Research On The Influence Of Social Platform Sharing Mechanism Design On Consumers’ Decision-Making

The rapid development of social media has changed people’s information searching and sharing behaviors and experiences, which will influence more and more decision-making processes, like consumers’decision-making process. Therefore, analyzing the relationship between social sharing and consumers’decision-making process is a research question needed special attention. However, now it’s still lacking of exploring the relationship from human computer interaction (HCI) and user study perspective. Firstly, for consumers’ decision-making process, the author proposes a factor model called social-sharing-based consumers’ decision-making process to provide a theory for the research work. Secondly, for the design of social platform sharing mechanism (DSPSM), the author analyses the features of sharing mechanism design of several social media platforms, takes checking-in as a point to study sharing behaviors, and explores how DSPSM supports sharing behaviors. Then, for the influence of social sharing behavior on consumers’ decision-making, the author studies shopping related sharing (SRS) behaviors, and analyses the effect laws behind according to the theory model proposed. Finally, the opinion from users with stronger social influence is one of the most important factors that can affect decision-making process. So it is necessary to study how to measure users’ social influence. Current studies mainly apply global measure metrics, while the author proposes a metric called within-field influence to accurately measure user’s social influence so that it can easily recognize opinion leaders with stronger within-field influence.The three important steps (needs recognition, information collection and sharing after purchasing) of consumers’ decision-making process are affected by social sharing. Therefore, the author proposes a hypothetical model called social sharing based consumers’ decision-making process. The model indicates that external environment features and personal features can influence perceived benefit and trust, and then influence consumers’ decision-making process. Moreover, it can be used for both traditional and online shopping. The hypothetical factor model is validated via the questionnaire analysis to be a formal one.DSPSM can influence social sharing behaviors directly. Therefore, the author try to study the features of DSPSM on different social media platforms, such as built-in consumer reviewing platform and attached commerce-oriented SNS platforms on online shopping websites, relationship-emphasized SNS platforms, instant messenger (IM) platforms, dedicated consumer reviewing platforms and LBS platforms. The author applies online data analysis according to checking-in data and user interview in Lab into the study to analyze sharing behaviors. The key points concerned are the features of time, area and text sentiment.SRS behaviors can influence consumers’ decision-making process. Therefore, the author studies SRS behaviors via user interview in Lab (plus observation) and online questionnaire analysis. There are 29 participants recruited and 206 valid questionnaires collected. According to the above data, the author finds that consumers’ comments and shop reputation from online shopping websites, consumers’ comments on dedicated consumers reviewing social platforms, geographically nearby friends’ comments and SRS comments on LBS can influence consumers’ decision-making process. All the findings can also verify the model proposed.The measurement of social influence is a very important question. Current related studies mainly use the number of fans or messages without considering that influence can work only within certain fields. Therefore, the author proposes within-field influence model. Firstly, applying machine learning method to classify the information into different fields, and then measuring users’ influence within the fields. Field information and field relationship are two aspects needed concern. With much better information and fans, the influence will be much stronger. Within-field influence is evaluated from the perspectives of stability and correlation with other global metrics. It is verified that within-field social influence is stable, but there is no certain correlation between it and other global metrics. So they can not be replaced by each other.