| 负面口碑、社会互动与创新扩散:基于小世界网络的仿真 |
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| 引用本文： | 邢梦珏,曹吉鸣,冯晓威,刘聪.负面口碑、社会互动与创新扩散:基于小世界网络的仿真[J].运筹与管理,2022,31(8):217-224. |
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| 作者姓名： | 邢梦珏 曹吉鸣 冯晓威 刘聪 |
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| 作者单位： | 同济大学 经济与管理学院,上海 200092 |
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| 基金项目： | 国家自然科学基金资助项目(71602107) |
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| 摘 要： | 为探究创新扩散失败的原因及作用机理,在创新扩散微观模型中引入负面口碑,建立个体在社会互动影响下的决策模型,并进行小世界网络中的多智能体仿真分析,研究网络结构、抵抗领袖比例、意见领袖创新性和社会规范约束力对创新扩散的影响。结果表明,考虑负面口碑的创新扩散曲线呈“S”形变化,但扩散深度受限;高度聚集的社会网络更有利于创新扩散。抵抗领袖比例越高,创新扩散速度和深度越小,且负面口碑作用范围越大;当抵抗领袖比例高于意见领袖比例时则会导致扩散失败。意见领袖创新性的提高可以缓解负面口碑的消极影响并促进创新扩散。社会规范约束力对创新扩散深度的影响随网络结构变化呈现不同态势。研究不但丰富了现有创新扩散理论,而且对开发创新推广策略具有指导意义。
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| 关 键 词： | 创新扩散 负面口碑 社会互动 小世界网络 多智能体仿真 |
| 收稿时间： | 2020-08-25 |
Negative Word-of-Mouth,Social Interaction and Innovation Diffusion: Simulation Based on Small-World Network |
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| XING Meng-jue,CAO Ji-ming,FENG Xiao-wei,LIU Cong.Negative Word-of-Mouth,Social Interaction and Innovation Diffusion: Simulation Based on Small-World Network[J].Operations Research and Management Science,2022,31(8):217-224. |
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| Authors: | XING Meng-jue CAO Ji-ming FENG Xiao-wei LIU Cong |
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| Affiliation: | School of Economics and Management, Tongji University, Shanghai 200092, China |
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| Abstract: | To explore the causes and mechanisms of innovation diffusion failure, negative word-of-mouth (WoM) is introduced into the micro-level of innovation diffusion model, and individuals' decision-making model under the influence of social interactions is established. Multi-agent-based simulation is conducted in small-world networks to explore the impacts of network structure, the proportion of resistance leaders, the innovativeness of opinion leaders, and the constraint of social norms on innovation diffusion. The results show that the diffusion curve considering negative WoM appears as an “S” shape, but the diffusion depth is limited. Highly clustered social networks are more conducive to innovation diffusion. The higher the proportion of resistance leaders, the lower the speed and depth of innovation diffusion, and the wider range the influence of negative WoM. When the proportion of resistance leaders surpasses that of opinion leaders, it will lead to diffusion failure. An increase in the innovativeness of opinion leaders can alleviate the impact of negative WoM and promote innovation diffusion. The influence of the constraint of social norms on innovation diffusion depth varies with network structure. The research not only enriches the existing innovation diffusion theory but also provides guidance on the formulation of innovation promotion strategies. |
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| Keywords: | innovation diffusion negative word-of-mouth social interaction small-world network multi-agent-based simulation |
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