• Journal of the Korean Society of Clothing and Textiles
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• v.48 no.3
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• pp.485-500
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• 2024

This study was conducted to examine the effects of consumer evaluations on size recommendation services based on body information on consumer responses and the moderating effect of the level of information search. To analyze the research model, a total of 200 data were collected from August 18 to 24, 2022, targeting consumers who had experience with using size recommendation services based on body information. As a result of the research model analysis, it was confirmed that the compatibility, reliability, and convenience of the size recommendation services based on body information influenced attitude, which, in turn, influenced usage intention. In addition, In the case of the group subject to a low level of information search, the path through which compatibility and reliability influenced attitude was significant, but that of convenience was not. In the group featuring a high level of information search, the path through which reliability and convenience influenced attitude was significant, but that of compatibility was not. This study is meaningful in that it expanded research related to size recommendation services to the field of consumer behavior.

• Asia pacific journal of information systems
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• v.29 no.2
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• pp.203-216
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• 2019

There is an accuracy-diversity dilemma with personalized recommendation services. Some researchers believe that accurate recommendations might reinforce customer satisfaction. However, others claim that highly accurate recommendations and customer satisfaction are not always correlated. Thus, this study attempts to establish the causal factors that determine customer satisfaction with personalized recommendation services to reconcile these incompatible views. This paper employs statistical analyses of simulation to investigate an accuracy-diversity dilemma with personalized recommendation services. To this end, we develop a personalized recommendation system and measured accuracy, diversity, and customer satisfaction using a simulation method. The results show that accurate recommendations positively affected customer satisfaction, whereas diverse recommendations negatively affected customer satisfaction. Also, customer satisfaction was associated with the recommendation product size when neighborhood size was optimal in accuracy. Thus, these results offer insights into personalizing recommendation service providers. The providers must identify customers' preferences correctly and suggest more accurate recommendations. Furthermore, accuracy is not always improved as the number of product recommendation increases. Accordingly, providers must propose adequate number of product recommendation.

• Journal of the Korean Society of Clothing and Textiles
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• v.48 no.4
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• pp.688-706
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• 2024

This study investigated the effect of self-efficacy on the usage intention of the size recommendation services, exploring the mediating roles of perceived ease of use and perceived usefulness. Moreover, it examined the moderating effects of filtering types on these relationships. Data were collected from 200 participants between December 11 and 13, 2023, using virtual scenarios and stimuli. Mediating and moderating effect analysis were performed using a process macro. As a result of path analysis and indirect effect analysis between individual variables, it was confirmed that the direct effect of self-efficacy for the size recommendation services on usage intention, and the indirect effect on usage intention through perceived ease of use and perceived usefulness were significant. Furthermore, as a result of the moderating effect analysis, it was found that the moderating effect of the filtering types was significant in the relationship between self-efficacy and perceived ease of use, between perceived ease of use and perceived usefulness, and between self-efficacy and usage intention.

• Journal of the Korean Society of Clothing and Textiles
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• v.47 no.3
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• pp.442-458
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• 2023

This study aimed to elucidate the information privacy attitudes and behaviors of users of size recommendation services based on body information. Focusing on the privacy calculus theory, the effects of information privacy concerns as well as perceived risk and benefit of information disclosure on information disclosure intention were analyzed. Consumers who used size recommendation services based on body information were surveyed from August 18 to 24, 2022. Analysis of the 251 responses collected revealed that information privacy concerns did not significantly affect information disclosure intention. Information privacy concerns had a positive effect on perceived privacy risk; however, perceived privacy risk had a negative effect on information disclosure intention, while perceived privacy benefit had a positive effect on information disclosure intention. Therefore, the privacy calculus theory confirms the existence of the privacy paradox, revealing perceived privacy benefit has a greater impact on information disclosure intention than perceived privacy risk.

• Journal of the Korean Society of Clothing and Textiles
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• v.48 no.2
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• pp.350-366
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• 2024

This study aimed to clarify the continuance intention of users of size recommendation services. The expectation-confirmation model framed the analysis of the 180 data points collected. The analysis determined the mediating effects of perceived usefulness and satisfaction on the relationship between expectation-confirmation and continuance intention. The moderated mediation effect of familiarity was also analyzed, and a path analysis was conducted using PROCESS macro. Results showed that expectation-confirmation had a significant effect on perceived usefulness, satisfaction, and continuance intention. Findings indicated that perceived usefulness affected satisfaction and continuance intention and confirmed that satisfaction affected continuance intention. In the relationship between expectation-confirmation and continuance intention, mediation analysis verified the mediation and double mediation of perceived usefulness and satisfaction. In the group with an above-average familiarity value, moderation analysis confirmed a moderating effect between perceived usefulness and satisfaction. Above-average familiarity values also confirmed that the moderating effect on continuance intention was significant.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.39 no.4
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• pp.60-66
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• 2016

Compound logistics is a service aimed to enhance logistics efficiency by supporting that shippers and consigners jointly use logistics facilities. Many of these services have taken place both domestically and internationally, but the joint logistics services for e-commerce have not been spread yet, since the number of the parcels that the consigners transact business is usually small. As one of meaningful ways to improve utilization of compound logistics, we propose a brokerage service for shipper and consigners based on the hybrid recommendation system using very well-known classification and clustering methods. The existing recommendation system has drawn a relatively low satisfaction as it brought about one-to-one matches between consignors and logistics vendors in that such matching constrains choice range of the users to one-to-one matching each other. However, the implemented hybrid recommendation system based brokerage agent service system can provide multiple choice options to mutual users with descending ranks, which is a result of the recommendation considering transaction preferences of the users. In addition, we applied feature selection methods in order to avoid inducing a meaningless large size recommendation model and reduce a simple model. Finally, we implemented the hybrid recommendation system based brokerage agent service system that shippers and consigners can join, which is the system having capability previously described functions such as feature selection and recommendation. As a result, it turns out that the proposed hybrid recommendation based brokerage service system showed the enhanced efficiency with respect to logistics management, compared to the existing one by reporting two round simulation results.

• Journal of the Korea Society of Computer and Information
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• v.28 no.9
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• pp.93-104
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• 2023

In modern society, the service method is tended to prefer the non-face-to-face method rather than the face-to-face method. However, services that recommend products such as shoes will inevitably be face-to-face method. In this paper, for the purpose of non-face-to-face service, a system that a foot size is automatically measured and some shoes are recommended based on the measurement result is proposed. To analyze the performance of the proposed method, size measurement error rate and recommendation performance were analyzed. In the recommendation performance experiments, a total of 10 methods for similarity calculation were used and the recommendation method with the best performance among them was applied to the system. From the experiments, the error rate the foot size was small and the recommendation performance was possible to derive significant results. The proposed method is at the laboratory level and needs to be expanded and applied to the real environment. Also, the recommendation method considering design could be needed in the future work.

• Journal of Information Technology and Architecture
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• v.9 no.1
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• pp.57-66
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• 2012

Recently, with a rapidly growing of the mobile content market, a variety of mobile-based applications are being launched. But mobile devices, compared to the average computer, take a lot of effort and time to get the final contents you want to use due to the restrictions such as screen size and input methods. To solve this inconvenience, a recommender system is required, which provides customized information that users prefer by filtering and forecasting the information.In this study, an tailored multi-information recommendation system utilizing a Personalized information recommendation system on smartphone is proposed. Filtering of information is to predict and recommend the information the individual would prefer to by using the user-based collaborative filtering. At this time, the degree of similarity used for the user-based collaborative filtering process is Euclidean distance method using the Pearson's correlation coefficient as weight value.As a real applying case to evaluate the performance of the recommender system, the scenarios showing the usefulness of recommendation service for the actual restaurant is shown. Through the comparison experiment the augmented reality based multi-recommendation services to the existing single recommendation service, the usefulness of the recommendation services in this study is verified.

• Journal of Fashion Business
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• v.27 no.3
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• pp.50-62
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• 2023

The e-commerce fashion market has experienced a remarkable growth, leading to an overwhelming availability of shared information and numerous choices for users. In light of this, chatbots have emerged as a promising technological solution to enhance personalized services in this context. This study aimed to develop user-product attributes for a chatbot-based personalized fashion recommendation service using big data text mining techniques. To accomplish this, over one million consumer reviews from Coupang, an e-commerce platform, were collected and analyzed using frequency analyses to identify the upper-level attributes of users and products. Attribute terms were then assigned to each user-product attribute, including user body shape (body proportion, BMI), user needs (functional, expressive, aesthetic), user TPO (time, place, occasion), product design elements (fit, color, material, detail), product size (label, measurement), and product care (laundry, maintenance). The classification of user-product attributes was found to be applicable to the knowledge graph of the Conversational Path Reasoning model. A testing environment was established to evaluate the usefulness of attributes based on real e-commerce users and purchased product information. This study is significant in proposing a new research methodology in the field of Fashion Informatics for constructing the knowledge base of a chatbot based on text mining analysis. The proposed research methodology is expected to enhance fashion technology and improve personalized fashion recommendation service and user experience with a chatbot in the e-commerce market.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.5
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• pp.41-50
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• 2020

The paper investigates the factors that affect the demand for a voluntary audit of small and medium-sized enterprises (SMEs) in Vietnam. A structured questionnaire survey of 284 SMEs was employed, preceded by in-depth interviews with auditors and SMEs' managers. The research used logistic regression estimator to address econometric issues and to improve the accuracy of the regression coefficients. The results show that the degree of director's view on voluntary audit, related stakeholder, degree of recommendation, and firm size have a statistically significant positive effect on audit decisions of SMEs while degree of audit fee has a statistically significant negative effect, and degree of subjective norm does not affect. This indicated that SMEs are more likely to have an external audit if they have some typical features: it is becoming larger in terms of size, and the directors consider that the audit has a relative benefit outweighing its cost. The research results suggested that Vietnam Government should make a statutory audit of SMEs' financial statements rather than make it an option for SMEs. The auditing firms were also recommended to actively take their audit services to SMEs rather than waiting for the SMEs' managers to contact them for their services.