## 1 Introduction
The agent-based model developed in innovation diffusion research can be used as a reference because scholars consider online social platform adoption as the process of \"accepting something emerging (i.e., joining an emerging platform)\" spreading through the social network, i.e., the process of innovation diffusion [22; 23]. [PERSON] et al. (2016), (2010), (2007) and [PERSON] et al. (2011) [19; 24; 25; 26] used a utility threshold model that closely resembles the process of social platform adoption. The model clearly defines the process by which individuals are aware of emerging things through WOM and mass media, as well as the process by which they accept new things under informational influences (perceptions of service quality) and normative effects (the proportion of people around them who accept new things). However, the model fails to capture the various strategies managers use to engage platform users in spreading WOM, such as initiating interactions among members, and cultivating opinion leaders [7; 27; 28]. In addition, the model does not define the different behavioral characteristics of elderly people with different digital literacy when they interact with others and react to promotional strategies. Therefore, it is necessary to adapt the model to make it more consistent with the process of elderly social platform adoption. To fill in the aforementioned gaps, this study aims to answer the following question: how does the digital literacy of the elderly population affect the effectiveness of platform promotional strategies? According to their information seeking expertise and the information sources they utilize to create meaning, we divide the elderly into PIRs and AISs. An empirical study was conducted to assess the behavioral characteristics of PIRs and AISs. With the assistance of our empirical results and research on innovation diffusion and platform promotion, we built an agent-based model to simulate the multistage process of social platform adoption among elderly people with different digital literacy levels. We used market penetration (that is, the proportion of older people joining the platform in the target population) to measure the macro results of social platform adoption. The impact of the proportion of PIRs on market penetration and the impact of each strategy on the market penetration of the social platform under different proportions of PIRs are analyzed. The results show that a high proportion of PIRs in the target population leads to the low market penetration of the platform. Improving service quality has a stronger effect on market penetration as the proportion of PIRs decreases. Strategies directly related to information diffusion, such as expanding the reach of mass media and increasing the number of seeds, are more effective when the proportion of PIRs is higher. In addition, cultivating opinion leaders is most effective when the proportion of PIRs is moderate. The effect of increased interaction time is marginal decreasing, regardless of the proportions of PIRs. The rest of the article is organized as follows. Section 2 reviews the literature on digital literacy to classify the elderly on social platform and innovation diffusion. Section 3 describes the empirical study aiming to assess the behavioral characteristics of AISs and PIRs. Section 4 analyzes the differentiated behaviors of the elderly in the process of platform promotion to build an agent-based model. Section 5 explains the parameter setting of the model. Section 6 analyzes the results of simulation experiments. Section 7 discusses the study's main conclusions, contributions, implications and limitations.