Social culture and innovation diffusion: a theoretically founded agent-based model
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Social culture and innovation diffusion: a theoretically founded agent-based model Meihan He 1 & Jongsu Lee 1 # Springer-Verlag GmbH Germany, part of Springer Nature 2020
Abstract This study proposes an agent-based model to theoretically investigate the effects of social culture on innovation diffusion. The model assumes that social culture (i.e., individualism, power distance, and uncertainty avoidance from Hofstede’s cultural dimension theory) has a direct effect on the small-world network structure and individual characteristics. We further explore how the characteristics of innovation influence the diffusion process. We find that individualism has a positive effect on the diffusion speed in the early stage, whereas uncertainty avoidance and power distance have negative effects on innovation diffusion. The effect of uncertainty avoidance on the diffusion speed turns positive after the early stage of diffusion and the negative effect of power distance becomes positive in the late stage. We compare real-world diffusion data with the proposed agent-based model, finding some similarities in the diffusion patterns. The characteristics of innovation affect innovation diffusion when the uncertainty avoidance is high. However, when both uncertainty avoidance and individualism are low, the effect of the characteristics of an innovation on diffusion is restricted. Keywords Hofstede . Social culture . Diffusion of innovation . Agent-based modeling .
Computational method JEL classification O33 . C63 . Z10 . D11
* Jongsu Lee [email protected] Meihan He [email protected]
1
Technology Management, Economics, and Policy Program, College of Engineering, Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul 08826, South Korea
M. He, J. Lee
1 Introduction Schumpeter (1939) finds that innovation is an essential driver of economic dynamics. He divides the innovation process into four phases, namely invention, innovation, diffusion, and imitation (Burton-Jones 1999; Schumpeter 1934), and shows that the diffusion and imitation processes have great impacts on the economy (Schumpeter 1934; Śledzik 2013). The diffusion of a new product is as important as its invention. To conduct a successful diffusion, organizations invest considerable effort in advertising and marketing. According to the statistics published by Gartner, marketing expenditure represents 11.2% of revenue on average globally (McIntyre and Virzi 2018). The retail industry allocates the highest percentage, 21.9%, of expenditure to advertising. With the development of information and communication technology, advertising and marketing behaviors in online social networks are more effective than offline (Evans 2009). According to the report of PwC, Global Entertainment & Media Outlook 2019–2023, in 2018 digital advertising expenditure in the United States is $30 billion higher than TV advertising expenditure (van Eeden and Chow 2019). Organizations tend to target directly individual social networks to improve marketing efforts when introducing an innovation (Peres e
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