MOBILE APPS IMPROVEMENT RECOMMENDATION BASED ON FACTORS THAT AFFECT CUSTOMER IN MAKING ONLINE FINANCIAL INVESTMENT

• Main Author: ZHAFARINA NIM 14414014, SAFIRA
• Format: Final Project
• Language: Indonesia
• Online Access: https://digilib.itb.ac.id/gdl/view/30767
• Institution: Institut Teknologi Bandung

The increase number of mobile phone and internet users in Indonesia every year have caused the increase number of Financial Technology (Fintech) Company. Fintech Company consists of eight fields, one of the fields is online investment. In general, investment becomes very interesting for Indonesian people. This fact can be seen by the increase number of investors every year. Online investment is able to be done via website or mobile apps. The percentage of Indonesian people using mobile apps to invest online is 3.24% (Kelola Student Ambassador, 2017). In order to attract Indonesian investors to invest online via mobile apps, the determination of the factors that affect investor intention in using online investment mobile apps is needed. Therefore, fintech company that provide online investment mobile apps is able to create a strategy based on these critical factors. <br /> <br /> In data collection processes, primary data are collected from respondents that fit the target market criteria for some of financial technology companies that provide online investment mobile apps. The target respondents are Indonesian people, 17 years old and above, both who has ever dan never use online investment mobile apps. The data collection processes are divided into some stages, which are sampling design creation, questionnaire creation, questionnaire distribution part I and questionnaire improvement, questionnaire distribution part II and questionnaire testing, and questionnaire final distribution. In this process, data from 255 rerspondents are collected. <br /> <br /> The reserach model is adopted from individual investor investing intention with behaviour as mediator model (Ali, 2011), consumer intention in using mobile banking model (Chinna, dkk., 2016), and consumer behaviour in investment intention model (Li, 2013). In data processing processes, data clearing is firstly performed to eliminate outlier and unconsistent respondents. This process results on 200 respondents data that will be utilized in the next process. The model is evaluated by using confirmatory factor analysis (CFA) for measurement model and structural equation modeling (SEM) for structural model. In the measurement model evaluation, five model’s indicators, which are II2, EA3, PR1, PR2, and UF1 is deleted. Based on the evaluation results, there is one factor that directly affect online investment intention, which is attitude toward online investment. Moreover, there are two factors that indirectly affect online investment intention, which are perceived trust and usefulness. <br /> <br /> By referring to the data processing, especially the hypothesis tests, the strategy recommendation for financial technology company that provide online investment apps to increase investor intention in online investment are created. The strategy recommendations are create partnership with influencer and company in related industry, create promotion with interesting merchant, minimize verification process duration, addition of some features, which are referral, connection, display of number of investor and funds managed in investment product, robo-advisor, smart simulation, instruction for new apps-downloader, article, discussion, and product benchmarking, and make a short video instruction for every feature in the apps.