FACTORS AFFECTING ONLINE BUYING BEHAVIORS IN TOKOPEDIA: ASSESSMENT USING FFF MODEL

• Main Author: Rinaldi, Christopher
• Format: Theses
• Language: Indonesia
• Online Access: https://digilib.itb.ac.id/gdl/view/68324
• Institution: Institut Teknologi Bandung

Increased convenience of commerce for both sellers and buyers can be attained with the utilization of online shopping platforms. The e-tailing or e-commerce is a form of retail from increased use and spread of internet. Novelty and different aspects of buying behaviors in online shopping necessitates a framework of evaluation in evaluating factors that might affect the purchase intentions of customers utilizing the online platforms. The adoption of e-commerce platforms and the subsequent attempts to spread the adoption through the mobile applications may be beneficial in driving the use of e-commerce in Indonesia. Several issues were noted in the use of the mobile phones regarding the mobile applications. Several reviews had indicated that the Tokopedia mobile application was relatively difficult to use; lower perceived ease of use may result in lower user experience and satisfaction, thus causing lower rate of mobile application use and potentially its adoption. Prior studies had noted that several characteristics of the consumers might affect the purchasing decisions on using these mobile applications from their chosen e-commerce platform. Hence, the study requiring use of the several frameworks available on measuring the shopping behaviors of the consumers. One of such models had been proposed prior: factors, filtering elements, and filtering behavior (FFF) model. The study was aimed to determine the correlation of demographic factors in association to the perceived risks in using Tokopedia as an online shopping platform A cross-sectional study in evaluating the demographic variables and its correlation with the perceived scores in ease of use, privacy, security, and user interface (UI) aesthetic ratings was performed. The samples were collected through a questionnaire spread online with all Indonesians that had used Tokopedia included in the study. Descriptive statistics were used to describe questionnaire scores and demographics. Spearman correlation was used to search the association and strength of demographics and scores of perceptions of the application. Significant correlation was found with education (r = 0.098, p < 0.05) and UI rating (r = -0.121, p < 0.05) with perceived ease of use with its UI; significant correlation was found in income per month (r = -0.108, p < 0.05), search function accuracy (r = -0.136, p < 0.01), and UI rating (r = -0.137, p < 0.01) with the perceived safety. Income per month (r = 0.106, p < 0.05), date of birth (r = 0.129, p < 0.01), application ease of use (r = 0.105, p < 0.05), and search function accuracy (r = -0.199, p < 0.01) were significantly correlated with perceived trustworthiness. Analysis with Kruskal-Wallis ANOVA had revealed significant association on the perceived ease of use of the features on the mobile application with the ratings on user interface and their association with the perceived ease of use, safety, and trust in using the platform. Higher ratings on user interface, specifically, was associated with higher perceived ease of use on the usage of the mobile application on the study. The study concludes that some demographics characteristics, such as highest attained education, income per month, dan date of birth may place different importance on different aspects on the user interface (UI) part of the application to evaluate their perceived risk during the usage of the online shopping platform. Several aspects related to the user interface design such as ease of use, may significantly affect the perceived safety and trust on the usage of the mobile platforms. Based on the study results above, the recommended solution in solving the business issue regarding the mobile application of the Tokopedia is to develop an alternative user interface to be compared with the currently used and available user interface. Alternative user interface design was targeted to collect analytics data to further determine other factors related to the design of the interface to further increase perceived user interface quality.