• Fashion & Textile Research Journal
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• v.12 no.2
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• pp.188-193
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• 2010

The purpose of this study was to investigate the online review writing motives of online shopping on repurchase intention and recommendation intention about fashion merchandise. The questionnaire was administered to 279 people who had experience in online shopping. The data were analyzed by utilizing factor analysis, multiple regression analysis and t-test. The results of this study were as follow. First, the online review writing motives were divided into three categories such as benefit pursuit/hedonic shopping value, information transmission and evaluation. Second, the consumer who has experience of writing review prefers to repurchase other products in that online shopping mall and to recommend those products more than the consumer who doesn't have that experience. Third, the benefit pursuit/hedonic and information transmission had an effect on repurchasing intention and recommendation intention.

• Information Systems Review
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• v.25 no.4
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• pp.67-87
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• 2023

Many online shopping sites now offer personalized recommendation systems to improve consumers' shopping experiences by lowering costs (time, cost, etc.), catering to consumers' tastes, and stimulating consumers' potential shopping needs. So far, domestic and foreign research on the personalized recommendation system has mainly focused on the field of computer science, which is advantageous for obtaining accurate personalized recommendation results for users but difficult to continuously track the users' psychological states or behavioral intentions. This study attempted to investigate the effect of the characteristics of the personalized recommendation system in the online shopping environment on consumer perception and purchase intention for consumers using the Stimulus-Organism-Response (S-O-R) model. The analysis results adopted all hypotheses on the effect of the quality of the personalized recommendation system and information quality on trust and perceived value. Through the empirical results of this study, the factors influencing consumers' use of personalized recommendation system can be identified. In order to increase more purchase, online shopping companies need to understand consumers' tastes and improve the quality of the personalized system by improving the recommendation algorithm thus to provide more information about products.

• Soft Computing and Machine Intelligence
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• v.1 no.1
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• pp.31-35
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• 2021

In recent years, due to COVID-19, the process of shopping has become more restricted and difficult for customers. Based on this aspect, customers are more interested in online shopping to keep the Untact rules and stay safe, similarly ordering their product based on their need and interest with most straightforward and fastest ways. In this paper, the reinforcement learning technique is applied in the product recommendation system to improve the recommendation system quality for better and more related suggestions based on click patterns and users' profile information. The dataset used in this system was taken from an online shopping mall in Jeju island, South Korea. We have compared the proposed method with the recent state-of-the-art and research results, which show that reinforcement learning effectiveness is higher than other approaches.

• Journal of Distribution Science
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• v.15 no.2
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• pp.15-20
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• 2017

Purpose - This paper aims to suggest a delivery constrained internet shopping optimization problem (DISOP) which must be solved for online recommendation system to provide a customized service considering cost and delivery conditions at the same time. Research design, data, and methodology - To solve a (DISOP), we propose a multi-objective formulation and a solution approach. By using a commercial optimization software (LINDO), a (DISOP) can be solved iteratively and a pareto optimal set can be calculated for real-sized problem. Results - We propose a new research problem which is different with internet shopping optimization problem since our problem considers not only the purchasing cost but also delivery conditions at the same time. Furthermore, we suggest a multi-objective mathematical formulation for our research problem and provide a solution approach to get a pareto optimal set by using numerical example. Conclusions - This paper proposes a multi-objective optimization problem to solve internet shopping optimization problem with delivery constraint and a solution approach to get a pareto optimal set. The results of research will contribute to develop a customized comparison and recommendation system to help more easy and smart online shopping service.

• The Journal of the Korea institute of electronic communication sciences
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• v.9 no.8
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• pp.945-953
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• 2014

This study attempts to explore the connectivity among brand personality, shopping value, customer satisfaction and recommendation intention by deriving brand personality image factors of online shopping malls. The analysis results are as follows. First, the brand personality of shopping malls were derived as 'vital', 'familiar', 'credible', 'competent', and 'sophisticated.' Second, shopping value was derived as hedonistic and practical shopping values. Third, it was shown that brand personality of shopping malls has significant impacts on shopping value. In addition, customers' shopping value, customer satisfaction and recommendation intention have significant impacts on each other. It is expected that this study can provide basic information for constructing differentiated marketing strategies in the domestic online shopping malls whose competition is heating up.

• Journal of Distribution Science
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• v.15 no.7
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• pp.35-41
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• 2017

Purpose - A product bundling is a marketing approach where multiple products or components are packaged together into one bundle solution. This paper aims to introduce an optimal bundle search problem (hereinafter called "OBSP") which may be embedded with online recommendation system to provide an optimized service considering pairwise discount and delivery cost. Research design, data, and methodology - Online retailers have their own discount policy and it is time consuming for online shoppers to find an optimal bundle. Unlike an online system recommending one item for each search, the OBSP considers multiple items for each search. We propose a mathematical formulation with numerical example for the OBSP and analyzed the complexity of the problem. Results - We provide two results from the complexity analysis. In general case, the OBSP belongs to strongly NP-Hard which means the difficulty of the problem while the special case of OBSP can be solved within polynomial time by transforming the OBSP into the minimum weighted perfect matching problem. Conclusions - In this paper, we propose the OBSP to provide a customized service considering bundling price and delivery cost. The results of research will be embedded with an online recommendation system to help customers for easy and smart online shopping.

• Journal of the Korean Operations Research and Management Science Society
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• v.32 no.2
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• pp.53-69
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• 2007

Internet shopping websites have offered comfort to consumers in shopping and built trust relationships with them by providing electronic agents for recommendation, escrow services, and customer centers etc. But as there is little big difference among the shopping websites in terms of technical competence, website design, operational policy, they recognize online feedback (reviews or recommendation of consumers or experts) and online feedback mechanism as important marketing tools. Based on online feedback related studies, this study explores antecedents (consensus, vividness of reviews, interactions in review boards) of the perceived effectiveness of review boards which are text-based feedback mechanisms and its consequences such as trust, satisfaction, and intention to use. The results show that the perceived effectiveness of review boards is significantly affected by vividness of reviews and interactions in review boards, and the impact of interaction in review boards on the perceived effectiveness of review boards is stronger than that of vividness of reviews. The results also show that the perceived effectiveness of review boards has a significant influence on trust and satisfaction with the shopping websites, and intention to use is influenced by both trust and satisfaction.

• The Journal of Economics, Marketing and Management
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• v.11 no.1
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• pp.21-30
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• 2023

Purpose: As one of the ongoing studies on the distribution industry, the purpose of this study is to identify the research trends on online shopping so far to propose not only the development of online shopping companies but also the possibility of coexistence between online and offline retailers and the development of the distribution industry. Research design, data and methodology: In this study, the English abstracts of 645 papers on online shopping registered in scienceON were obtained. For the analysis through BERTopic and LDA using Python 3.7 and identifying which topics were interesting to researchers. Results: As a result of word frequency analysis and co-occurrence analysis, it was found that studies related to online shopping were frequently conducted on factors such as products, services, and shopping malls. As a result of BERTopic, five topics such as 'service quality' and 'sales strategy' were derived, and as a result of LDA, three topics including 'purchase experience' were derived. It was confirmed that 'Customer Recommendation' and 'Fashion Mall' showed relatively high interest, and 'Sales Strategy' showed relatively low interest. Conclusions: It was suggested that more diverse studies related to the online shopping mall platform, sales content, and usage influencing factors are needed to develop the online shopping industry.

• Journal of the Korean Society of Clothing and Textiles
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• v.36 no.11
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• pp.1222-1236
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• 2012

This study examined the effects of product recommendation services as an atmosphere for online mass customization shopping sites on consumers' cognitive and affective responses. We conducted a between-subject experimental study using a convenience sample of college students. A total of 196 participants provided usable responses for structural equation modeling analysis. The findings of the study support the S-O-R model for a product recommendation system as an element of the shopping environment with an influence on OMC product evaluations and arousal. The results showed that OMC product recommendation service positively affected cognitive and affective responses. The findings of the study suggest that OMC retailers might pay attention to the affective and cognitive responses of consumers through product recommendation services that can enhance product evaluations and OMC usage intentions.

• East Asian Journal of Business Economics (EAJBE)
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• v.7 no.1
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• pp.1-16
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• 2019

Purpose - For the development of fresh food shopping malls, consumers should continue to experience loyalty and favorability for the company's products or brands, and this should lead directly to purchase so that active word-ofmouth and recommendation should be encouraged. Therefore, the purpose of this study is to investigate the effect of e-service quality and e-ERM on e-loyalty with customer satisfaction and commitment as mediators. Research design, data, and methodology - This study was conducted by sample survey method on 320 online customers who have experience in using major online fresh food shopping malls for more than one year. Data analysis methods were frequency analysis, confirmatory factor analysis, reliability analysis, correlation analysis, and structural equation model analysis. Result - Hypothesis 1 through Hypothesis 7 were all supported. The results of this study suggest that e-service quality and e-CRM of online fresh food shopping malls have a significant effect on satisfaction and commitment. Therefore, the conclusion has been derived that the focus of this study, that such satisfaction and commitment have a significant effect on e-customer loyalty. has been supported theoretically and empirically. Conclusion - This study suggests that studies on customer loyalty based on activation commerce factors related to fresh food in online shopping malls will be an index that can reflect on customer's needs corresponding with future trends of not only online shopping malls but also offline shopping malls.