• Journal of Distribution Science
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• v.22 no.2
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• pp.11-20
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• 2024

Purpose: The primary objective of this study is to investigate the impact of website quality on impulse buying of the online retailer, which is mediated by positive emotion and moderated by personalized advertising. Research design, data and methodology: The present study used a survey methodology conducted on many user's smartphones. The sample in this study included 409 college students in Indonesia. Purposive sampling was used as the sampling technique. Data was collected by distributing questionnaires to many respondents through the Google Documents online survey. Results: The findings derived from the application of structural equation modelling for data analysis show that 1). Website quality affects impulse buying and positive emotion, and 2). The impact of website quality on impulse buying was mediated by positive emotion and moderated by personalized advertising. Conclusions: The findings presented in this study has significant theoretical implications that contribute to the existing concept on the relationship between website quality, positive emotion, personalized advertising and impulse buying. The findings of the research possess managerial implications. It can be used can as a reference in determining website quality and the appropriate personalized advertising that increases online impulse buying at online retailer In Indonesia.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.14 no.1
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• pp.139-146
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• 2014

This paper proposes a new personalized mobile advertising service using a smartphone connected with a digital signage which is increasingly common for out-of-home advertising. The advertising contents can be transferred with their metadata to a digital signage. Then, the signage delivers only metadata to smartphones in close proximity of it. Based on the user's preference, an application on a smartphone stores advertising metadata and publishes a personalized advertising e-catalog automatically. A smartphone user can browse, edit and share it with friends. In the view of extension of the reach of the advertising contents of various N-Screen devices including a digital signage and a smart TV to a smartphone and supplying personalized advertising data, this advertising model will be very beneficial and commercialized in the near future.

• Industry Promotion Research
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• v.8 no.4
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• pp.1-15
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• 2023

This study was conducted from May 10th to 30th, 2023 to confirm the relationship between advertisement irritation, privacy concerns, personalized marketing, and social influence of brand customized advertisements on advertisement avoidance and brand loyalty targeting the MZ generation. The following results were verified using the SPSS 28.0 and Smart PLS 4.0 programs for a valid survey of 400 people targeting the MZ generation nationwide on a daily basis. First, advertisement irritation had a positive (+) effect on advertisement avoidance but had no effect on brand loyalty, and personalized marketing had a positive (+) effect on advertisement avoidance but had no effect on brand loyalty. Second, concerns about personal information had a positive (+) effect on avoidance of advertisements and brand loyalty. Third, social influence had a positive (+) effect on advertisement avoidance and brand loyalty. Fourth, advertisement avoidance played a significant mediating role between advertisement irritation and brand avoidance, but did not play a significant mediating role between personalized marketing and social influence. Based on these results, this study is meaningful in that it can be used as basic data for research on advertising avoidance and brand loyalty and for establishing strategies necessary for brand marketing activities.

• Asia pacific journal of information systems
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• v.22 no.4
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• pp.125-149
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• 2012

As the smart phone is propagating rapidly, the importance of mobile advertisement has also grown. One of the main characteristics of the Internet and smart phone advertising is that they can deliver personalized advertisements to each customer. The smart phone enables the identification of additional personalized information such as the customer's location and the accessibility to the site at any place any time. As the Internet platform becomes richer, firms that offer the ad services via the wired PC Internet and wireless smart phone are seeking various types of personalized ads. However, their service platform and Information and Communication Technology (ICT) platform should be suitable to the characteristics of personalized ads. This research explores various types of personalized ad methods and evaluates their adequacy encompassing four types of ad service platforms (such as search portal, news portal, e-mall servers, and SNS) and two types of ICT platforms (PC Internet and smart phone). To this end, we classified the personalized ads into seven types: three basic types and four composite types. The basic types of ad methods are identified by considering the current activity that the customer is engaged, the individual profile and log history, and the customer's current location or planning location. Four composite types of ad methods are constructed as the combination of these basic types. For those types of ad methods, we evaluate whether each ad method adequately maps with four types of ad service platforms and two types of ICT platforms. We proposed a metric of evaluation and demonstrated the concept with illustrative numbers. Specifically, we analyze and compare personalized ad methods in three ways. Firstly, the possibility of implementing a personalized ad method on the platform is analyzed to confirm the degree of suitability. Secondly, the value of personalized ad method is analyzed based on the customer accessibility. Lastly, expected effectiveness for each personalized ad method is computed by multiplying the possibility and the value. Through this kind of analysis, the ad service providers as well as advertising companies can evaluate what kinds of personalized ad methods and platforms are possible and suitable to maximize their ad effectiveness on the Internet and smart phone platforms.

• Journal of the Korea Society of Computer and Information
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• v.20 no.8
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• pp.93-104
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• 2015

In this paper, the design of intelligent_advertisement_operation system(IAdOS) based on user's feedback is proposed for mobile environments. The proposed system stores the advertising contents created by the advertising provider and recommends the personalized advertising contents by analyzing the context information, and then feedback information of the advertisements. Since the proposed system which can recommends provide the smart advertisement contents based on personal preference, it is expected to contribute the new service model development of in the field of advertising market.

• Journal of Information Technology Services
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• v.8 no.4
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• pp.151-163
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• 2009

In this paper, we design and develop a personalized advertisement and information services system based on mobile RFID using RFID virtual tag. It is a system to perform the use of the contents information or the commercial transaction on the contents products through internet server connection by using RFID tag information with a mobile according as transmitting immediately to a cell phone after a tag generator derived RFID tag information to be substituted for the contents information being output at present, after being transmitted from a cell phone the information request signal on the contents information being output from video media. This service system provides a mechanism for gathering advertisement information left behind by many clients visiting advertisement sites for analysis of customers property, service model for selecting personalized services, and mechanism for providing them to customers who visited in a advertisement mall joined to the shopping site.

• Proceedings of the Korea Information Processing Society Conference
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• 2021.11a
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• pp.1160-1163
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• 2021

DOOH(Degital Out of Home) advertisement market is developing steadily, and the case of use is also increasing, In advertisement market, personalized services is actively being provided with technological development. On the other hand, personalized services are difficult to be provided in DOOH and are p rovided by only personal information, not feelings. This study aims to construct personalized DOOH se rvices by using AI facial expression recognition and suggesting a solution optimized for interaction bet ween user and services by providing healing and advertisement.

• Journal of Digital Convergence
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• v.12 no.4
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• pp.183-192
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• 2014

This study aims to empirically investigate how personalized and socialized mobile media impacts on users' acceptance of mobile advertising, given the consideration of users' mobile possession attachment. For this, the current study used focus group interview and surveyed mobile users. Interestingly, the findings reveal that personalized and socialized mobile characteristicssignificantly affect users' acceptance of mobile ads. That is to say, users' personalized mobile characteristics play an important role in either awareness of mobile ads or exposure to mobile ads.

• Journal of Intelligence and Information Systems
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• v.29 no.2
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• pp.323-338
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• 2023

TV advertising with deep analysis of watching pattern of audiences is important to set-top box audience targeting. Applying session-based recommendation model(SBR) to internet commercial, or recommendation based on searching history of user showed its effectiveness in previous studies, but applying SBR to the TV advertising was difficult in South Korea due to data unavailabilities. Also, traditional SBR has limitations for dealing with user preferences, especially in data with user identification information. To tackle with these problems, we first obtain set-top box data from three major broadcasting companies in South Korea(SKB, KT, LGU+) through collaboration with Korea Broadcast Advertising Corporation(KOBACO), and this data contains of watching sequence of 4,847 anonymized users for 6 month respectively. Second, we develop personalized session-based recommendation model to deal with hierarchical data of user-session-item. Experiments conducted on set-top box audience dataset and two other public dataset for validation. In result, our proposed model outperformed baseline model in some criteria.

• Journal of Intelligence and Information Systems
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• v.28 no.4
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• pp.95-117
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• 2022

With the emergence of various media types due to the development of Internet technology, advertisers have difficulty choosing media suitable for corporate advertising strategies. There are challenging to effectively reflect consumer contextual information when advertising media is selected based on traditional marketing strategies. Thus, a recommender system is needed to analyze consumers' past data and provide advertisers with personalized media based on the information consumers needs. Since the traditional recommender system provides recommendation services based on quantitative preference information, there is difficult to reflect various contextual information. This study proposes a methodology that uses deep learning to recommend personalized media to advertisers using consumer contextual information such as consumers' media viewing time, residence area, age, and gender. This study builds a recommender system using media & consumer research data provided by the Korea Broadcasting Advertising Promotion Corporation. Additionally, we evaluate the recommendation performance compared with several benchmark models. As a result of the experiment, we confirmed that the recommendation model reflecting the consumer's contextual information showed higher accuracy than the benchmark model. We expect to contribute to helping advertisers make effective decisions when selecting customized media based on various contextual information of consumers.