Abstract
In light of the rapid growth of social networks around the world, this study analyses the impact of social networks on the diffusion of products and demonstrates the effective way to diffuse products in the society where social networks play an important role. We construct a consumer behaviour model by multi-agent simulation taking the movie market as an example. After validating it by using data from 13 US movies, we conduct simulations. Our simulation results show that the impact of social networks on the diffusion differs according to the customers’ expectations and evaluation for a movie. We also demonstrate the effective weekly advertising budget allocations corresponding to the types of movies. We find that the difference of weekly advertising budget allocations gives greater impact on the diffusion with the growth of social networks. This paper provides firm’s managers with important suggestions for diffusion strategy considering the impact of social networks.
Highlights
Social networking services such as Twitter and Facebook have grown rapidly around the world and are generating a significant impact on changing consumer behaviour and the diffusion process of products
Impact of Social Networks on Diffusion where, pb is the effect of production budgets, adv represents the effect of advertising, pre depicts the effect of previous movies and original novels, Fp (t) is the time variation of consumers’ interests in a new movie, represents the individuality of agent i, and Di is a dummy variable that denotes whether or not agent i has an interest in the movie’s genre (Di =1 if agent i has an interest, Di =0 if otherwise)
The results of our simulations that utilise this model demonstrate the impact of social networks on consumer behaviour and product diffusion
Summary
Social networking services such as Twitter and Facebook have grown rapidly around the world and are generating a significant impact on changing consumer behaviour and the diffusion process of products. We developed a consumer behaviour model considering social networks’ effects by multi-agent simulation using the movie market as an example. Impact of Social Networks on Diffusion where, pb is the effect of production budgets, adv represents the effect of advertising, pre depicts the effect of previous movies and original novels, Fp (t) is the time variation of consumers’ interests in a new movie, represents the individuality of agent i, and Di is a dummy variable that denotes whether or not agent i has an interest in the movie’s genre (Di =1 if agent i has an interest, Di =0 if otherwise). These data are available at ‘The Numbers (http://www.the-numbers.com/box-office/2010),’ and ‘The Comics Chronicles (http://www.comichron.com/titlespotlights.html),’ respectively
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