Beauty Consumption Matchmaking Mechanism for Confirming the Requirement Specification of app Development in the Post-COVID-19 Era

Frontiers in Psychology 13 (2022)
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Abstract

COVID-19 began to spread worldwide in early 2020. Various governments have taken measures such as isolation, travel bans, and evacuation, mandating people to wear masks and go out less, in an attempt to prevent the spread of the virus. Governments also restrict human contact service industries, including beauty and hair salons. When the pandemic was very serious, consumers had great doubts about going for hairdressing so the beauty industry was greatly affected. This study designed and developed an app platform that considers the COVID-19 and is used for the psychological role of consumer safety. The methodology of this research is a qualitative study. Based on the Capability, Opportunity, Motivation, Behavior model, and presenting the context of capabilities, opportunities, and motives of the theoretical framework, this study investigates the factors that identify the demand for the development of the platform for the beauty industry app matching mechanism. Four groups of people including consumers, beauty technicians, store managers, and application development engineers all conduct interviews based on their ability, opportunity, and motivation after experiencing the using application of OpenBeautiful. The results found that all groups of people already had the knowledge and ability to avoid infection in a pandemic, so it was possible to establish the need and feasibility of using the app platform. The use of the beauty industry app platform can bring new consumption patterns and career opportunities, and can trigger more business behavior activities. Therefore, this study starts from the COM-B model, and then explores the user needs of the platform according to the COM-B model framework, and proposes the mechanism and platform of app matching. Finally, based on the conclusion of the study, we propose practices and suggestions for the future operation of the app matching platform.

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Chang Wen
New York University

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