• International Journal of Internet, Broadcasting and Communication
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• 제9권3호
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• pp.59-69
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• 2017

The best 'hub' to communicate with the citizen is using social media to marketing the business. However, there has several issued and the most common issue that face in critical is a capital issue. This issue is always highlight because most of automatic sentiment detection tool for Facebook or any other social media price is expensive and they lack of technical skills in order to control the tool. Therefore, in directly they have some obstacle to get faster product's feedback from customers. Thus, the personal online retailing need to struggle to stay in market because they need to compete with successful online company such as G-market. Sentiment analysis also known as opinion mining. Aim of this research is develop the tool that allow user to automatic detect the sentiment comment on social media account. RAD model methodology is chosen since its have several phases could produce more activities and output. Soppy tool will be develop using Microsoft Visual. In order to generate an accurate sentiment detection, the functionality testing will be use to find the effectiveness of this Soppy tool. This proposed automated Soppy Tool would be able to provide a platform to measure the impact of the customer sentiment over the postings on their social media site. The results and findings from the impact measurement could then be use as a recommendation in the developing or reviewing to enhance the capability and the profit to their personal online retailing company.

• 유통과학연구
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• 제13권5호
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• pp.15-22
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• 2015

Purpose - Transparency, seller reputation, and website security are considered to be important factors that influence online customer purchasing decisions in China. This paper empirically examines the relative influence of Taobao.com on customers' online purchasing decisions. Research design, data, and methodology - We perform structural equation analysis, with a sample of 306 observations. The data comes from consumers' real transaction experiences from a specific website. This gives the results of our study more generalizability than studies using subjects who are not asked to engage in real transactions. Results - The results of this study reveal that perceived security and perceived reputation are critical factors affecting consumer trust and perceived transparency is most closely associated with purchase intention. Conclusions - The findings suggest that perceived transparency plays a significant role in increasing online consumer's purchase intention. The knowledge of the relative impacts of these factors and their roles in the customer transaction experience will be useful in developing customized sales strategies. The results of this study reveal that perceived transparency exerts a stronger effect than perceived reputation on consumer purchase intentions.

• 한국의류학회지
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• 제35권9호
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• pp.1099-1111
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• 2011

This study identified the types of consumer review information about apparel products based on consumer satisfaction/dissatisfaction with the availability/non-availability of consumer review information for online stores. Data were collected from 318 females aged 20s' to 30s', who had significant experience in reading consumer reviews posted on online stores. Consumer satisfaction/dissatisfaction with availability or non-availability of review information on online stores is different for information in regards to apparel product attributes, product benefits, and store attributes. According to the concept of quality elements suggested by the Kano model, two types of consumer review information were determined: Must-have information (product attribute information about size, fabric, color and design of the apparel product; benefit information about washing & care and comport of the apparel product; store attribute information about responsiveness, disclosure, delivery and after service of the store) and attracting information (attribute information about price comparison; benefit information about coordination with other items, fashionability, price discounts, value for price, reaction from others, emotion experienced during transaction, symbolic features for status, health functionality, and eco-friendly feature; store attribute information about return/refund, damage compensation and reputation/credibility of online store and interactive and dynamic nature of reviews among customers). There were significant differences between the high and low involvement groups in their perceptions of consumer review information.

• Fashion, Industry and Education
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• 제15권2호
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• pp.1-10
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• 2017

The purposes of this study were to explore (1) how fit reviews differ among height groups and (2) how overall numerical ratings differ depending on height groups and ifferent types of fit reviews. Content analysis was used to analyze systematically sampled online consumer reviews (OCRs) of formalwear dresses rented online. In part 1, 201 OCRs were analyzed to develop the coding scheme, which included three aspects of fit (physical, aesthetic, and functional), valence (negative, neutral, positive), and overall numerical rating. In part 2, 600 OCRs were coded and statistically analyzed. Differences in frequency were not found among height groups for any types of mentions (negative, neutral, and positive) in terms of the three aspects of fit in the OCRs. Differences in overall mean ratings were not found among height groups. Interestingly, valence of each aspect of fit reviews affected mean numeric ratings. This study is new in examining relationships among textual information (i.e., fit reviews), numerical information (i.e., numerical rating), and reviewer's characteristic (i.e., height). The results of this study offered practical implications for etailers and marketers that they should pay attention to the three aspects of fit reviews and monitor garments with negative fit evaluations for lower ratings. They may attempt to increase ratings by providing customers recommendations to get a better fit.

• 트랜스-
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• 제10권
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• pp.15-29
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• 2021

코로나 팬데믹 이후, 전염병의 창궐 속에서 개인의 건강과 안녕을 위한 수단으로 '언택트 경제' 비대면 경제활동이 주요 이슈가 되면서, 쿠팡, 마켓컬리 같은 온라인 마켓이 생필품을 구매하기 위한 주요 수단으로 부상했다. 이처럼 코로나가 야기한 집합과 국가간 이동제한은 사회 전반적인 활동에 지대한 영향을 미쳤으며 사람들의 행동 방식과 소비습관, 나아가서는 라이프 스타일에까지 큰 변화를 불러왔다. 미술시장 역시 많은 변화를 맞이했다. 집합의 제한, 국가간 이동의 제한 상황 발생은 미술시장 규모에 일차적으로 타격을 입혔으며 나아가 작품이 거래되는 방식, 거래되는 작품의 특성, 작품을 구매하는 사람에게 까지 영향을 미치고 있다. 본 논문에서는 코로나가 미술시장에 미친 영향을 온라인 미술시장 중심으로 살펴보고, 앞으로 야기할 변화와 대응방식을 모색해보고자 한다.

• 한국의류산업학회지
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• 제24권2호
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• pp.183-194
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• 2022

This study aims to understand the consumers' negative responses to communication failure of chatbots caused by their imperfections. Specifically, this study examines 1) the relationship among chatbot's communication failure, dissatisfaction, negative behavior (complaint, negative word-of-mouth (nWOM), and inertia); 2) the moderating effect of technostress on the relationship between chatbot's communication failure and dissatisfaction; 3) the differences in the negative responses between the generation MZ and the previous generations. Data were collected via an online survey. First, the participants interacted with the chatbot developed for this survey, to experience the chatbot's communication failure. Thereafter, they responded to a questionnaire. PLS-SEM was conducted using the R software environment to test the hypotheses. This study empirically identified that chatbot's communication failure positively affected dissatisfaction. In addition, the customers who were more dissatisfied with the chatbot's communication failures were more likely to complain than engage in nWOM. Compared to the generation MZ, chatbot's communication failure caused a higher level of dissatisfaction in previous generations. The results suggest that online shopping malls should carefully introduce an improved chatbot service after minimizing its communication failure rate. The chatbot developers of online shopping malls targeting middle-aged and elderly consumers should strive to develop and implement strategies to further alleviate consumers' dissatisfaction in the situation of chatbot's communication failure.

• 한국정보시스템학회지:정보시스템연구
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• 제31권4호
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• pp.161-187
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• 2022

Purpose This study analyzed the topic of game review contents and how the characteristics of game reviews affect the reviews helpfulness. In addition, this study explore the content of game reviews according to the game's sales strategy such as early access strategy and releasing without early access. Design/methodology/approach We collected a list of 3,572 action genre games released in 2020. 58,336 online reviews were collected by random sampling 50 reviews in each games, and topic modeling was performed on those reviews. We dynamized the results of topic modeling and analyzed the effect on review helpfulness with multiple regression analysis. Findings The results of analysis indicate that the longer the review is or the shorter the time it is written, the more helpful the review is. In addition the topic with positive and negative review has a significant effect on the review helpfulness. As a result of exploratory analysis, games from early access had relatively fewer reviews of story-related topics than games that were released without early access. These findings can present direct guidelines for collecting specific opinions from customers in the game industry when releasing games.

• Human Ecology Research
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• 제62권1호
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• pp.1-13
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• 2024

This study analyzed the current operational status, business continuity, and business continuity strategies of 11 Soho fashion shopping malls through a longitudinal case study (2019/2020 and 2022/2023). The aim was to determine how Soho fashion shopping malls are continuing their business having been successfully established in the fiercely competitive current online fashion market. Regarding changes in shopping mall operation status, all cases displayed changes in items, distribution channels, marketing channels, core values, and profit structures. After establishing the businesses, a crisis arose due to the COVID-19 pandemic, leading to difficulties in creating new customers. Moreover, there was excessive business expansion, resulting in saturation of the online platform store market. This meant companies were experiencing reduced sales (5) or difficulties in maintaining their business (3). However, there were differences in the direction of overcoming the crisis and continuing or converting the business. These revealed that to continue the business after successful establishment of an online fashion shopping mall, it is essential to have the expertise of entrepreneurs, work performance, and marketing ability, as well as differentiation capabilities such as product power and management strategy and core competitiveness that provides a relative advantage over other shopping malls. Customized government support at the level of the start-up ecosystem is also essential for the survival and business continuity of a SOHO online fashion shopping mall with poor human and material resources.

• Asia pacific journal of information systems
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• 제31권4호
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• pp.472-490
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• 2021

The detection of products with manipulated reviews has received widespread research attention, given that a truthful, informative, and useful review helps to significantly lower the search effort and cost for potential customers. This study proposes a method to recognize products with manipulated online customer reviews by examining the sequence of each review's sentiment, readability, and rating scores by product on randomness, considering the example of a Russian online retail site. Additionally, this study aims to examine the association between brand awareness and existing manipulation with products' reviews. Therefore, we investigated the difference between well-known and unknown brands' products online reviews with and without manipulated reviews based on the average star rating and the extremely positive sentiment scores. Consequently, machine learning techniques for predicting products are tested with manipulated reviews to determine a more useful one. It was found that about 20% of all product reviews are manipulated. Among the products with manipulated reviews, 44% are products of well-known brands, and 56% from unknown brands, with the highest prediction performance on deep neural network.

• 한국컴퓨터정보학회논문지
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• 제25권9호
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• pp.53-62
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• 2020

최근 연구된 상품 추천 서비스들은 고객들의 구매 이력을 통해서만 추천이 이루어졌다. 본 논문에서는 구매 이력을 통해 추천뿐만 아니라 고객이 상품을 고를 때 취하는 행동 패턴을 분석하여 관심도가 높은 광고를 노출하는 행동 패턴 분석 기반 디지털 사이니지 서비스를 제안한다. 이 서비스는 고객행동 패턴을 분석하여 실질적으로 관심을 가지는 상품에 대해 관심도를 추출한다. 추출된 관심도와 고객들의 구매 이력을 Wide & Deep 모델을 통해 학습하고, 이를 바탕으로 MF(Matrix Factorization) 모델을 통해 다른 상품들의 희소 벡터를 예측한다. 예측된 상품 관심도에 대한 순위를 도출하고, 적합한 광고를 노출하기 위해 고객과 상호 작용할 수 있는 인도어 사이니지를 활용한다. 본 논문의 서비스를 통해 온라인뿐만이 아닌 오프라인 환경에서도 고객의 관심 정보를 파악하고 단순히 무작위로 노출하는 광고가 아닌 고객에게 적합한 광고를 제공하여 만족도 높은 구매 환경이 조성될 것이다.