Analysis Of Factors Influencing User's Intention To Recommend Bike-sharing Apps

The division of bike-sharing market is extremely fierce,noticing that there are a large number of users in real life recommend products or apps to others,there is a word of mouth effect,the effect is even better than the advertising heavily invested by companies.This study continues the previous perception from the internal and external perspective to analyze the factors affecting the user's intention to recommend the use of shared bicycle app,and extract the latest influencing factors in the supplementary study related to the impact mechanism and the relationship between the factors through interviews.In reality,it is especially important for the users to share the bicycle application's recommendation because it helps operators to attract more potential users and to make potential users register,experience and use to become the new word of mouth communicators and eventually form a virtuous circle.However,the research on bike sharing so far mainly focuses on optimizing the scheduling of the bike sharing,the selection of the delivery site and the optimal number of bike sharing.Domestic research on the intent of influencing the recommendation of bike sharing users is less.This study aims to investigate the issue of factors that influence the user's intention to share the intention of sharing a bicycle through structural equation modeling,further discover the relevant factors and their relationship,and improve the existing research system.The main research work of this dissertation is as follows:Firstly,on the basis of literature research,this paper defines the intent of the user-recommended bike sharing app and defines its theoretical and structural equation model theory.Secondly,based on the existing theoretical results,the main assumptions that affect the user's intention of sharing a bicycle application are proposed based on the characteristics of the bike sharing,and the research hypotheses are put forward.The influencing factors include perceived usefulness,perceived ease of use,user expectancy,user satisfaction,etc.Finally,a formal questionnaire and model are formed.The students and friends are selected as the empirical subjects of the questionnaires and questionnaires are conducted one after the other.Data processing and analysis,model checking and correction.Finally,the conclusions and recommendations of the empirical research are put forward based on the output of the modified model.This article's innovation lies in not sticking to the predecessors'excellent experience,and through the further interviews and questionnaires to extract the latest impact factors to enrich the research content.The data was collected from 133 shared bike app customers and the results showed the following key findings:(1)User loyalty is the most important factor affecting user's recommendation intention,Economic incentive has a positive impact on loyalty;(2)Satisfaction has no significant effect on user's recommendation intention,but satisfaction has a significant influence on loyalty.Based on the conclusions,the hypothetical situation is analyzed and practical inspiration is presented to the platform.