• The Journal of the Korea Contents Association
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• v.21 no.1
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• pp.426-433
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• 2021

Investment in public sector information services has been on the rise in recent years. The supply of high-speed Internet and smartphones has become more common, and the stability of the information system provided to the public in the public sector has become an important management factor. In other words, tasks such as handling civil complaints and issuing certificates by public institutions, financial transactions by banks, customs clearance work, and e-commerce by individuals or institutions are mostly done online. Therefore, how to deal with obstacles arising from the information system, which is in charge of important civil service affairs, is becoming a very important issue. In other words, in the case of a disability that does not function normally even for a short period of time, various problems can occur when the work is delayed, as well as causing serious financial damage to the civil petitioner. This could be accompanied by a decline in public confidence and various other damages such as filing civil complaints. The reasons for the occurrence of information system failures are very diverse and realistically difficult to predict when. Among the various measures to cope with disability, this paper proposed a plan to establish a disability situation notification system that can minimize confusion caused by disability in the event of a homepage malfunction. The proposed disability situation notification system was established in the public IDC environment to show the possibility of utilization.

• Journal of Digital Convergence
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• v.19 no.5
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• pp.135-144
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• 2021

In Korea, the parcel delivery service is showing a high growth rate every year thanks to the activation of e-commerce, but the courier unit price continues to drop. Due to the low cost of parcel delivery, there is a need for improvement to normalize courier rates due to deterioration in profitability for couriers, deterioration in service for consumers, and overwork and accidents for workers. In this study, a rational rate system model and a systematic approach were presented. The study method modeled the chargeable weight by reflecting the voulumatirc weight and revenue ton by the volume and weight of the cargo, and presented a new parcel freight charge model based on the cost of delivery. In addition, a rate-determining support system was developed that can be easily, conveniently and reasonably determined on-site. In the demonstration, the rate difference was determined by relying on weight rather than volume, and 63.5% for personal courier and 40% for B2C courier were found to be inadequate. This study could be used as an alternative to solving side effects and problems at the delivery site, in the urgent need for research on ways to improve delivery prices.

• Journal of Digital Convergence
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• v.19 no.8
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• pp.319-325
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• 2021

With the advancement of wireless technology and the rapid growth of the infrastructure of mobile communication technology, systems applying AI-based platforms are drawing attention from users. In particular, the system that understands users' tastes and interests and recommends preferred items is applied to advanced e-commerce customized services and smart homes. However, there is a problem that these recommendation systems are difficult to reflect in real time the preferences of various users for tastes and interests. In this research, we propose a Fuzzy-AHP-based movies recommendation system using the Gated Recurrent Unit (GRU) language model to address a problem. In this system, we apply Fuzzy-AHP to reflect users' tastes or interests in real time. We also apply GRU language model-based models to analyze the public interest and the content of the film to recommend movies similar to the user's preferred factors. To validate the performance of this recommendation system, we measured the suitability of the learning model using scraping data used in the learning module, and measured the rate of learning performance by comparing the Long Short-Term Memory (LSTM) language model with the learning time per epoch. The results show that the average cross-validation index of the learning model in this work is suitable at 94.8% and that the learning performance rate outperforms the LSTM language model.

• Journal of Korea Entertainment Industry Association
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• v.14 no.3
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• pp.1-13
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• 2020

Tencent is an internet-based entertainment platform corporation using technology to enrich the lives of Tencent platform users and assist the contents expansion. Since 2000, Tencent have developed a great growth and innovation in entertainment contents domain. Tencent have become the market leading innovator due to the imitative innovation and M&A. The present study designed case study analyses to investigate the mechanism with regard to the growth strategy of Tencent corporation. Tencent began with imitative internet-based game and social messaging services but then added its own wechat messenger platform, now being extended to other products or services. This imitative innovation strategy enabled Tencent corporation to grow rapidly, to achieve outstanding growth. In addition, Tencent's M&A investment drive is underpinned by a vision of top management team and flexible organizational culture, from building out the Tencent's entertainment platform, game, finance, e-commerce, to global market expansion. While our results shed light on the implications to understanding Tencent's growth, there are limitations of the current study that should be considered when designing next research.

• The Korean Journal of Franchise Management
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• v.13 no.2
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• pp.33-51
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• 2022

Purpose: The online market is growing the most in history due to the expansion of non-face-to-face commerce. In addition, as consumers' interest in health, food safety, and environment increases, interest in and consumption of eco-friendly agricultural products is also increasing. Therefore, in the case of a specialty store that sells eco-friendly organic agricultural products, a marketing strategy that can increase customer loyalty by reflecting these consumer needs is necessary. In this study, the store attributes of eco-friendly food stores are classified into location, assortment, price, quality, and employee service, and the effect of each store attribute on utilitarian and hedonic value is investigated. Research design, data, and methodology: The subjects of this study were customers who visited an eco-friendly food store. Of the 511 survey responses, 311 were used for statistical verification, excluding 200 who had not visited within the last 3 months. For statistical analysis, Smart PLS 3.0 was used, and after checking the validity and reliability of the items, hypothesis testing was performed. Result: As a result of the study, it was found that assortment, quality, and employee service among store attributes had a positive (+) effect on utilitarian and hedonic value. Second, location had no significant effect on utilitarian and hedonic value. Third, price did not appear to have a positive (+) effect on the utilitarian value, and it was found to have a positive (+) effect on the hedonic value. Fourth, It was investigated whether the presence or absence of delivery service had an effect on store attributes between utilitarian and hedonic value, and it was found that there was a significant effect between employee service and hedonic value. Conclusions: Among eco-friendly food store environment management will be required in order to provide food that meets the tastes and needs of consumers by diversifying the taste, standard, and quality grade of food, and to maintain or improve the quality. In order to unlike other stores, eco-friendly food stores have high price resistance from the point of view of consumers, so it is necessary to diversify promotional media such as YouTube and SNS to raise awareness of eco-friendly organic food.

• Journal of Intelligence and Information Systems
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• v.28 no.2
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• pp.171-189
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• 2022

Online reviews play an essential role in the consumer's purchasing decision-making process, and thus, providing helpful and reliable reviews is essential to consumers. Previous online review helpfulness prediction studies mainly predicted review helpfulness based on the consistency of text and rating information of online reviews. However, there is a limitation in that representation capacity or review text and rating interaction. We propose a CNN-RHP model that effectively learns the interaction between review text and rating information to improve the limitations of previous studies. Multi-channel CNNs were applied to extract the semantic representation of the review text. We also converted rating into independent high-dimensional embedding vectors representing the same dimension as the text vector. The consistency between the review text and the rating information is learned based on element-wise operations between the review text and the star rating vector. To evaluate the performance of the proposed CNN-RHP model in this study, we used online reviews collected from Amazom.com. Experimental results show that the CNN-RHP model indicates excellent performance compared to several benchmark models. The results of this study can provide practical implications when providing services related to review helpfulness on online e-commerce platforms.

• Knowledge Management Research
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• v.23 no.2
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• pp.253-276
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• 2022

Online reviews attract much attention because they play an essential role in consumer decision-making. Therefore, it is necessary to investigate the review attributes that affect the perceived helpfulness of consumers. However, most previous studies on the helpfulness of online reviews mainly focus on quantitative factors such as review volume and reviewer attributes. Recently, some studies have investigated the impact of review content and linguistic style matching on consumers' purchase decision-making. Those studies show that consumers consider additional review attributes when evaluating reviews in decision-making. To fill the research gap with existing literature, we investigated the impact of review content and linguistic style matching on review helpfulness. Moreover, this study investigated how the reviewers' expertise moderates the effect of the review content and linguistic style matching on the review helpfulness. The empirical results show that positive affective content has a negative effect on the review helpfulness. The negative affective content and linguistic style matching positively affect review helpfulness. Review expertise relieved the impact of negative affective content and linguistic style matching on review helpfulness. According to the mechanism confirmed in this study, online e-commerce companies can achieve corporate sales growth by identifying factors affecting review helpfulness and reflecting them in their marketing strategies.

• Journal of Intelligence and Information Systems
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• v.29 no.1
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• pp.41-63
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• 2023

As the online e-commerce market growing, the need for a recommender system that can provide suitable products or services to customer is emerging. Recently, many studies using the sentiment score of online review have been proposed to improve the limitations of study on recommender systems that utilize only quantitative information. However, this methodology has limitation in extracting specific preference information related to customer within online reviews, making it difficult to improve recommendation performance. To address the limitation of previous studies, this study proposes a novel recommendation methodology that applies deep learning technique and uses various linguistic factors within online reviews to elaborately learn customer preferences. First, the interaction was learned nonlinearly using deep learning technique for the purpose to extract complex interactions between customer and product. And to effectively utilize online review, cognitive contents, affective contents, and linguistic style matching that have an important influence on customer's purchasing decisions among linguistic factors were used. To verify the proposed methodology, an experiment was conducted using online review data in Amazon.com, and the experimental results confirmed the superiority of the proposed model. This study contributed to the theoretical and methodological aspects of recommender system study by proposing a methodology that effectively utilizes characteristics of customer's preferences in online reviews.

• Journal of Practical Agriculture & Fisheries Research
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• v.12 no.1
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• pp.137-150
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• 2010

Traditionally, like many people in mountain region of the Himalaya, the Lwang communities depend on mix of subsistence agriculture, animal husbandry, and seasonal migrant labor for their livelihoods. These traditional systems are characterized by low productivity, diverse use of available natural resources (largely for home consumption), limited markets, and some aversion for innovation. The potential to generate wealth through commerce has largely been untapped by these mountain residents and thus is undervalued in local and national economies. Introduction of organic tea farming is a part of Lwang community's several initiatives to break the vicious poverty cycle Annapurna Conservation Area Project (ACAP) played facilitating roles in all their efforts since beginning. In five years, the tea plantation emerged as a new means for secured a livelihood. This study aims to analyze the current practices in tea farming both in terms of farm management and soil nutrient status(technical) and the prosperity of the tea farmers (social). The technical aspect covers the soil and tea leaf analysis of various nutrients contents in the soil and tea leaf. Originally, the technical aspect of the study was not planned but later during the consultation with the advisor it was taken into consideration which added value to the research study. The sample were collected from different locations and analyzed on the field itself. The other part of the study i.e. the social aspect was done through questionnaire survey and focus group discussion. the tea farming provided them not only a new opportunity but also earned an identity in the region. This initiative was undertaken as a piloting measure. Now that the tea is in production with processing unit established locally, more serious consideration has to be given for better yield and economic prosperity. This research finding will help the community to analyze their efforts and make correction measures in tea garden management and application of fertilizer. It is also expected to fill up the gaps of knowledge and information required to reduce economic stresses and enhance capacity of farmers to make the tea farming a sustainable and beneficial business. The findings are expected to Sustainability of organic tea farming has direct impacts on biodiversity conservation compared to the other traditional farming practices that are more resource intensive. The study will also contribute to identify key action points required for reducing poverty while conserving environment and enhancing livelihoods

• Journal of Service Research and Studies
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• v.13 no.1
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• pp.127-143
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• 2023

Currently, the domestic traditional market has not escaped the swamp of stagnation that began in the early 2000s despite various projects promoted by many related players such as the central government and local governments. In order to overcome the crisis faced by the traditional market, various R&Ds have recently been conducted on how to build a smart traditional market that combines information and communication technologies such as big data analysis, artificial intelligence, and the Internet of Things. This study analyzes various previous studies, users of traditional markets, and application cases of ICT technology in foreign traditional markets since 2012 and proposes a model to build a smart traditional market using ICT technology based on the analysis. The model proposed in this study includes building a traditional market metaverse that can interact with visitors, certifying visits to traditional markets through digital signage with NFC technology, improving accuracy of fire detection functions using IoT and AI technology, developing smartphone apps for market launch information and event notification, and an e-commerce system. If a smart traditional market platform is implemented and operated based on the smart traditional market platform model presented in this study, it will not only draw interest in the traditional market to MZ generation and foreigners, but also contribute to revitalizing the traditional market in the future.