.

Details

Asia-Pacific Journal of Business Administration, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1757-4323

Keywords

Book part
Publication date: 19 July 2022

Pallavi Seth and Kamal Gulati

Introduction: There is a variety of wearables and health applications available in the market which allow the tracking of various health and lifestyle measures like blood…

Abstract

Introduction: There is a variety of wearables and health applications available in the market which allow the tracking of various health and lifestyle measures like blood sugar, calorie counter, number of steps, sleep patterns, etc. After the Covid-19 pandemic, people have become more aware of their health and use these wearables to maintain a healthy lifestyle. Insurance companies in India are also eyeing the potential usage of these wearables in life and health insurance.

Purpose: This research aims to look at the emergence of wearables and health apps and their usage in India’s life and health insurance industry. This study also focuses on how these devices might benefit insurers’ business models and some of the pitfalls to consider.

Methodology: The study used both primary and secondary data. A survey was conducted to understand the customer perception towards usage of wearables. The secondary research included the analysis of the integration of wearables by insurance companies.

Findings: The research would be helpful to the insurance companies as it would help them to understand the customer’s viewpoint for the usage of wearables in the insurance industry. This study would also allow insurers to understand new dimensions, such as where the wearables improve customer satisfaction and engagement. The study results would be helpful for the customers for the appropriate usage of wearables and the internet of things (IoT). Insurance companies can provide better pricing and make personalised insurance plans that ultimately help customers.

Details

Big Data: A Game Changer for Insurance Industry
Type: Book
ISBN: 978-1-80262-606-3

Keywords

Article
Publication date: 8 April 2022

Constanza Bianchi, Sven Tuzovic and Volker G. Kuppelwieser

This empirical study examines the drivers of consumer intention to adopt wearable technology for healthcare in a South American country. Specifically, it proposes and…

Abstract

Purpose

This empirical study examines the drivers of consumer intention to adopt wearable technology for healthcare in a South American country. Specifically, it proposes and tests a model of nonuser consumer intention to adopt fitness trackers for healthcare purpose in Chile.

Design/methodology/approach

This study draws on the technology acceptance framework UTAUT2 to develop and test a conceptual model of wearable technology adoption. Data were collected through an online survey applied to 470 nonusers of wearable technology in Santiago, Chile.

Findings

Findings indicate that hedonic motivation, social influence and perceived usefulness have the strongest influence on intention to adopt fitness trackers in Chile for healthcare. In addition, health motivation is an indirect predictor of consumer's intention to adopt wearable technology through its effect on perceived usefulness.

Practical implications

The study contributes to a better understanding of consumer intention to adopt wearable technology for healthcare objectives in a less developed country in South America. Findings are useful for wearable technology managers, retail business and public policymakers.

Originality/value

Despite the vast growth and importance of wearable technology for healthcare purposes, academic research considering less developed countries is scarce, especially the South American region. The proposed model and findings can extend this research gap. Theoretical and managerial implications are discussed as well as implications for public policy.

Details

Information Technology & People, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0959-3845

Keywords

Article
Publication date: 29 April 2022

Bowei Hu and Sumin Koo

The aim of this study was to develop a smart wearable mask designed for the prevention of respiratory infectious diseases by understanding consumer's preferences in…

Abstract

Purpose

The aim of this study was to develop a smart wearable mask designed for the prevention of respiratory infectious diseases by understanding consumer's preferences in designs and functions of the smart wearable masks.

Design/methodology/approach

To develop a smart mask design, a survey was conducted on Chinese consumers in their 20–40s and analyzed their mask wearing behaviors, preferences and caring aspects of masks. The collected data were analyzed to identify the demographic characteristics of the subjects surveyed by using the SPSS program, and technical statistical analysis was conducted. To identify differences in demographic characteristics, an independent samples t-test, one-way analysis of variance and Scheffe's ad hoc test were conducted.

Findings

Based on the research results, design guidelines for wearable masks were defined, and four wearable mask designs were developed and presented in 2D and 3D images based on the design guidelines. There were significant differences among people with different backgrounds.

Originality/value

It is significant that this research presents smart wearable mask design guidelines and designs through supplementation and improvement of existing mask. It is expected that this research provides basic empirical data for mask designs through the planning of smart wearable mask designs and surveys assessing consumer perceptions, attitudes and satisfaction.

Details

International Journal of Clothing Science and Technology, vol. 34 no. 5
Type: Research Article
ISSN: 0955-6222

Keywords

Article
Publication date: 7 December 2021

Prashant Raman and Kumar Aashish

There are two-fold objectives to this research. First is to analyse the importance of technology readiness (TR) for the users in using sports and fitness wearable devices…

Abstract

Purpose

There are two-fold objectives to this research. First is to analyse the importance of technology readiness (TR) for the users in using sports and fitness wearable devices in India. And second is to explore if gymnasium (gym) users are much more technologically ready as compared to non-gym users to use sports and fitness wearable devices.

Design/methodology/approach

The study uses technology readiness and acceptance model (TRAM) to examine the users' intention to use sports and fitness wearable devices. Data from a survey of 907 respondents from India were collected and partial least squares (PLS)-structural equation modelling (SEM) technique was used to empirically examine it.

Findings

The outcomes reveal that innovativeness and optimism have a positive influence on perceived ease of use (PEOU) and perceived usefulness (PU), and insecurity and discomfort have a negative influence on PEOU and PU. Both PEOU and PU act as important determinants in the user's intention to use sports and fitness wearable devices. The multi-group analysis (MGA) suggests that gym users tend to exhibit more positive intention towards using sports and fitness wearable devices and show higher probability of using the wearable devices relative to non-gym users.

Originality/value

There are hardly any studies on intention to use sports and fitness wearable devices in India. The current research tries to understand the intention behind the gym users and non-gym users to use sports and fitness wearable devices. The outcomes of the research will help the marketers to align their promotional campaign based on the new segmentation variable “gym-user/non-gym user”. The research also highlights the importance of TR in the use of sports and fitness wearable devices in India.

Details

International Journal of Sports Marketing and Sponsorship, vol. 23 no. 4
Type: Research Article
ISSN: 1464-6668

Keywords

Article
Publication date: 16 December 2021

Bishwajit Nayak, Som Sekhar Bhattacharyya, Saurabh Kumar and Rohan Kumar Jumnani

The purpose of this study is to identify the major factors influencing the adoption of health-care wearables in generation Z (Gen Z) customers in India. A conceptual…

Abstract

Purpose

The purpose of this study is to identify the major factors influencing the adoption of health-care wearables in generation Z (Gen Z) customers in India. A conceptual framework using push pull and mooring (PPM) adoption theory was developed.

Design/methodology/approach

Data was collected from 208 Gen Z customers based on 5 constructs related to the adoption of health-care wearables. Confirmatory factor analysis and structural equation modelling was used to analyse the responses. The mediation paths were analysed using bootstrapping method and examination of the standardized direct and indirect effects in the model.

Findings

The study results indicated that the antecedent factors consisted of push (real-time health information availability), pull (normative environment) and mooring (decision self-efficacy) factors. The mooring factor (MOOR) was related to the push factor but not the pull factor. The MOOR, in turn, was related to the switching intention of Gen Z customers for health wearables adoption.

Research limitations/implications

The research study extended the literature related to the PPM theory in the context of the adoption of health wearables among Gen Z customers in India.

Practical implications

The study outcome would enable managers working in health wearable organizations to understand consumer behaviour towards health wearables.

Social implications

The use of health wearables among Gen Z individuals would lead to future generations adopting a healthy lifestyle resulting in an effective workforce and better economy.

Originality/value

This was one of the few studies which have explored the PPM theory to explore the factors for the adoption of health wearables among Gen Z customers in India.

Details

Journal of Information, Communication and Ethics in Society, vol. 20 no. 1
Type: Research Article
ISSN: 1477-996X

Keywords

Article
Publication date: 14 October 2021

Mona Bokharaei Nia, Mohammadali Afshar Kazemi, Changiz Valmohammadi and Ghanbar Abbaspour

The increase in the number of healthcare wearable (Internet of Things) IoT options is making it difficult for individuals, healthcare experts and physicians to find the…

Abstract

Purpose

The increase in the number of healthcare wearable (Internet of Things) IoT options is making it difficult for individuals, healthcare experts and physicians to find the right smart device that best matches their requirements or treatments. The purpose of this research is to propose a framework for a recommender system to advise on the best device for the patient using machine learning algorithms and social media sentiment analysis. This approach will provide great value for patients, doctors, medical centers, and hospitals to enable them to provide the best advice and guidance in allocating the device for that particular time in the treatment process.

Design/methodology/approach

This data-driven approach comprises multiple stages that lead to classifying the diseases that a patient is currently facing or is at risk of facing by using and comparing the results of various machine learning algorithms. Hereupon, the proposed recommender framework aggregates the specifications of wearable IoT devices along with the image of the wearable product, which is the extracted user perception shared on social media after applying sentiment analysis. Lastly, a proposed computation with the use of a genetic algorithm was used to compute all the collected data and to recommend the wearable IoT device recommendation for a patient.

Findings

The proposed conceptual framework illustrates how health record data, diseases, wearable devices, social media sentiment analysis and machine learning algorithms are interrelated to recommend the relevant wearable IoT devices for each patient. With the consultation of 15 physicians, each a specialist in their area, the proof-of-concept implementation result shows an accuracy rate of up to 95% using 17 settings of machine learning algorithms over multiple disease-detection stages. Social media sentiment analysis was computed at 76% accuracy. To reach the final optimized result for each patient, the proposed formula using a Genetic Algorithm has been tested and its results presented.

Research limitations/implications

The research data were limited to recommendations for the best wearable devices for five types of patient diseases. The authors could not compare the results of this research with other studies because of the novelty of the proposed framework and, as such, the lack of available relevant research.

Practical implications

The emerging trend of wearable IoT devices is having a significant impact on the lifestyle of people. The interest in healthcare and well-being is a major driver of this growth. This framework can help in accelerating the transformation of smart hospitals and can assist doctors in finding and suggesting the right wearable IoT for their patients smartly and efficiently during treatment for various diseases. Furthermore, wearable device manufacturers can also use the outcome of the proposed platform to develop personalized wearable devices for patients in the future.

Originality/value

In this study, by considering patient health, disease-detection algorithm, wearable and IoT social media sentiment analysis, and healthcare wearable device dataset, we were able to propose and test a framework for the intelligent recommendation of wearable and IoT devices helping healthcare professionals and patients find wearable devices with a better understanding of their demands and experiences.

Details

Library Hi Tech, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0737-8831

Keywords

Article
Publication date: 7 December 2021

Aarthy Prabakaran and Elizabeth Rufus

Wearables are gaining prominence in the health-care industry and their use is growing. The elderly and other patients can use these wearables to monitor their vitals at…

Abstract

Purpose

Wearables are gaining prominence in the health-care industry and their use is growing. The elderly and other patients can use these wearables to monitor their vitals at home and have them sent to their doctors for feedback. Many studies are being conducted to improve wearable health-care monitoring systems to obtain clinically relevant diagnoses. The accuracy of this system is limited by several challenges, such as motion artifacts (MA), power line interference, false detection and acquiring vitals using dry electrodes. This paper aims to focus on wearable health-care monitoring systems in the literature and provides the effect of MA on the wearable system. Also presents the problems faced while tracking the vitals of users.

Design/methodology/approach

MA is a major concern and certainly needs to be suppressed. An analysis of the causes and effects of MA on wearable monitoring systems is conducted. Also, a study from the literature on motion artifact detection and reduction is carried out and presented here. The benefits of a machine learning algorithm in a wearable monitoring system are also presented. Finally, distinct applications of the wearable monitoring system have been explored.

Findings

According to the study reduction of MA and multiple sensor data fusion increases the accuracy of wearable monitoring systems.

Originality/value

This study also presents the outlines of design modification of dry/non-contact electrodes to minimize the MA. Also, discussed few approaches to design an efficient wearable health-care monitoring system.

Details

Sensor Review, vol. 42 no. 1
Type: Research Article
ISSN: 0260-2288

Keywords

Open Access
Article
Publication date: 22 November 2021

Rosiane Serrano, Larissa Fortunati and Daniel Pacheco Lacerda

The fashion sector is complex. It involves multiple actors with distinct and potentially conflicting interests, forming a value ecosystem. Thus, knowing the interested…

Abstract

Purpose

The fashion sector is complex. It involves multiple actors with distinct and potentially conflicting interests, forming a value ecosystem. Thus, knowing the interested parties and belonging to the fashion sector may be a means to promote technological innovation, such as products with wearables. The purpose of this paper to identify the participants of the fashion ecosystem from the perspective of wearable technologies and develop a conceptual model.

Design/methodology/approach

The present work aims to identify the participants (actors) and develop a conceptual model of the fashion ecosystem from the perspective of wearable technologies. The systematic literature review is the recommended method to qualitatively analyze documents and identify the interested parties (actors) in the fashion sector in order to design the proposed conceptual model.

Findings

From the studies, the conceptual model of the fashion value ecosystem was designed, and the wearable product was considered its core business. The studies identified addressed ecosystems of fashion value in general but not specific to wearable products and their relations with other complementary industries.

Research limitations/implications

The model was designed using secondary data only. Its validation is relevant through interviews with experts.

Originality/value

In terms of relevance, when conducting a systematic literature review, there were no studies that included wearable technologies in the fashion ecosystems discussed and their relations with other industries. The topic of wearables is an emerging subject that needs further research aiming to insert this technology in productive sectors.

Details

Innovation & Management Review, vol. 19 no. 2
Type: Research Article
ISSN: 2515-8961

Keywords

Article
Publication date: 13 August 2021

Shweta Pandey, Deepak Chawla, Sandeep Puri and Luz Suplico Jeong

Notwithstanding the novelty and importance of wearable fitness devices, few studies have focussed on comparing the drivers of adoption and usage of wearable fitness in the…

Abstract

Purpose

Notwithstanding the novelty and importance of wearable fitness devices, few studies have focussed on comparing the drivers of adoption and usage of wearable fitness in the context of developing countries. This study aims to explore factors that drive overall acceptance of wearable fitness devices in developing countries (India and the Philippines) and whether the impact of these factors on the intention to adopt (INT) differs by country and gender.

Design/methodology/approach

The study extends the existing body of knowledge by developing a model that integrates the impact of various perceived benefits (health, autonomy, social, hedonic, symbolic), health self-efficacy (HEALTHSE) and individual characteristics (technological innovativeness [TI]) on the INT wearable fitness devices and the moderating impact of country and gender. The analysis was carried out using partial least square and data of 343 respondents.

Findings

This study finds that the INT wearable fitness devices by consumers in developing countries are positively impacted by hedonic, health and autonomy, HEALTHSE and TI. Symbolic and social factors do not have any significant impact on the overall INT wearable fitness devices. However, there are country and gender-specific differences that are consequential to the development of marketing strategies.

Research limitations/implications

The framework and results are specific to the two countries and limited by convenience sampling. Future research can focus on replication across different countries and extend the model with additional contextual factors such as perceived risks.

Originality/value

To the best knowledge of the authors, this is one of the few studies to examine and compare the drivers of adoption of wearable fitness devices in lesser researched developing countries. Also, it is one of the few studies to compare the moderating impact of country and gender in the context of the INT wearable devices. The study provides a theoretical and methodological foundation for future research, as well as practical implications for global companies developing and promoting wearable fitness devices.

Details

Journal of Asia Business Studies, vol. 16 no. 4
Type: Research Article
ISSN: 1558-7894

Keywords

1 – 10 of over 2000