Nonlinear Dynamic Analysis of New Product Diffusion considering Consumer Heterogeneity
When a new product enters the market, individual consumers’ decision-making behavior and purchase time are uncertain. Based on the dynamics of epidemic transmission theory and agent modeling technology, this study proposes a new coupling model through the combination of the improved SEIR epidemic mo...
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| Format: | Article |
| Language: | English |
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Wiley
2020-01-01
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| Series: | Complexity |
| Online Access: | http://dx.doi.org/10.1155/2020/2915797 |
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| _version_ | 1832560047489548288 |
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| author | Zhongjun Tang Huike Zhu |
| author_facet | Zhongjun Tang Huike Zhu |
| author_sort | Zhongjun Tang |
| collection | DOAJ |
| description | When a new product enters the market, individual consumers’ decision-making behavior and purchase time are uncertain. Based on the dynamics of epidemic transmission theory and agent modeling technology, this study proposes a new coupling model through the combination of the improved SEIR epidemic model and the heterogeneous agent model. This model considers consumer heterogeneity resulting from three aspects in consumers’ sensitivity, network topology, and considerations of information flow received. It aims to analyze how consumer heterogeneity affects the scale and speed of new product diffusion. The proposed model showed that consumers’ characteristics and behavior combination at the microlevel lead to the diversity of nonlinear diffusion curves at the macrolevel for new products. Moreover, a pilot study is conducted to simulate this model and examine how to estimate the model’s parameters using aggregated data about film products. The pilot study results suggested that different consumer characteristics and behavior combinations affect the scale and speed of new product diffusion to varying degrees. In different scenarios, there were significant differences in the influence of the degree of consumer heterogeneity on diffusion, accompanied by the occurrence of threshold. The results of the empirical analysis in this study are in line with reality. |
| format | Article |
| id | doaj-art-8aae57409f66430db2e07d0f2c9a3f64 |
| institution | Kabale University |
| issn | 1076-2787 1099-0526 |
| language | English |
| publishDate | 2020-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Complexity |
| spelling | doaj-art-8aae57409f66430db2e07d0f2c9a3f642025-02-03T01:28:33ZengWileyComplexity1076-27871099-05262020-01-01202010.1155/2020/29157972915797Nonlinear Dynamic Analysis of New Product Diffusion considering Consumer HeterogeneityZhongjun Tang0Huike Zhu1Research Base of Beijing Modern Manufacturing Development, College of Economics and Administration, Beijing University of Technology, No. 100 Pingleyuan, Beijing, 100124, ChinaResearch Base of Beijing Modern Manufacturing Development, College of Economics and Administration, Beijing University of Technology, No. 100 Pingleyuan, Beijing, 100124, ChinaWhen a new product enters the market, individual consumers’ decision-making behavior and purchase time are uncertain. Based on the dynamics of epidemic transmission theory and agent modeling technology, this study proposes a new coupling model through the combination of the improved SEIR epidemic model and the heterogeneous agent model. This model considers consumer heterogeneity resulting from three aspects in consumers’ sensitivity, network topology, and considerations of information flow received. It aims to analyze how consumer heterogeneity affects the scale and speed of new product diffusion. The proposed model showed that consumers’ characteristics and behavior combination at the microlevel lead to the diversity of nonlinear diffusion curves at the macrolevel for new products. Moreover, a pilot study is conducted to simulate this model and examine how to estimate the model’s parameters using aggregated data about film products. The pilot study results suggested that different consumer characteristics and behavior combinations affect the scale and speed of new product diffusion to varying degrees. In different scenarios, there were significant differences in the influence of the degree of consumer heterogeneity on diffusion, accompanied by the occurrence of threshold. The results of the empirical analysis in this study are in line with reality.http://dx.doi.org/10.1155/2020/2915797 |
| spellingShingle | Zhongjun Tang Huike Zhu Nonlinear Dynamic Analysis of New Product Diffusion considering Consumer Heterogeneity Complexity |
| title | Nonlinear Dynamic Analysis of New Product Diffusion considering Consumer Heterogeneity |
| title_full | Nonlinear Dynamic Analysis of New Product Diffusion considering Consumer Heterogeneity |
| title_fullStr | Nonlinear Dynamic Analysis of New Product Diffusion considering Consumer Heterogeneity |
| title_full_unstemmed | Nonlinear Dynamic Analysis of New Product Diffusion considering Consumer Heterogeneity |
| title_short | Nonlinear Dynamic Analysis of New Product Diffusion considering Consumer Heterogeneity |
| title_sort | nonlinear dynamic analysis of new product diffusion considering consumer heterogeneity |
| url | http://dx.doi.org/10.1155/2020/2915797 |
| work_keys_str_mv | AT zhongjuntang nonlineardynamicanalysisofnewproductdiffusionconsideringconsumerheterogeneity AT huikezhu nonlineardynamicanalysisofnewproductdiffusionconsideringconsumerheterogeneity |