• Journal of the Korean Society of Food Culture
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• v.21 no.4
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• pp.375-380
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• 2006

The purpose of this study was to research eating-out information search methods according to college student's lifestyle and their influences on overall satisfaction at fast-food restaurants in eastern province of Kangwondo. Lifestyle was divided into 7 factors and 6 clusters. According to the results, information search methods through Newspaper, magazine and word of mouth were used the most preferably by Cluster 3, 'Brand preference intention'. And TV advertising was used the most preferably by Cluster 4, 'Convenience intention', and the advertisement through internet was used the most preferably by Cluster 5, 'Health ${\cdot}$ effort intention'. However, Information searches through TV advertising and word of mouth had negative influence on the overall satisfaction. But method through internet had positive influences on the overall satisfaction. Eventually, it's proved that information search methods had significant differences according to student's lifestyle. And some information search methods influenced their overall satisfaction. Therefore, food-sonics corporations need to try reducing negative images of various advertisements and activating positive aspects of specialized promotion instruments.

• The Journal of the Korea Contents Association
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• v.5 no.2
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• pp.69-77
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• 2005

This study made a comparison of two different websites in characteristics of their users and advertising effects. Both websites have the same contents but in different forms. Especially this study examined the technographic, demographic and psychographic characteristics of users of an website which offers services only online and another website which offers services both online and offline. Also the advertising effects of both websites were studied. The analysis of the data was done by SPSSWIN, mainly $x^2$ and t-test. In addition, the data was collected online. The website, feelpost.com collected total 432 copies, and cardkorea.com collected 210 copies. Also among those collected copies, the ones from people in the 20's were selected again in order to rule out the special characters that both websites have in their users age group. Finally 308 copies were selected for the analysis. In result, it was proved that the users of both websites have a very similar lifestyle. Also there was only a little difference in the users' values and social consciousness. Regarding the advertising effect, Feelpost got the highest score in usefulness while Cardkorea got the highest score in positive acceptance of new products. Regarding the attitude toward advertisements and products, the advertising preference and brand preference was higher in Feelpost than in Cardkorea.

• The Journal of the Korea Contents Association
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• v.21 no.9
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• pp.149-163
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• 2021

The 4th industrial revolution refers to the next-generation industrial revolution led by information and communication technologies such as artificial intelligence (AI), Internet of Things (IoT), robot technology, drones, autonomous driving and virtual reality (VR) and it also has made a significant impact on the development of the advertising industry. However, the world is rapidly changing to a non-contact, non-face-to-face living environment to prevent the spread of COVID 19. Accordingly, the role of the 4th industrial revolution and advertising is changing. Therefore, in this study, text analysis was performed using Big Kinds to examine the 4th industrial revolution and changes in advertising before and after COVID 19. Comparisons were made between 2019 before COVID 19 and 2020 after COVID 19. Main topics and documents were classified through LDA topic model analysis and Word2vec, a deep learning technique. As the result of the study showed that before COVID 19, policies, contents, AI, etc. appeared, but after COVID 19, the field gradually expanded to finance, advertising, and delivery services utilizing data. Further, education appeared as an important issue. In addition, if the use of advertising related to the 4th industrial revolution technology was mainstream before COVID 19, keywords such as participation, cooperation, and daily necessities, were more actively used for education on advanced technology, while talent cultivation appeared prominently. Thus, these research results are meaningful in suggesting a multifaceted strategy that can be applied theoretically and practically, while suggesting the future direction of advertising in the 4th industrial revolution after COVID 19.

• Science of Emotion and Sensibility
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• v.17 no.2
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• pp.13-24
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• 2014

Mobile phone makers compete for market shares through domination in media advertisements. These include domination of advertisements (Ads) in TV and the internet. However, the abundance and complexity of the competitions of Ads in TV does not guarantee advertising success which can influence consumers' emotion and the purchase intention towards the brand. This research analyses the case of a directional model on Attitude-towards-the-Ad model as a baseline into a new proposed correlation models (MacKenzie, Scott, &Lutz, 1989). The survey targets the involvements of Asian smartphone owners' attitude on advertisements, brands and purchase intentions. CFA (Confirmatory factor Analysis) was used in the research experiments, including hypothesis testing, the outcome of model fit which revealed significant levels and were successful. The study revealed that all three paths have consistently high coefficient paths (Attitude to Ads - Attitude to Brands - Purchase Intention), showing significant value of (${\beta}$=>.80), which supported each correlation factors. Therefore, this structural model, could set standards for creative managers and advertising teams to improve the brands visibility and build strong influences on attitudes in advertisements and improve purchase intentions.

• Journal of Information Processing Systems
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• v.18 no.2
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• pp.245-257
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• 2022

In the Internet of Things (IoT) era, the types of devices used by one user are becoming more diverse and the number of devices is also increasing. However, a forensic investigator is restricted to exploit or collect all the user's devices; there are legal issues (e.g., privacy, jurisdiction) and technical issues (e.g., computing resources, the increase in storage capacity). Therefore, in the digital forensics field, it has been a challenge to acquire information that remains on the devices that could not be collected, by analyzing the seized devices. In this study, we focus on the fact that multiple devices share data through account synchronization of the online platform. We propose a novel way of identifying the user's interest through analyzing the remnants of targeted advertising which is provided based on the visited websites or search terms of logged-in users. We introduce a detailed methodology to pick out the targeted advertising from cache data and infer the user's interest using deep learning. In this process, an improved learning model considering the unique characteristics of advertisement is implemented. The experimental result demonstrates that the proposed method can effectively identify the user interest even though only one device is examined.

• International Journal of Computer Science & Network Security
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• v.21 no.7
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• pp.305-316
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• 2021

The objective is to recognize the better opportunities from targeted reveal advertising, to show a banner ad to the consumer of online who is most expected to obtain a preferred action like signing up for a newsletter or buying a product. Discovering the most excellent commercial impression, it means the chance to exhibit an advertisement to a consumer needs the capability to calculate the probability that the consumer who perceives the advertisement on the users browser will acquire an accomplishment, that is the consumer will convert. On the other hand, conversion possibility assessment is a demanding process since there is tremendous data growth across different information dimensions and the adaptation event occurs infrequently. Retailers and manufacturers extensively employ the retail services from internet as part of a multichannel distribution and promotion strategy. The rate at which web site visitors transfer to consumers is low for online retail, out coming in high customer acquisition expenses. Approximately 96 percent of web site users concluded exclusive of no shopper purchase[1].This category of conversion rate is collected from the advertising of social media sites and pages that dataset must be estimating and assessing with the concept of big data clustering, which is used to group the particular age group of people along with their behavior. This makes to identify the proper consumer of the production which leads to improve the profitability of the concern.

• International journal of advanced smart convergence
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• v.12 no.3
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• pp.175-185
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• 2023

As the era of ChatGPT and generative AI technologies unfolds, the marketing industry stands on the precipice of a paradigm shift. Innovations such as GPT-4, DALL-E 2, and Mid-journey Stable Diffusion possess the capacity to dramatically transform the methods by which advertisers reach and engage with customers. The potential applications of these advanced tools herald a new age for the marketing and advertising sectors, offering unprecedented opportunities for growth and optimization. Nevertheless, the rapid adoption of generative AI within these industries presents a unique set of challenges, particularly for organizations that lack the necessary technological infrastructure and human capital to effectively leverage these innovations. As a result, a competitive crisis may emerge, exacerbating existing disparities between well-equipped enterprises and their less technologically adept counterparts. In this article, we undertake a comprehensive exploration of the implications of generative AI for the future of marketing, examining both its potential benefits and drawbacks. We consider the possible impact of these developments on the advertising and marketing industries at large, as well as the ways in which professionals operating within these fields may need to adapt to remain competitive in an increasingly AI-driven landscape. By providing a holistic overview of the challenges and opportunities associated with generative AI, this study aims to elucidate the complex dynamics at play in the ongoing evolution of the marketing and advertising sectors.

• Journal of Intelligence and Information Systems
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• v.23 no.4
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• pp.1-31
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• 2017

Modern businesses are adopting new technologies to serve their markets better as well as to improve efficiency and productivity. The advertising industry has continuously experienced disruptions from the traditional channels (radio, television and print media) to new complex ones including internet, social media and mobile-based advertising. This case study focuses on proposing intelligent advertising business model in Seoul's metro network. Seoul has one of the world's busiest metro network and transports a huge number of travelers on a daily basis. The high number of travelers coupled with a well-planned metro network creates a platform where marketers can initiate engagement and interact with both customers and potential customers. In the current advertising model, advertising is on illuminated and framed posters in the stations and in-car, non-illuminated posters, and digital screens that show scheduled arrivals and departures of metros. Some stations have digital screens that show adverts but they do not have location capability. Most of the current advertising media have one key limitation: space. For posters whether illuminated or not, one space can host only one advert at a time. Empirical literatures show that there is room for improving this advertising model and eliminate the space limitation by replacing the poster adverts with digital advertising platform. This new model will not only be digital, but will also provide intelligent advertising platform that is driven by data. The digital platform will incorporate location sensing, e-commerce, and mobile platform to create new value to all stakeholders. Travel cards used in the metro will be registered and the card scanners will have a capability to capture traveler's data when travelers tap their cards. This data once analyzed will make it possible to identify different customer groups. Advertisers and marketers will then be able to target specific customer groups, customize adverts based on the targeted consumer group, and offer a wide variety of advertising formats. Format includes video, cinemagraphs, moving pictures, and animation. Different advert formats create different emotions in the customer's mind and the goal should be to use format or combination of formats that arouse the expected emotion and lead to an engagement. Combination of different formats will be more effective and this can only work in a digital platform. Adverts will be location based, ensuring that adverts will show more frequently when the metro is near the premises of an advertiser. The advertising platform will automatically detect the next station and screens inside the metro will prioritize adverts in the station where the metro will be stopping. In the mobile platform, customers who opt to receive notifications will receive them when they approach the business premises of advertiser. The mobile platform will have indoor navigation for the underground shopping malls that will allow customers to search for facilities within the mall, products they may want to buy as well as deals going on in the underground mall. To create an end-to-end solution, the mobile solution will have a capability to allow customers purchase products through their phones, get coupons for deals, and review products and shops where they have bought a product. The indoor navigation will host intelligent mobile-based advertisement and a recommendation system. The indoor navigation will have adverts such that when a customer is searching for information, the recommendation system shows adverts that are near the place traveler is searching or in the direction that the traveler is moving. These adverts will be linked to the e-commerce platform such that if a customer clicks on an advert, it leads them to the product description page. The whole system will have multi-language as well as text-to-speech capability such that both locals and tourists have no language barrier. The implications of implementing this model are varied including support for small and medium businesses operating in the underground malls, improved customer experience, new job opportunities, additional revenue to business model operator, and flexibility in advertising. The new value created will benefit all the stakeholders.

• International Journal of Advanced Culture Technology
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• v.8 no.1
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• pp.120-127
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• 2020

The use of digital signage in the public and commercial communication areas has been increasing in recent years. By integrating cutting-edge information technologies such as 5G, artificial intelligence, and the Internet of Things, digital signage continues to break apart from traditional outdoor advertising media. This study identified the problems facing the domestic digital signage industry by exploring and analyzing major issues related to digital signage and derived future development measures. Specifically, online documents were collected based on the digital signage-related keywords created over the past 12 years to conduct big data network analysis, and key topics were derived through visualization of the results. This study has great policy implications in that it excluded biased interpretations based on the viewpoints of companies or the government and, more objectively, suggested the direction of the digital signage industry's development in the domestic media market.

• International journal of advanced smart convergence
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• v.13 no.2
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• pp.110-118
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• 2024

This study examines factors influencing nonusers' resistance to the adoption of the metaverse, focusing on propagation mechanisms. It elucidates the role of innovation resistance within the metaverse adoption process. We applied the Innovation Resistance Model in the context of the metaverse and considers three major groups of factors influencing resistance to the metaverse: innovation characteristics (perceived usefulness, compatibility, perceived risk, and complexity), consumer characteristics (personal innovativeness), and propagation mechanisms (mass media, online media, and personal communication). An online survey of college students who do not use the metaverse revealed that perceived usefulness, compatibility, personal innovativeness, and online media were negative predictors of resistance to the metaverse. Conversely, perceived risk, mass media, and personal communication were positive predictors of resistance to the metaverse. Furthermore, innovation resistance was found to play a mediating role in the metaverse adoption process. Drawing upon the findings, we suggested marketing strategies to decrease resistance to the metaverse.