Journal of the Korean Society for Library and Information Science
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v.32
no.4
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pp.209-225
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1998
This research focuses on how users behave when they search by subject using online public access catalog(OPAC). Major findings are as follows. 1)Main access poults are subject field$(55.2\%)$and title field$(42.2\%)$. 2) The search failure rate in subject searching is $59.3\%$. 3) Ma]or reasons for subject search failures are two-fold : use of inappropriate search terms $(48.5\%)$ and non-use of Boolean Operators$(42.5\%)$. 4) In order to overcome search failures users tend to change originally used search terms$(42.0\%)$ and search fields$(33.8\%) into different ones.
Online consumers browse products belonging to a particular product line or brand for purchase, or simply leave a wide range of navigation without making purchase. The research on the behavior and purchase of online consumers has been steadily progressed, and related services and applications based on behavior data of consumers have been developed in practice. In recent years, customization strategies and recommendation systems of consumers have been utilized due to the development of big data technology, and attempts are being made to optimize users' shopping experience. However, even in such an attempt, it is very unlikely that online consumers will actually be able to visit the website and switch to the purchase stage. This is because online consumers do not just visit the website to purchase products but use and browse the websites differently according to their shopping motives and purposes. Therefore, it is important to analyze various types of visits as well as visits to purchase, which is important for understanding the behaviors of online consumers. In this study, we explored the clustering analysis of session based on click stream data of e-commerce company in order to explain diversity and complexity of search behavior of online consumers and typified search behavior. For the analysis, we converted data points of more than 8 million pages units into visit units' sessions, resulting in a total of over 500,000 website visit sessions. For each visit session, 12 characteristics such as page view, duration, search diversity, and page type concentration were extracted for clustering analysis. Considering the size of the data set, we performed the analysis using the Mini-Batch K-means algorithm, which has advantages in terms of learning speed and efficiency while maintaining the clustering performance similar to that of the clustering algorithm K-means. The most optimized number of clusters was derived from four, and the differences in session unit characteristics and purchasing rates were identified for each cluster. The online consumer visits the website several times and learns about the product and decides the purchase. In order to analyze the purchasing process over several visits of the online consumer, we constructed the visiting sequence data of the consumer based on the navigation patterns in the web site derived clustering analysis. The visit sequence data includes a series of visiting sequences until one purchase is made, and the items constituting one sequence become cluster labels derived from the foregoing. We have separately established a sequence data for consumers who have made purchases and data on visits for consumers who have only explored products without making purchases during the same period of time. And then sequential pattern mining was applied to extract frequent patterns from each sequence data. The minimum support is set to 10%, and frequent patterns consist of a sequence of cluster labels. While there are common derived patterns in both sequence data, there are also frequent patterns derived only from one side of sequence data. We found that the consumers who made purchases through the comparative analysis of the extracted frequent patterns showed the visiting pattern to decide to purchase the product repeatedly while searching for the specific product. The implication of this study is that we analyze the search type of online consumers by using large - scale click stream data and analyze the patterns of them to explain the behavior of purchasing process with data-driven point. Most studies that typology of online consumers have focused on the characteristics of the type and what factors are key in distinguishing that type. In this study, we carried out an analysis to type the behavior of online consumers, and further analyzed what order the types could be organized into one another and become a series of search patterns. In addition, online retailers will be able to try to improve their purchasing conversion through marketing strategies and recommendations for various types of visit and will be able to evaluate the effect of the strategy through changes in consumers' visit patterns.
Purpose - The purpose of this study is to examine the influence of the compulsive hoarding behavior of consumers on the intention to purchase hedonic and utilitarian types of products. Design/methodology/approach - The online and offline survey was conducted and a total of 210 domestic data were collected. Simple and multiple regression analysis and ANOVA were conducted to analyze the data. Findings - First, the consumers'compulsive hoarding behavior had a significantly positive influence on the purchase intention. According to the analysis results of the sub-factors, however, only 'Difficulty Discarding' had a significant influence on the purchase intention, while 'Clutter' and 'Acquisition' did not. Second, as the results of identifying the moderating effect by product type in the purchase intention in accordance with the consumers'compulsive hoarding behavior, their compulsive hoarding behavior had a significant influence on only the intention to purchase hedonic products but not on the intention to purchase utilitarian ones. Similarly, the results of analyzing the sub-factors showed that only'Difficulty Discarding' significantly influenced the intention to purchase hedonic types of products, but 'Clutter' and 'Acquisition' were not significantly influential to both the hedonic and utilitarian types of products. Research implications or Originality - First, this study is meaningful in that it expanded the research discussion on compulsive hoarding behavior by conducting empirical research on this behavior in the general public, which is unlike the previous studies that focused on only severe pathological compulsive hoarding behavior. Second, it identified that the consumers'compulsive hoarding behavior could cause purchase behaviors that were different depending on the type of product by searching the purchase intention with divided types of products (hedonic and utilitarian).
This study is set out to investigate the factors that influence customers' behavior of choice and switching between online and offline channels, separating the purchase decision into two stages, i.e., information search and purchase. Factors influencing channel choice are found to differ from stage to stage. The main results of this study are as follows. At the information search stage, customers' channel knowledge had impacts on the choice of the channel. Customers are more likely to visit offline bookstores when they have hedonic shopping orientation and higher involvement level with books. On the contrary, customers are more apt to search online when they have a lot of online shopping experiences. At the purchase stage, the results varied according to the search channel. When customers search for information online, the following variables lead to online purchases: online shopping experiences with books, price-focused shopping orientation, and time availability for shopping. Perceived risk made customers purchase offline even though they searched online. In case of offline searching, customers with more convenience-focused, hedonic-focused shopping orientation and less tim availability purchased offline.
Journal of the Korean BIBLIA Society for library and Information Science
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v.20
no.1
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pp.209-220
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2009
The purpose of this study is to investigate the information behavior of the junior high school students in the public library and to find the effectiveness of the behavior analysis using a cognitive work analysis(CWA). Data was collected through a dept interview and an observation method. Results show that the students had four constraints when they searched materials for reports: relevant materials for reports, limitation of materials, opening hours, use possibility. There are three behavior types. A type is that students find materials on the shelf through searching an online catalog, then make a report using reading the materials. B type is that students find materials on the shelf and check out the materials. C type is that students find materials and check out them by library staff help. CWA can be used for the information behavior research on the library space. CWA can, however, apply for space redesign when various researches would be conducted about the information behavior.
KIPS Transactions on Software and Data Engineering
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v.10
no.6
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pp.223-234
/
2021
Recent advances in the 4th Industrial Revolution have accelerated the change of the shopping behavior from offline to online. Search queries show customers' information needs most intensively in online shopping. However, there are not many search query research in the field of search, and most of the prior research in the field of search query research has been studied on a limited topic and data-based basis based on researchers' qualitative judgment. To this end, this study defines the type of search query with data-based quantitative methodology by applying machine learning to search research query field to define the 15 topics of search query by conducting topic modeling based on search query and clicked document information. Furthermore, we present a new classification system of new search query types representing searching behavior characteristics by extracting key variables through principal component analysis and analyzing. The results of this study are expected to contribute to the establishment of effective search services and the development of search systems.
Some consumers prefer online and others prefer offline. What makes them prefer online or offline? There has been a lack of theoretical development to adequately explain consumers' channel switching behavior between traditional physical stores and new virtual stores. Through consumers' purchase decision processes, this study examined the reasons why consumers changed channels depending on purchase process stages. Consumer's purchase decision process could be divided into three stages: pre-purchase stage, purchase stage, and post-purchase stage. We used the intention of channel selection as a surrogate dependent variable of channel selection. And some constructs, that is, channel function, channel benefits, customer relationship benefits, and perceived behavioral control, were selected as independent variables. In buying look-and-feel products, it was identified that consumers preferred virtual stores to physical stores at pre-purchase stage. To put it concretely, all constructs except channel benefits were more influenced to consumers at virtual stores. This result implied that information searching function, which is a main function at pre-purchase stage, was better supported by virtual stores than physical stores. In purchase stage, consumers preferred physical stores to virtual stores. Specially, all constructs influenced much more to consumers at physical stores. This result implied that although escrow service and trusted third parties were introduced, consumers felt that financial risk, performance risk, social risk, etc. still remained highly online. Finally, consumers did not prefer any channel at post-purchase stage. But three independent variables, i.e. channel function, channel benefits, and customer relationship benefits, were significantly preferred at physical stores rather than virtual stores at post-purchase stage. So we concluded that physical stores were a little more preferred to virtual stores at post-purchase stage. Through this study, it was identified that most consumers might switch channels according to purchase process stages. So, first of all, sales representatives should decide that what benefits should be given them through virtual stores at the pre-purchase stage and through physical stores at the purchase and post-purchase stages, and then devise collaborative channel strategies.
In this study, we determined the characteristics and importance of market maven to today's fashion retailers. Market maven is defined as an individual who is highly involved in the marketplace and takes a role as an information diffuser. In order to identify market maven, a total of 415 data were collected from 30-40 consumers who purchased fashion items from the various types of retailers. The data were divided into three groups based on the average score of summated market maven's scale, and the high group was referred to as "market mavens." Results suggested that the market mavens existed in the fashion retailing market and presented the differences from the other two groups. The market maven group spent more and purchased more fashion items than the other groups. With respect to shopping behavior, the market maven group was more likely to browse and bargain hunt when shopping, and showed higher mean scores on impulse buying and overall satisfaction. In addition, market maven tended to purchase fashion items from different types of retailers including online channel. Accordingly, market mavens seemed to present common characteristics with heavy browser, recreational shopper, and/or multi-channel shopper. Market mavens showed shopping enjoyment characteristics when searching for market-related information from various retailers, hence this segment should be the essential target market in the multi-channel retailing environment.
Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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v.8
no.10
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pp.1-9
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2018
The purpose of this exploratory study is to identify the mobile phone applications (apps) used by foreign tourists visiting South Korea through a pilot study using focus groups and individual interviews. Concentrating on tourist mobile app use in a smart tourism environment and categorized through a taxonomy of mobile applications lays the framework and determines the factors boosting tourism smartphone app trends by foreign tourists visiting South Korea. Researchers collected data through ethnographic methods and analyzed it through qualitative research to uncover major themes within the smart tourism app use phenomenon. The researchers coded, counted, analyzed, and then divided the findings gleaned from a pilot study and interviews into a taxonomy of seven logical smartphone app categories. The labeling and coding of all the data accounting for similarities and differences can be recognized and are logically discussed in the implications of the apps used by tourists to assist tourist destinations. More specifically these findings will assist smart tourism destinations by better understanding foreign tourist smartphone app use behavior. Tourists visiting South Korea interviewed in this study exhibited significant mastery of Internet of Things (IoT) technologies, craved free WiFi access, and utilized smartphone apps for all facets of their travel. Findings show major concentrations of app use in bookings of accommodations, tourist attractions, online shopping, navigation, wayfinding, augmented reality, information searching, language translation, gaming, and online dating while traveling in South Korea.
Today, because of the consumers who should constantly decide which to buy in a flood of information can't search for complete information by the limited time and the lack of the ability in evaluating the goods, the price being important as the information clue in consumers' goods or dependence on the price will be gradually increasing. The purpose of this study is to know how much price sensitivity recognized by consumers will have and effect on buying feeling of satisfaction in internet shopping mall. The result of this study is that the consumers' target-oriented behavior searching appropriate price for buying goods in internet shopping mall substantially elevates the price sensitivity and shapes the positive attitude toward the feeling of satisfaction. It is meaningful in that it has provided the base for studying the price sensitivity centering around some limited factors through actual proof of how the consumers respond to the price at this point of activating online transactions.
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