COVID-19 pandemic changed how society behaves. Travel and social restrictions, commonly associated with the term lockdown became popular and ubiquitous. Given the rise of gig economy and mobile app delivery in the past several years, combined with lockdowns during the pandemic, and the application of telemedicine becomes essential. Halodoc is one of the popular telemedicine applications in Indonesia, having several useful features such as text-based doctor consultation and prescription drug order-delivery, and Halodoc is easily preferred by many. This article explored the motivation behind using Halodoc as the preferred method of getting health service during the pandemic, behind the perceived usefulness and perceived ease of use of the application, we found that fear of missing out (FOMO) has an indirect role in the application adoption in society, especially during lockdowns, where social interaction is limited to social media and other internet-based platforms. The reason why FOMO can be an important factor in technology adoption and how advertisers should explore FOMO is further discussed.
<span lang="EN-US">We proposed an approach of retailer segmentation using a hybrid swarm intelligence algorithm and recency frequency monetary (RFM)-location model to develop a tailored marketing strategy for a pharmacy industry distribution company. We used sales data and plug it into MATLAB to implement ant clustering algorithm and K-means, then the results were analyzed using RFM-location model to calculate each clusters’ customer lifetime value (CLV). The algorithm generated 13 clusters of retailers based on provided data with a total of 1,138 retailers. Then, using RFM-location, some clusters were combined due to identical characteristics, the final clusters amounted to 8 clusters with unique characteristics. The findings can inform the decision-making process of the company, especially in prioritizing retailer segments and developing a tailored marketing strategy. We used a hybrid algorithm by leveraging the advantage of swarm intelligence and the power of K-means to cluster the retailers, then we further added value to the generated clusters by analyzing it using RFM-location model and CLV. However, location as a variable may not be relevant in smaller countries or developed countries, because the shipping cost may not be a problem. </span>
The emergence of the COVID-19 pandemic has changed the learning system in higher education which is becoming distance learning using information technology. In addition to providing good opportunities, online learning poses risks that can threaten students. The risks encountered can be sourced from the information aspect. This study aims to determine the level of the role of information literacy which includes skills to obtain, analyze, and evaluate information, on students' awareness of online risk exposure. In this study, a survey was conducted to 264 undergraduate students at various universities in Indonesia. Data analysis was carried out using the SEM-PLS method with the help of SmartPLS 3.0 software to measure the construct of the hypothetical model. The results show that information literacy has a positive relationship with students' awareness of online risks. The relationship is mediated by the existence of self-control and awareness of information privacy by the individual. Therefore, the relationship means that the higher the level of information literacy, the students will be more aware of the online risks that can occur, especially in online learning.
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