ABSTRACT
Nowadays, the number of smartphone users shopping online over the internet is increasing due to the COVID-19 pandemic situation. People need to stay safe at home and work from home according to the social distancing policy. It is difficult for people to go shopping onsite at a physical store. Especially, cosmetic consumers cannot try on cosmetic products, and they are not sure which product is suitable for them. Therefore, to solve these problems, this research project proposes 'Beauty Face', which is an android application for cosmetic consumers who would like to try on products and receive recommendations. The Beauty Face application allows users to find the desired products and view product information. Also, it provides a useful feature for users to try on products by applying augmented reality (AR) technology to simulate cosmetic and beauty products on the user's face. Moreover, the Beauty Face application can recommend products that are appropriate for users by applying machine learning (ML) technology. The Beauty Face application can be helpful for cosmetic users to be more convenient in buying cosmetic and beauty products online and reducing chances of being infected or spreading COVID-19. © 2022 IEEE.
ABSTRACT
E-commerce shows steady growth in the marketplace since it makes the lives of people easier. Today's generation is more inclined toward convenience in purchasing goods. The COVID-19 shut down many food establishments across the Philippines, resulting in an online bakeries boom. Pastries are one of the most sought goods online, especially with the pandemic surge where physical stores are seldomly open. E-commerce with a recommender system is the trend that helps customers choose products, which helps in decision-making on what to purchase. On the other hand, a mobile application counterpart could increase brand recognition and customer engagement as it is now the most effective, direct, and personalized way to deliver product information. In this study, the descriptive research method was used, with a questionnaire using the functionality, usability, reliability, performance and supportability (FURPS) serving as the instrument for testing the acceptability. The overall quality of the system was given an acceptable rating with a weighted mean of 4.07, indicating that the system's functions were well integrated, that navigation was simple, performed consistently, and that the system was accessible regardless of device. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
ABSTRACT
After the COVID-19 pandemic influenced the global market, people around the world reduced their visits to physical stores, however opted to make purchases online instead. By providing a platform for their products to be heard during the crisis, the public was able to express their opinion through social media.The purpose of this study is to improve the understanding of "digital marketing" and to examine the effects and factors that influence the use of social media (digital marketing), publication-related journals on online marketing on brands and consumers in the study of digital marketing.The study collected data using the Web of Science (WoS) SSCI database from January 2016 to June 2022 on the topic "Digital Marketing", where 4,295 articles containing quantitative analysis of the relevant literature on Digital Marketing (DM) to find overall trends and predictions were adopted. Six different categories of DM articles were used to classify and investigate the different distribution states in order to find the relevant research developments and division states between 2016 and 2022. Research gaps and DMs are analyzed and synthesized, and a framework for future directions is proposed.This study presents the relevance of digital marketing journal capabilities to the advertising business, research trends and future information in organizing digital marketing (DM), marketing-related research and identifying the core of DM-related research, key aspects of measuring business performance. The proposed dimension of the Digital Marketing Capability Framework is to identify new research directions in the marketing and advertising chain. Systematic evaluation of the relevant literature is categorized at the company level. Key measures of the relevance of digital marketing capabilities to companies (B2C and B2B) and business performance are presented. © 2022 International Consortium for Electronic Business. All rights reserved.
ABSTRACT
The outbreak of COVID-19 since the end of 2019 has led many people to work for home, reducing economic activity in many countries except online shopping, which is thriving during the pandemic. However, shopping is not take-and-go activity,as it needs references to help make the decision. Buying goods online is not as convenient as buying at physical stores where the customers can check the actual state of goods, obtain recommendations from the clerks or compare it with other similar goods. All these physical activities are persuasions. However, the main references for buying online are online third-party comments and brand image. People noticed the comments online, whether positive or negative about the product. Consumers write comments on the Internet according to their different impressions on the brands. Therefore, how the brand image and online comments affect persuasion is worthy of study. This pilot study thus takes the purchase of mobile phones as an example to explore the factors of people's evaluation of comments and brand image. The analytical results of exploratory factor analysis show that the questionnaire design is suitable. The formal study can take these research results as a reference. © 2021 ACM.
ABSTRACT
The recent Covid-19 pandemic has changed many aspects of people's life. One of the principal preoccupations regards how easily the virus spreads through infected items. Of special concern are physical stores, where the same items can be touched by a lot of people throughout the day. In this paper a system to efficiently detect the human interaction with clothes in clothing stores is presented. The system recognizes the elements that have been touched, allowing a selective sanitization of potentially infected items. In this work two approaches are presented and compared: the pixel approach and the bounding box approach. The former has better detection performances while the latter is slightly more efficient. Copyright for this paper by its authors. Use permitted under Creative.