• Title/Summary/Keyword: Online shopping Mall

Search Result 355, Processing Time 0.034 seconds

The Effects of Product Involvement on Required Trust Level and the Online Merchant Choice (제품관여도가 요구 신뢰수준 및 온라인 상인의 선택에 미치는 영향)

  • Lee, Jung-Min;Cho, Hwi-Hyung;Seo, Yong-Won;Hong, Il-Yoo
    • Information Systems Review
    • /
    • v.13 no.2
    • /
    • pp.17-41
    • /
    • 2011
  • A review of the related literature indicates that consumers' risk perceptions are largely affected by product involvement. This study investigates the impact of product involvement on required trust level and the online merchant choice. We developed a conceptual model that depicts the nomological relationships among product involvement, required trust level, and the online merchant choice, and formulated three hypotheses based on the conceptual model. An empirical study designed to accomplish the research objectives has been conducted using a questionnaire survey with 230 students in a university in Korea. The findings indicated that high-involvement products have higher trust level as required by consumers than low-involvement products, that consumers buying high-involvement products prefer digital storefronts, and that consumers buying low-involvement products prefer B2C e-marketplaces. The paper offers implications for academics as well as practitioners, based on the research results.

Consumer Behavior for Regional Shopping Facilities and its Impact on Small Businesses (광역쇼핑시설의 중소유통 상권잠식 효과: 복합쇼핑몰 등 4개 신유통업태를 중심으로)

  • Shin, Ki Dong;Park, Ju-Young
    • Korean small business review
    • /
    • v.41 no.1
    • /
    • pp.53-73
    • /
    • 2019
  • Recently, as the number of shopping facilities has increased, such as complex shopping malls, warehouse type superstores, large fashion outlets, and so on, the conflicts over the opening of large stores between neighboring municipalities are increasing. However, current regulations on the opening of large-scale stores, such as the impact analysis on commercial area, do not adequately reflect the characteristics of new type shopping facilities. In this study, we tried to suggest a rational policy alternative with more realistic suitability by analyzing the characteristics of 'regional shopping facilities' beyond the scope of the municipalities, and analyzing the impact on the regional merchants. The main results of the study are summarized as follows. First, unlike previous researches, which are limited to small business sector, this study presents the results of comprehensively comparing and analyzing the impact on the detailed sectors of the whole distribution market, including the large distribution sector and online distribution sector. Second, in this study, we calculated the total (average) amount of market penetration rate of existing shopping facilities by the entire regional shopping facilities in the Seoul metropolitan area, and this is considered to be of great value in relation to the recognition of problems at the whole level of the metropolitan area and the search for alternative solutions.

A Hybrid Collaborative Filtering-based Product Recommender System using Search Keywords (검색 키워드를 활용한 하이브리드 협업필터링 기반 상품 추천 시스템)

  • Lee, Yunju;Won, Haram;Shim, Jaeseung;Ahn, Hyunchul
    • Journal of Intelligence and Information Systems
    • /
    • v.26 no.1
    • /
    • pp.151-166
    • /
    • 2020
  • A recommender system is a system that recommends products or services that best meet the preferences of each customer using statistical or machine learning techniques. Collaborative filtering (CF) is the most commonly used algorithm for implementing recommender systems. However, in most cases, it only uses purchase history or customer ratings, even though customers provide numerous other data that are available. E-commerce customers frequently use a search function to find the products in which they are interested among the vast array of products offered. Such search keyword data may be a very useful information source for modeling customer preferences. However, it is rarely used as a source of information for recommendation systems. In this paper, we propose a novel hybrid CF model based on the Doc2Vec algorithm using search keywords and purchase history data of online shopping mall customers. To validate the applicability of the proposed model, we empirically tested its performance using real-world online shopping mall data from Korea. As the number of recommended products increases, the recommendation performance of the proposed CF (or, hybrid CF based on the customer's search keywords) is improved. On the other hand, the performance of a conventional CF gradually decreased as the number of recommended products increased. As a result, we found that using search keyword data effectively represents customer preferences and might contribute to an improvement in conventional CF recommender systems.

Effect of On/off-line Acquaintance's Recommendation Message on Product Attitude and Purchase Intention (온·오프라인 지인의 추천메시지가 제품태도와 구매의도에 미치는 영향)

  • Lee, Jung-Woo;Kim, Mi Young
    • Journal of the Korean Society of Clothing and Textiles
    • /
    • v.40 no.6
    • /
    • pp.1010-1024
    • /
    • 2016
  • This study identifies the influence of on/off-line acquaintances' recommendation messages on fashion product attitude and purchase intention on the online purchase of fashion products in two-sided word of mouth situations as well as compares the difference in influence according to bond-base with equidistance. This study was conducted for one month on university students in their 20s who were believed to be active in smartphone use. Out of the collected 174 copies of the questionnaire, 162 copies were used for analysis. The questionnaire was classified into online and offline recommendation messages of an acquaintance. We present two-sided fashion product reviews made similar to the type found in an actual shopping mall web-site. As for analysis, confirmatory factory analysis, structural equation modeling, and multi-group analysis were conducted using AMOS 19.0. The analysis results are as follows. First, on/off-line acquaintances' recommendation messages had significant influences on product attitude in the situation where two-sided reviews on fashion products were presented; however, those messages did not influence purchase intention. Recommendation messages positively increased product attitude and enhanced purchase intention if acquaintances' recommendation messages were mediated between on/off-line acquaintances' recommendation messages and purchase intention. Consequently, a mediating effect on product attitude was revealed. Second, there was no difference between online acquaintances and offline acquaintances in terms of the influence of acquaintances' recommendation messages on product attitude and purchase intention, in the situation where two-sided reviews were presented on online fashion products. Therefore, no control effect according to the type of acquaintance was confirmed.

Effects of Consumer Trust and Perceived Usefulness on Mobile Payments and Online Shopping Website Loyalty (간편결제 서비스에 대한 지각된 유용성 및 신뢰가 결제 및 쇼핑몰 충성도에 미치는 영향)

  • Han, Jin-Hee;Jae, So-Hyun;Kim, Bo-Hyun;Park, Jee-Sun
    • Journal of Digital Convergence
    • /
    • v.13 no.12
    • /
    • pp.75-87
    • /
    • 2015
  • The current study examines whether consumers' perceived usefulness of and trust in the integrated mobile payments services positively influence consumer loyalty to the payments system as well as to the online shopping websites where they have used the payments system. Moreover, the study investigates the effects of individual characteristics and brand awareness of the provider of mobile payments on perceived usefulness and trust. Online survey was administered to consumers ranging in age from 20s to 40s. Data analysis reveals that as consumers' perceived usefulness of and trust in the mobile payments system positively influence consumer loyalty to mobile payments and shopping mall websites. The results of the study suggests that e-commerce's user interface design, particularly the transaction system, should receive greater attention as a basic web element of e-commerce building rather than a set of plug-ins or so.

Open-source robot platform providing offline personalized advertisements (오프라인 맞춤형 광고 제공을 위한 오픈소스 로봇 플랫폼)

  • Kim, Young-Gi;Ryu, Geon-Hee;Hwang, Eui-Song;Lee, Byeong-Ho;Yoo, Jeong-Ki
    • Journal of Convergence for Information Technology
    • /
    • v.10 no.4
    • /
    • pp.1-10
    • /
    • 2020
  • The performance of the personalized product recommendation system for offline shopping malls is poor compared with the one using online environment information since it is difficult to obtain visitors' characteristic information. In this paper, a mobile robot platform is suggested capable of recommending personalized advertisement using customers' sex and age information provided by Face API of MS Azure Cloud service. The performance of the developed robot is verified through locomotion experiments, and the performance of API used for our robot is tested using sampled images from open Asian FAce Dataset (AFAD). The developed robot could be effective in marketing by providing personalized advertisements at offline shopping malls.

The Effects of Intermediary and Site Characteristics of a B2C E-marketplace Upon Trustworthiness Factors and Trust (오픈마켓에서 중개자특성 및 사이트특성이 신뢰가치성 요인과 신뢰에 미치는 영향에 관한 연구)

  • Cho, Hwi-Hyung;Hong, Il-Yoo
    • Information Systems Review
    • /
    • v.11 no.3
    • /
    • pp.83-106
    • /
    • 2009
  • Trust is becoming one of the critical forces that drive consumers into purchases in e-marketplaces, as consumers face uncertainty associated with buying online from unknown sellers. In this paper we propose a consumer trust model specifically designed for an online marketplace. It aims at examining how intermediary and site characteristics of an e-marketplace affect factors of trustworthiness, and understanding the relationship between trustworthiness factors and trust in intermediary. Findings from an empirical analysis indicate that both intermediary and site characteristics are positively associated with factors of trustworthiness - namely, competence, integrity, and benevolence. In addition, all the three factors of trustworthiness were found to have positive relationship with overall trust in intermediary; in particular, integrity had higher association with trust than the other two factors. The paper concludes with suggestions for building consumer trust for the owners of online marketplaces.

A Study on the Information Cascades Effects of the Offline WOM and Online Review (오프라인 구전과 온라인 리뷰간의 정보 캐스케이드 영향 분석)

  • Kim, Jin-Hwa;Bae, Jae-Kwon;Jeon, Han-Cheol
    • The Journal of Society for e-Business Studies
    • /
    • v.15 no.1
    • /
    • pp.39-60
    • /
    • 2010
  • It becomes common thing that many customers buy the goods through the online shopping mall as internet grows very fast. The information cascades that happen when a person imitates the other's acts also it occurs in online. Many people buy the goods referring on other people's purchasing experiences and such cases are spreading more and more. Through numerous existing researches, the researches in association with this issue have been studied on the information cascades effect on offline or online separately. The research of comparing the information cascades effects from the offline word of mouth (WOM) and the online review has not studied yet. On that reason this study shows that the online review induces the information cascades. We also compared the effects with information cascades effects from traditional offline word of mouth. In result of this study, the following points have been concluded. Firstly, we examined that information cascades was occurred through both the online review and offline word of mouth. Secondly, the information cascades effect through the online review is greater than through the offline words of mouth. It means the company has to understand the importance of the online review and manage it. Thirdly, the information cascades effects are occurred differently in accordance with the goods brands. Therefore a company has to know whether its products is superior to the competitor's one or not.

The Impact of Perceived Risks Upon Consumer Trust and Purchase Intentions (인지된 위험의 유형이 소비자 신뢰 및 온라인 구매의도에 미치는 영향)

  • Hong, Il-Yoo B.;Kim, Woo-Sung;Lim, Byung-Ha
    • Asia pacific journal of information systems
    • /
    • v.21 no.4
    • /
    • pp.1-25
    • /
    • 2011
  • Internet-based commerce has undergone an explosive growth over the past decade as consumers today find it more economical as well as more convenient to shop online. Nevertheless, the shift in the common mode of shopping from offline to online commerce has caused consumers to have worries over such issues as private information leakage, online fraud, discrepancy in product quality and grade, unsuccessful delivery, and so forth, Numerous studies have been undertaken to examine the role of perceived risk as a chief barrier to online purchases and to understand the theoretical relationships among perceived risk, trust and purchase intentions, However, most studies focus on empirically investigating the effects of trust on perceived risk, with little attention devoted to the effects of perceived risk on trust, While the influence trust has on perceived risk is worth studying, the influence in the opposite direction is equally important, enabling insights into the potential of perceived risk as a prohibitor of trust, According to Pavlou (2003), the primary source of the perceived risk is either the technological uncertainty of the Internet environment or the behavioral uncertainty of the transaction partner. Due to such types of uncertainty, an increase in the worries over the perceived risk may negatively affect trust, For example, if a consumer who sends sensitive transaction data over Internet is concerned that his or her private information may leak out because of the lack of security, trust may decrease (Olivero and Lunt, 2004), By the same token, if the consumer feels that the online merchant has the potential to profit by behaving in an opportunistic manner taking advantage of the remote, impersonal nature of online commerce, then it is unlikely that the merchant will be trusted, That is, the more the probable danger is likely to occur, the less trust and the greater need to control the transaction (Olivero and Lunt, 2004), In summary, a review of the related studies indicates that while some researchers looked at the influence of overall perceived risk on trust level, not much attention has been given to the effects of different types of perceived risk, In this context the present research aims at addressing the need to study how trust is affected by different types of perceived risk, We classified perceived risk into six different types based on the literature, and empirically analyzed the impact of each type of perceived risk upon consumer trust in an online merchant and further its impact upon purchase intentions. To meet our research objectives, we developed a conceptual model depicting the nomological structure of the relationships among our research variables, and also formulated a total of seven hypotheses. The model and hypotheses were tested using an empirical analysis based on a questionnaire survey of 206 college students. The reliability was evaluated via Cronbach's alphas, the minimum of which was found to be 0.73, and therefore the questionnaire items are all deemed reliable. In addition, the results of confirmatory factor analysis (CFA) designed to check the validity of the measurement model indicate that the convergent, discriminate, and nomological validities of the model are all acceptable. The structural equation modeling analysis to test the hypotheses yielded the following results. Of the first six hypotheses (H1-1 through H1-6) designed to examine the relationships between each risk type and trust, three hypotheses including H1-1 (performance risk ${\rightarrow}$ trust), H1-2 (psychological risk ${\rightarrow}$ trust) and H1-5 (online payment risk ${\rightarrow}$ trust) were supported with path coefficients of -0.30, -0.27 and -0.16 respectively. Finally, H2 (trust ${\rightarrow}$ purchase intentions) was supported with relatively high path coefficients of 0.73. Results of the empirical study offer the following findings and implications. First. it was found that it was performance risk, psychological risk and online payment risk that have a statistically significant influence upon consumer trust in an online merchant. It implies that a consumer may find an online merchant untrustworthy if either the product quality or the product grade does not match his or her expectations. For that reason, online merchants including digital storefronts and e-marketplaces are suggested to pursue a strategy focusing on identifying the target customers and offering products that they feel best meet performance and psychological needs of those customers. Thus, they should do their best to make it widely known that their products are of as good quality and grade as those purchased from offline department stores. In addition, it may be inferred that today's online consumers remain concerned about the security of the online commerce environment due to the repeated occurrences of hacking or private information leakage. Online merchants should take steps to remove potential vulnerabilities and provide online notices to emphasize that their website is secure. Second, consumer's overall trust was found to have a statistically significant influence on purchase intentions. This finding, which is consistent with the results of numerous prior studies, suggests that increased sales will become a reality only with enhanced consumer trust.

Using Ontologies for Semantic Text Mining (시맨틱 텍스트 마이닝을 위한 온톨로지 활용 방안)

  • Yu, Eun-Ji;Kim, Jung-Chul;Lee, Choon-Youl;Kim, Nam-Gyu
    • The Journal of Information Systems
    • /
    • v.21 no.3
    • /
    • pp.137-161
    • /
    • 2012
  • The increasing interest in big data analysis using various data mining techniques indicates that many commercial data mining tools now need to be equipped with fundamental text analysis modules. The most essential prerequisite for accurate analysis of text documents is an understanding of the exact semantics of each term in a document. The main difficulties in understanding the exact semantics of terms are mainly attributable to homonym and synonym problems, which is a traditional problem in the natural language processing field. Some major text mining tools provide a thesaurus to solve these problems, but a thesaurus cannot be used to resolve complex synonym problems. Furthermore, the use of a thesaurus is irrelevant to the issue of homonym problems and hence cannot solve them. In this paper, we propose a semantic text mining methodology that uses ontologies to improve the quality of text mining results by resolving the semantic ambiguity caused by homonym and synonym problems. We evaluate the practical applicability of the proposed methodology by performing a classification analysis to predict customer churn using real transactional data and Q&A articles from the "S" online shopping mall in Korea. The experiments revealed that the prediction model produced by our proposed semantic text mining method outperformed the model produced by traditional text mining in terms of prediction accuracy such as the response, captured response, and lift.