Researchers at the Indian Institute of Technology, Mandi, analyzed various factors that influence herd adoption of wearable technology for personal health care. They use mathematical models to analyze data collected from surveys and provide insights into the marketing effectiveness of online reviews.
The survey results are published in the Journal of Marketing Communications.The research was led by Dr. Saumir DixitHumanities and Social Sciences Assistant Professor, IIT Mandyco-authored with PhD student Anjali Pathania IIT Mandy and Dr. Gohar RasulGraduate School of Business, Central University of Jammu, Jammu.
The team’s recent research aims to understand the drivers of pastoralism in adopting wearable technology for personal health care. The use of such devices has increased since the outbreak of the COVID-19 pandemic. Examples of such devices include fitness trackers, smartwatches, wearable sensors, and wearable medical devices. This includes oximeters, which were widely used to monitor blood oxygen levels during the pandemic. Wearable devices can connect to smartphones and other sources to display health-related data and provide features such as alerts, reminders and personalized recommendations.
Recommendations and reviews by other users have traditionally been the main drivers of adoption for any product, including wearable devices. Historically, these reviews have been word of mouth, but advances in Web 2.0 technology have enabled consumers to easily and freely experience services and products at scale and in real-time through various means such as social media and social media. Now you can share. Online review site. Today, online reviews are the electronic equivalent of word-of-mouth (eWOM) and can influence individual ‘crowds’ or group behaviors in the adoption of wearable technology in personal healthcare.
Researchers at IIT Mandi aimed to understand the role that online reviews play in inducing others to purchase and use wearable technology for personal health care. They surveyed 434 of her wearable technology his users and analyzed the data using the method of Partial Least Squares Structural Equation Modeling (PLS-SEM) with Smart PLS.
Describing the research expertise, Dr. Saumya Dixit of IIT Mandi said: A review of the adoption of wearable technology in healthcare. ”
According to the analysis, by reading reviews written by users with similar backgrounds and needs, and combining usage information related to ease of use, usefulness of wearable technology for personal health management, and company reputation, , could influence whether a potential user decides to adopt. of wearable healthcare devices.
While discussing other recommendations based on the results of the analysis, IIT Mandi, Ms Anjali Pathania, Ph.D. In addition, we provide gay information-based filters and review management systems/algorithms on her platform online to reduce information overload and encourage adoption of wearable her devices for personal health management by potential users. should be promoted. ”
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