• Title/Summary/Keyword: Online search

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Designing and Implementing an Online-Helping Systems for Class Registration Management - Relate - Classes Search System Perspective - (학사프로그램을 위한 온라인-도움시스템의 설계 및 구현 - 연계과목 검색 시스템을 중심으로 -)

  • Kim Jun-Woo;Lee Ki-Dong;Kim Hak-Hee
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.27 no.4
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    • pp.147-156
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    • 2004
  • Recently, there is the trend that online and reuse have been focused via digitalization of information and business process that individuals, government and firms own. This study, by designing and implementing a system, has the aim to provide on-line information about the classes and related classes to students on real time. Furthermore, with this system, the students can easily search the necessary class information and understand the curriculum structure. Thus he or she can make a decision about classes and moreover his and her career development. Also this system has been designed to be managed with ease and has more expandibility. Thus this is expected to affect the effort of universities and research centers that the online systems and digital contents have been more applied in order to adapt toward rapidly changing education environment.

Cross-channel consumption behavior of clothing product - A cross-category analysis - (의류제품 크로스채널 소비행동 - 타제품군과의 비교 -)

  • Hong, Woo Jung;Lee, Kyu-Hye
    • The Research Journal of the Costume Culture
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    • v.27 no.2
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    • pp.98-108
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    • 2019
  • With the expansion of various distribution channels in online and offline stores, TV, and mobile, consumers now have more information search and retail selection channels to choose from than ever before. Major retailers now use multi- and omni-channel strategies. This study focused on cross-channel consumption, which involves the use of different information search and purchase channels. Using cross-channel consumption, consumers can search for information online and then make purchases offline and vice versa. The purpose of this study was to examine the relationship between channel strategies and other consumer variables, and the study also assessed the effect of product type. To conduct this empirical study, the researchers developed a consumer questionnaire concerning three consumer channel strategies-on-on, cross, and off-off-and four product categories-clothing, cosmetics, books, and electronics. The results indicated that gender and marital status did not influence consumer channel strategies, but that age did have a significant influence. The analysis showed that consumers in their 40s preferred the cross channel strategy, perceiving it to be effective, satisfactory, and rewarding. Compared to other products, clothing products showed higher levels of cross channel strategies. Consumers indicated that they prefer searching for information online and then purchasing clothing offline. Overall, clothing products generated higher levels of channel satisfaction and channel switch intentions. Cross-channel clothing shoppers reported effective information retrieval times but longer delivery times.

The Determinant Factors Affecting Economic Impact, Helpfulness, and Helpfulness Votes of Online (온라인 리뷰의 경제적 효과, 유용성과 유용성 투표수에 영향을 주는 결정요인)

  • Lee, Sangjae;Choeh, Joon Yeon;Choi, Jinho
    • Journal of Information Technology Services
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    • v.13 no.1
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    • pp.43-55
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    • 2014
  • More and more people are gravitating to reading products reviews prior to making purchasing decisions. As a number of reviews that vary in usefulness are posted every day, much attention is being paid to measuring their helpfulness. The goal of this paper is to investigate firstly various determinants of the helpfulness of reviews, and intends to examine the moderating effect of product type, i.e., search or experience goods on the product sales, helpfulness and helpfulness votes of online reviews. The determinants include product data, review characteristics, and textual characteristics of reviews. The results indicate that the direct effect exists for the determinants of product sales, helpfulness, and helpfulness votes. Further, the moderating effects of product type exist for these determinants on three dependent variables. The results of study will identify helpful online review and design review sites effectively.

A Methodology for Extracting Shopping-Related Keywords by Analyzing Internet Navigation Patterns (인터넷 검색기록 분석을 통한 쇼핑의도 포함 키워드 자동 추출 기법)

  • Kim, Mingyu;Kim, Namgyu;Jung, Inhwan
    • Journal of Intelligence and Information Systems
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    • v.20 no.2
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    • pp.123-136
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    • 2014
  • Recently, online shopping has further developed as the use of the Internet and a variety of smart mobile devices becomes more prevalent. The increase in the scale of such shopping has led to the creation of many Internet shopping malls. Consequently, there is a tendency for increasingly fierce competition among online retailers, and as a result, many Internet shopping malls are making significant attempts to attract online users to their sites. One such attempt is keyword marketing, whereby a retail site pays a fee to expose its link to potential customers when they insert a specific keyword on an Internet portal site. The price related to each keyword is generally estimated by the keyword's frequency of appearance. However, it is widely accepted that the price of keywords cannot be based solely on their frequency because many keywords may appear frequently but have little relationship to shopping. This implies that it is unreasonable for an online shopping mall to spend a great deal on some keywords simply because people frequently use them. Therefore, from the perspective of shopping malls, a specialized process is required to extract meaningful keywords. Further, the demand for automating this extraction process is increasing because of the drive to improve online sales performance. In this study, we propose a methodology that can automatically extract only shopping-related keywords from the entire set of search keywords used on portal sites. We define a shopping-related keyword as a keyword that is used directly before shopping behaviors. In other words, only search keywords that direct the search results page to shopping-related pages are extracted from among the entire set of search keywords. A comparison is then made between the extracted keywords' rankings and the rankings of the entire set of search keywords. Two types of data are used in our study's experiment: web browsing history from July 1, 2012 to June 30, 2013, and site information. The experimental dataset was from a web site ranking site, and the biggest portal site in Korea. The original sample dataset contains 150 million transaction logs. First, portal sites are selected, and search keywords in those sites are extracted. Search keywords can be easily extracted by simple parsing. The extracted keywords are ranked according to their frequency. The experiment uses approximately 3.9 million search results from Korea's largest search portal site. As a result, a total of 344,822 search keywords were extracted. Next, by using web browsing history and site information, the shopping-related keywords were taken from the entire set of search keywords. As a result, we obtained 4,709 shopping-related keywords. For performance evaluation, we compared the hit ratios of all the search keywords with the shopping-related keywords. To achieve this, we extracted 80,298 search keywords from several Internet shopping malls and then chose the top 1,000 keywords as a set of true shopping keywords. We measured precision, recall, and F-scores of the entire amount of keywords and the shopping-related keywords. The F-Score was formulated by calculating the harmonic mean of precision and recall. The precision, recall, and F-score of shopping-related keywords derived by the proposed methodology were revealed to be higher than those of the entire number of keywords. This study proposes a scheme that is able to obtain shopping-related keywords in a relatively simple manner. We could easily extract shopping-related keywords simply by examining transactions whose next visit is a shopping mall. The resultant shopping-related keyword set is expected to be a useful asset for many shopping malls that participate in keyword marketing. Moreover, the proposed methodology can be easily applied to the construction of special area-related keywords as well as shopping-related ones.

Iterative Cyclic Model of Generation MZ's Consumer Purchase Decision Journey for a Fashion Product (MZ세대 소비자의 패션상품 구매의사결정여정의 반복순환모델)

  • Lee, Jung-Woo;Kim, Mi Young
    • Journal of the Korean Society of Clothing and Textiles
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    • v.46 no.4
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    • pp.638-656
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    • 2022
  • This study aimed to identify characteristics of Generation MZ's consumer purchase decision journey to develop the new fashion CDJ model. The initial stage was affected by habit, online community, social media, aesthetics, circumstantial need, and proxy. In the search and consideration stage, mobile channels were used actively. In the active search and evaluation stage, online media, experiential data, and personal information were employed. In the purchase stage, zoomers took plenty of time in search and evaluation before spending, contrary to millennials who made their purchases more quickly. In the post-purchase experience stage, zoomers actively displayed follow-up behaviors depending on their satisfaction, such as retaining or deleting the app. While, millennials did not turn away from the store or brand, but followed up on their purchases even when they had an unsatisfactory experience. Based on the characteristics of CDJ, iterative cycle CDJ models were developed. Zoomers CDJ model was presented as a search loop that consists of the search and evaluation process, in which information accumulates, and a purchase loop in which the actual purchase occurs. The iterative cycle CDJ model was presented connected to the loyalty loop as the main section, which is accelerated in millennials' CDJ model.

A Study on LibraryLookup Services Using Bookmarklets (북마크릿을 활용한 LibraryLookup 서비스 제공방안에 관한 연구)

  • Gu, Jung-Eok;Lee, Eung-Bong
    • Journal of the Korean Society for information Management
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    • v.23 no.3 s.61
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    • pp.49-68
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    • 2006
  • It is required to enhance the value of ISBN as a tool for book search, identification, browsing, and improve the accessability and search capability of library OPAC. Bookmarklet is a small size javascript which can be saved as URL in a web browser bookmark or web page hyperlink. Open source bookmarklet can extract ISBN from web pages and search a book from library OPAC using the ISBN, so it is recognized as a simple but powerful search tool. In foreign countries, commercial library system vendors, libraries, OCLC, etc. are providing bookmarklets which allow a user to search for library holdings and loan information in a real time while he/she is travelling in an online bookshop web page. Therefore, this paper compared and analyzed international bookmarklets application examples and proposed LibraryLookup service in which library OPAC and online bookshop can make use of the bookmarklets.

A Study on the Searching Behavior of the Online Database Searchers (온라인 데이터베이스 탐색자의 탐색 행태에 관한 연구)

  • 장혜란
    • Journal of the Korean Society for information Management
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    • v.8 no.2
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    • pp.32-73
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    • 1991
  • The purpose of this study is to find important personal characteristics that affect search process and outcome, and to formulate causal models about searching behavior, by examining the channels and the magnitude of the factors identified. The study was designed to conduct a quasi-experiment with 67 student subjects. A total of 29 elements concerned with aptitude, personality, formal education, effectiveness of online training, search process, and search outcome are measured and reduced to 9 variables. 12 hypotheses were tested statistically and path analysis was done to investigate causal relationship among variables. Finally 5 models were formulated.

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How to improve oil consumption forecast using google trends from online big data?: the structured regularization methods for large vector autoregressive model

  • Choi, Ji-Eun;Shin, Dong Wan
    • Communications for Statistical Applications and Methods
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    • v.29 no.1
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    • pp.41-51
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    • 2022
  • We forecast the US oil consumption level taking advantage of google trends. The google trends are the search volumes of the specific search terms that people search on google. We focus on whether proper selection of google trend terms leads to an improvement in forecast performance for oil consumption. As the forecast models, we consider the least absolute shrinkage and selection operator (LASSO) regression and the structured regularization method for large vector autoregressive (VAR-L) model of Nicholson et al. (2017), which select automatically the google trend terms and the lags of the predictors. An out-of-sample forecast comparison reveals that reducing the high dimensional google trend data set to a low-dimensional data set by the LASSO and the VAR-L models produces better forecast performance for oil consumption compared to the frequently-used forecast models such as the autoregressive model, the autoregressive distributed lag model and the vector error correction model.

An Empirical Study on Influencing Factors of Switching Intention from Online Shopping to Webrooming (온라인 쇼핑에서 웹루밍으로의 쇼핑전환 의도에 영향을 미치는 요인에 대한 연구)

  • Choi, Hyun-Seung;Yang, Sung-Byung
    • Journal of Intelligence and Information Systems
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    • v.22 no.1
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    • pp.19-41
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    • 2016
  • Recently, the proliferation of mobile devices such as smartphones and tablet personal computers and the development of information communication technologies (ICT) have led to a big trend of a shift from single-channel shopping to multi-channel shopping. With the emergence of a "smart" group of consumers who want to shop in more reasonable and convenient ways, the boundaries apparently dividing online and offline shopping have collapsed and blurred more than ever before. Thus, there is now fierce competition between online and offline channels. Ever since the emergence of online shopping, a major type of multi-channel shopping has been "showrooming," where consumers visit offline stores to examine products before buying them online. However, because of the growing use of smart devices and the counterattack of offline retailers represented by omni-channel marketing strategies, one of the latest huge trends of shopping is "webrooming," where consumers visit online stores to examine products before buying them offline. This has become a threat to online retailers. In this situation, although it is very important to examine the influencing factors for switching from online shopping to webrooming, most prior studies have mainly focused on a single- or multi-channel shopping pattern. Therefore, this study thoroughly investigated the influencing factors on customers switching from online shopping to webrooming in terms of both the "search" and "purchase" processes through the application of a push-pull-mooring (PPM) framework. In order to test the research model, 280 individual samples were gathered from undergraduate and graduate students who had actual experience with webrooming. The results of the structural equation model (SEM) test revealed that the "pull" effect is strongest on the webrooming intention rather than the "push" or "mooring" effects. This proves a significant relationship between "attractiveness of webrooming" and "webrooming intention." In addition, the results showed that both the "perceived risk of online search" and "perceived risk of online purchase" significantly affect "distrust of online shopping." Similarly, both "perceived benefit of multi-channel search" and "perceived benefit of offline purchase" were found to have significant effects on "attractiveness of webrooming" were also found. Furthermore, the results indicated that "online purchase habit" is the only influencing factor that leads to "online shopping lock-in." The theoretical implications of the study are as follows. First, by examining the multi-channel shopping phenomenon from the perspective of "shopping switching" from online shopping to webrooming, this study complements the limits of the "channel switching" perspective, represented by multi-channel freeriding studies that merely focused on customers' channel switching behaviors from one to another. While extant studies with a channel switching perspective have focused on only one type of multi-channel shopping, where consumers just move from one particular channel to different channels, a study with a shopping switching perspective has the advantage of comprehensively investigating how consumers choose and navigate among diverse types of single- or multi-channel shopping alternatives. In this study, only limited shopping switching behavior from online shopping to webrooming was examined; however, the results should explain various phenomena in a more comprehensive manner from the perspective of shopping switching. Second, this study extends the scope of application of the push-pull-mooring framework, which is quite commonly used in marketing research to explain consumers' product switching behaviors. Through the application of this framework, it is hoped that more diverse shopping switching behaviors can be examined in future research. This study can serve a stepping stone for future studies. One of the most important practical implications of the study is that it may help single- and multi-channel retailers develop more specific customer strategies by revealing the influencing factors of webrooming intention from online shopping. For example, online single-channel retailers can ease the distrust of online shopping to prevent consumers from churning by reducing the perceived risk in terms of online search and purchase. On the other hand, offline retailers can develop specific strategies to increase the attractiveness of webrooming by letting customers perceive the benefits of multi-channel search or offline purchase. Although this study focused only on customers switching from online shopping to webrooming, the results can be expanded to various types of shopping switching behaviors embedded in single- and multi-channel shopping environments, such as showrooming and mobile shopping.

Knowledge Level of Users of Keyword/Boolean Searching on an Online Public Access Catalog : SELIS (OPAC에 있어서 키워드/불연산자 탐색에 대한 이용자 지식수준 연구)

  • Koo Bon-Young
    • Journal of the Korean Society for Library and Information Science
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    • v.32 no.4
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    • pp.249-274
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    • 1998
  • It is the analyses of replies showed n the questionnaire consisted of four kinds of matters to see level of knowledge among SELIS (SEoul Women's University Library and Information System) OPAC users of keyword/boolean search. The result of this analyses is : in SELIS search, users who prefer keyword search than any other, who satisfy work of retrieval by means of boolean operator, and who think it easier, show lusher level of knowledge than those who deny it in the questionnaire. Knowledges Presented in the survey are ; characteristics of keyword search, single or double keys, using boolean operator in keyword, knowledge of index, knowledge of stop list, uncontrolled term. keyword search technique, right truncation, correct application of boolean logic operator, and selecting major subject in keyword browsing. The above mentioned knowledges will work as important factors n keyword/boolean search, OPAC. For successful search it requires conceptional knowledge of information retrieval processing, or inquiry word transformation how to search required information, and semantic ability to get result questioned In the given system, when and how to apply the characteristics of the system, and scientific record for user's inquiry, or fundamental computer technology and syntax knowledge to make search word in detail. But so far now important knowledge considered as user's online index search, has been emphasized on knowledge of scientific record, and has been lag of semantic and conceptional knowledge. So, it is recommendable for online index user to train to concentrate semantic knowledge, syntax ability, and conceptional knowledge, rather than scientific technique too much.

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