Design of Brand Business Model Based on Big Data and Internet of Things Technology Application

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Abstract

Appropriate business models are very important for enterprises. With the advent of the new century, the rapid development and application of technologies such as the Internet of Things and big data have become more and more widely used, which provides great convenience for people's daily life. With the rise and development of the Internet of Things and big data technology, human work and life have become easier and easier, and it has also greatly changed human production and development. Under the fierce market competition, enterprises pay more and more attention to the independent research and development capabilities of their own brand products. With the rapid development of the Internet age, the status of brands in the improvement of business models is also increasing. The brand business model design must not only meet the ever-changing market consumer demand but also conform to the ever-changing fashion trends. The article briefly analyzed the development and application of the Internet of Things and big data technology and optimized the design method of the brand business model by using big data technology in design of the brand business model. On this basis, a decision support method for a brand business model based on a data warehouse was proposed to achieve scientific, efficient, and accurate brand product development. In order to understand consumers' consumption habits and awareness of brands, the article randomly selected 400 people to conduct a survey. It was found that 45% of male respondents preferred commercials with simple and elegant colors; 38% of female respondents preferred commercials with minimalist styles. Modern consumers are mainly pragmatic, and the design of brand business models should be developed in this regard.

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APA

Yao, S. (2022). Design of Brand Business Model Based on Big Data and Internet of Things Technology Application. Computational Intelligence and Neuroscience, 2022. https://doi.org/10.1155/2022/9189805

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