This study considers the effect of smartphone involvement for purchase intentions in fashion shopping malls based on mobile web apps and on PC web apps; in addition, it investigates the correlation between purchase intention in fashion shopping malls (based on activated PC web apps) and those of fashion shopping malls (based on newly created mobile web apps). The results of this study are: First, the analysis of smartphones factors showed that smartphones consist of 6 kinds of dimensions of 'appearance involvement', 'time and information search involvement', 'application involvement', 'entertainment involvement', 'communication involvement', and 'transaction involvement'. Second, the higher the entertainment and transaction involvement among descriptive variables for smartphone involvement were due to the positive responses displayed towards fashion shopping mall purchases based on mobile web apps. Third, a higher application and entertainment involvement in the descriptive variables for smartphones resulted in a positive response displayed for purchases in fashion shopping malls based on PC web apps shown in a regression analysis that verified the smartphone and purchase intention relationship in fashion shopping malls based on PC web apps. Fourth, consumers with high purchase intention in the existing PC web app based fashion shopping malls were shown to have a high purchase intention in mobile web app based fashion shopping malls due to the results of a correlation analysis that analyzed the relationship between purchase intention in PC web app based fashion shopping malls and mobile web app based fashion shopping malls.
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.
Conceptualization of store image have been suggested in the past by many marketing scholars. The dominant perspective about store image is treated as the results of a multi-attribute model. Store image is expressed as a function of the salient attributes of a particular store that are evaluated. Though, there is a little confusions about what elements compose the store image, most scholars agree that merchandise, service, atmosphere, physical facilities, comfort, and location are generally accepted elements as store image. A considerable researches support that shopping can provide both hedonic and utilitarian value. Hedonic shopping value reflects the value received from fantasy and emotive aspects of shopping experience, while utilitarian shopping value reflects the acquisition of products. These two types of shopping value can affect shopping satisfaction. This study examines the relationships among stores images(store atmosphere, salespeople services, facilities, product assortment, and store location), shopping values(utilitarian shopping value and hedonic shopping value), and shopping satisfaction based on discount stores (E-Mart, Home plus, and Lotte Mart). The author hypothesized that five store image components affect shopping values, and these shopping values affect shopping satisfaction. The author focused on the roles of perceived retail crowding between these relationships. Specifically, the author hypothesized that perceived retailing crowding moderated the relationship between shopping values and shopping satisfaction. The author also hypothesized the direct effect of perceived retail crowding on shopping satisfaction. Finally, the author hypothesized that five store image components affect directly shopping satisfaction. Research model is presented in
Many prior studies have been conducted that positive reviews increase the intention to purchase. However, there are very few papers that have studied the impact of review search on purchase satisfaction. It is meaningful to study the impact of review search on purchase satisfaction as it can lead the business successfully by inducing repurchase. There is also no study of how review search have different effects on purchase satisfaction among countries. Given the growing number of cross-border e-commerce, we believe that the need for research is high because identifying these differences between countries can have a very important impact on a company's successful overseas expansion. Therefore, in this study, the impact of positive and negative review search on purchase satisfaction and the national impact were set up as a research model. In order to verify this research model, the survey was distributed to those who experienced online purchase in Korea and China, and a total of 234 copies were collected, including 125 copies in Korea, 109 copies in China, and the research model was verified using Smart-PLS structural equation analysis tools. First, positive review search has been shown to positively affect purchase satisfaction. Second, it has been shown that negative review search also has a positive effect on purchase satisfaction. Third, the impact of positive and negative review search on purchase satisfaction was different between Korea and China. While Korea is more aggressive in review search than China due to its high tendency to avoid uncertainty, China is less likely to avoid uncertainty than Korea and is more likely to rely on brand familiarity. Therefore, according to the uncertainty avoidance moderation effect the impact of positive and negative review search on purchase satisfaction was higher in Korea than in China. In this study, Shopping mall managers need to take strategic measures to maximize shopping mall performance by recognizing positive aspects of negative review search on purchase satisfaction. Companies and managers in Korea and China can establish strategies to promote product sales when companies enter the global market.
For web application vulnerability diagnosis, from the development stage to the operation stage, it is possible to stably operate the web only when there is a policy that is commonly applied to each task through diagnosis of vulnerabilities, removal of vulnerabilities, and rapid recovery from web page damage. KISA presents 28 evaluation items for technical vulnerability analysis of major information and communication infrastructure. In this paper, we diagnose the vulnerabilities in the automobile goods shopping mall website and suggest security measures according to the vulnerabilities. As a result of diagnosing 28 items, major vulnerabilities were found in three items: cross-site scripting, cross-site request tampering, and insufficient session expiration. Cookie values were exposed on the bulletin board, and personal information was exposed in the parameter values related to passwords when personal information was edited. Also, since the session end time is not set, it was confirmed that session reuse is always possible. By suggesting security measures according to these vulnerabilities, the discovered security threats were eliminated, and it was possible to prevent breaches in web applications and secure the stability of web services.
It is possible to provide Smart Tourism Service through the development of information technology. It is necessary for the tourism industry to understand and utilize Big Data that has tourists' consumption patterns and service usage patterns in order to continuously create a new business model by converging with other industries. This study suggests to activate Jeju Smart Tourism by analyzing Big Data based on credit card usage records and location of tourists in Jeju. The results of the study show that First, the percentage of Chinese tourists visiting Jeju has decreased because of the effect of THAAD. Second, Consumption pattern of Chinese tourists is mostly occurring in the northern areas where airports and duty-free shops are located, while one in other regions is very low. The regional economy of Jeju City and Seogwipo City shows a overall stagnation, without changes in policy, existing consumption trends and growth rates will continue in line with regional characteristics. Third, we need a policy that young people flow into by building Jeju Multi-complex Mall where they can eat, drink, and go shopping at once because the number of young tourists and the price they spend are increasing. Furthermore, it is necessary to provide services for life-support related to weather, shopping, traffic, and facilities etc. through analyzing Wi-Fi usage location. Based on the results, we suggests the marketing strategies and public policies for understanding Jeju tourists' patterns and stimulating Jeju tourism industry.
Designed by star architect of Moshes Safdie, Raffles City Chongqing includes a total of 6 mega high-rise towers 250 to 380 m tall, a sky conservatory, a 5-storey high shopping mall and a 3-storey basement car parking. Located at the confluence of the Yangtze and Jailing Rivers, the site for the project is imbued with a significance that is immediately symbolic, both as a sign of Chongqing's important past and as a vivid indicator of the city's thriving present and future. The design for the project to be situated at this gateway takes as its governing idea the image of powerful sails upon the water. The outer facades of the project's eight towers - the transparent surfaces that will face the water to the north - are meant to recall a fleet of ancient Chinese ships, with their huge rectangles of white canvas filled by the wind. This is a
The controversy about the burger button triggered in 2013 is that it is difficult to know what the hamburger button itself means and that it is difficult to predict what will happen when the button is clicked, Could. This controversy was found to be fundamentally out of touch, and it could be seen that it caused conflict with Apple's navigation structure with iOS. Therefore, in the case of Apple, it is often used in the form of a tab at the bottom instead of using the slide menu, but it is preferable to be used for the purpose of the hamburger button. I've looked through a variety of documents and found that the amount of content you want to offer on your app or the web is large, and there are five or more categories. And if a sub-category needs to exist in the main category like a large shopping mall, the hamburger button could provide the best UI. Apps and webs that can be curated, such as news and pinterest, are better used to enhance the search filter than to place a hamburger button, and for apps or the web that has a longer amount of content on a page Scrolling was available as an alternative to the burger button. In other words, depending on the amount of content to be provided, it is possible to decide whether to use the hamburger menu from the time of designing the information architecture.
Recently, due to the advent of ubiquitous computing and the spread of intelligent portable device such as smart phone, iPad and PDA has been amplified, a variety of services and the amount of information has also increased fastly. It is becoming a part of our common life style that the demands for enjoying the wireless internet are increasing anytime or anyplace without any restriction of time and place. And also, the demands for e-commerce and many different items on e-commerce and interesting of associated items are increasing. Existing collaborative filtering (CF), explicit method, can not only reflect exact attributes of item, but also still has the problem of sparsity and scalability, though it has been practically used to improve these defects. In this paper, using a implicit method without onerous question and answer to the users, not used user's profile for rating to reduce customers' searching effort to find out the items with high purchasability, it is necessary for us to analyse the segmentation of customer and item based on customer data and purchase history data, which is able to reflect the attributes of the item in order to improve the accuracy of recommendation. We propose the method of recommendation system using association rule and weighted preference so as to consider many different items on e-commerce and to refect the profit/weight/importance of attributed of a item. To verify improved performance of proposing system, we make experiments with dataset collected in a cosmetic internet shopping mall.
Xiaohongshu is called China's Instagram and is leading overseas product purchases and culture sharing. The purpose of this study is to investigate the structural relationship between Xiaohongshu service quality, emotional response perceived by users, and adhesion to confirm the impact on Xiaohongshu's adhesion at a time when non-face-to-face activities due to COVID-19 have increased. This study distributed and collected questionnaires from October 1st to October 7th, 2021, targeting 210 online shopping mall users. The research results were derived from a total of 206 questionnaires, excluding 4 questionnaires such as omission of record contents, and the causal relationship of the existing PAD model was attempted to be reported by revising and supplementing the existing PAD model. As a result of the study, first, it was confirmed that design among service quality had a positive effect only on ventilation during the user's emotional response. Second, it was confirmed that information among service quality had a positive effect on pleasure and ventilation among users' emotional responses. Third, it was found that security among service quality had a positive effect on pleasure among users' emotional responses. Finally, it was found that pleasure and ventilation had a positive effect on adhesion in the user's emotional response. Based on this result, it is expected that it will be used for operation on other online platforms than the plan for the development of Xiaohongshu.
. To test model and hypotheses, data were collected from 114 consumers located mid-size city in local area. The author employs PLS methodology (SmartPLS 2.0) to test hypotheses. Data analysis results indicate that among five store images salespeople services, and store location affect utilitarian shopping value. Store atmosphere, salespeople services, and store location affect hedonic shopping value. Two shopping values affect shopping satisfaction. Hedonic shopping value affect more shopping satisfaction than utilitarian shopping value. Data analysis results is presented in . The author examines the moderating effects of perceived retail crowding between shopping values and shopping satisfaction. Results indicate that there are no moderating effects between shopping values and shopping satisfaction. Moderating effects of perceived retail crowding between utilitarian shopping value and shopping satisfaction are presented in
. Moderating effects of perceived retail crowding between hedonic shopping value and shopping satisfaction is presented in
. The author analyzed the relationship between perceived retail crowding and shopping satisfaction using WarpPLS 3.0 which can analyze the non-linear relationship. Result indicates that perceived retail crowding affects directly shopping satisfaction and there is a non-linear relationship between them. Among five store image components, store atmosphere and salespeople services affect directly shopping satisfaction. The author describes about the managerial implications, limitations, and future research issues.
A Cross-Country Comparative Study on the Effect of Online Review Search on Purchase Satisfaction of Existing Buyers
(온라인 후기 탐색이 기존 구매자의 구매 만족도에 미치는 영향의 국가 간 비교연구)
Security Measures by Diagnosing Vulnerabilities in Web Applications
A Case Study on the Smart Tourism City Using Big Data: Focusing on Tourists Visiting Jeju Province
(빅 데이터를 활용한 스마트 관광 도시 사례 분석 연구: 제주특별자치도 관광객 데이터를 중심으로)
Multi-Dimensional Hybrid Design and Construction of Skyscraper Cluster -Innovative Engineering of Raffles City Chongqing-
A study on hamburger button UI of smart phone
(스마트 폰의 햄버거 버튼 UI 연구)
A Study of Recommendation System Using Association Rule and Weighted Preference
(연관규칙과 가중 선호도를 이용한 추천시스템 연구)
The Effect of Xiaohongshu Service Quality on the Stickiness Through the Emotional Responses of Users
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