• International Commerce and Information Review
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• v.13 no.1
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• pp.3-28
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• 2011

Recently marketing methods of small and medium exporting firms have changed from internet marketing using homepage, or e-catalogs, to search engine marketing. However, there is no specific proof of search engine marketing effectiveness. Therefore the purpose of this research is to explore marketing performance of search engine marketing(SEM) based on search engine optimization. In order to build an optimal SEM strategy, quantitative data are collected from the Google-analytics such as homepage visits, page views, and traffic source for three years. At the same time, this study has carried out a survey to measure the qualitative effectiveness. The result of this quantitative study suggests that the existing carryover effects and lag effects would be maintained through search engine optimization. Meanwhile, the qualitative survey shows that satisfaction and awareness of homepage have been improved after search engine optimization. This can support logically increase of homepage visiting ratio of quantitative analysis. Also exporting companies know very well, that traffic and page views have increased after search engine optimization.

• International Journal of Advanced Culture Technology
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• v.11 no.2
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• pp.358-365
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• 2023

As the Internet is used as a major channel for marketing and sales, the top ranking of search engine results is becoming a key competitor among websites. Various methods exist to maintain the top ranking of websites in search engines, typically investing heavily in organic coding or search engine optimization. The purpose of this paper, we present the ranking by recognizing factors that should be removed as negative factors when designing a web page in consideration of website visibility (SEO) because if website visibility is not met, the ranking may fall behind or be completely removed from the search engine index. The experiments that recognized and ranked the negative factors of website visibility proposed in this paper were provided through theory and experiments based on the existing website visibility analysis model. The models analyzed in this paper, we expressed or quantified as scores based on the methodology of each model, and 10 items were selected as negative factors through experiments and ranked as high scores. Therefore, when designing a website, it should be considered that the website is not removed from the search engine index as it is designed by excluding high-ranking items, which are negative factors.

• The Journal of Industrial Distribution & Business
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• v.8 no.6
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• pp.7-16
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• 2017

Purpose - Today's world revolves around search engines which are the driving force behind any marketer. The thirst for marketing has led to the evolution of online 'Pay per click' over last few years and is the most widely used instrument. Research design, data, and methodology - Exploratory research design highlights many marketing variables getting affected by pay per click marketing. To analyze the said phenomenon, the data was gathered through questionnaire from the sample of 338 respondents which were selected by simple random sampling method mostly from the National Capital Region (NCR) of Delhi in India. The data collected from the respondents was loaded on SAS base for exploratory factor analysis and multiple regression analysis. Results - Pay per click as a marketing tool has significant impact on the consumers. The most prominent factors of pay per click marketing identified in the research are Ad quality, Competition, Targeting, Trend and Budget. Conclusions - Organic as well as inorganic ads, keeping in mind the end goal to gage the exchange of these two postings in the marked look territory. Additionally, here we dissected supported pursuit promotions in all. It would be beneficial to break down the impact of promotion position on the pay per click marketing.

• Asia Marketing Journal
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• v.16 no.3
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• pp.23-33
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• 2014

The selection of keywords for bidding is a critical component of paid search advertising. When the number of possible keywords is enormous, it becomes difficult to choose the best keywords for advertising and then subsequently to assess their effect. To this end, we propose an ultrahigh dimensional keyword selection approach that not only reduces the dimension for selections, but also generates the top listed keywords for profits. An empirical analysis using a unique panel dataset from a large online clothes retailer that advertises on the largest search engine in China (i.e., Baidu) is presented to illustrate the usefulness of our approach.

• Journal of Information Science Theory and Practice
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• v.5 no.4
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• pp.6-25
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• 2017

In this paper, a large-scale study on users' understanding of search-based advertising is presented. It is based on (1) a survey, (2) a task-based user study, and (3) an online experiment. Data were collected from 1,000 users representative of the German online population. Findings show that users generally lack an understanding of Google's business model and the workings of search-based advertising. 42% of users self-report that they either do not know that it is possible to pay Google for preferred listings for one's company on the SERPs or do not know how to distinguish between organic results and ads. In the task-based user study, we found that only 1.3 percent of participants were able to mark all areas correctly. 9.6 percent had all their identifications correct but did not mark all results they were required to mark. For none of the screenshots given were more than 35% of users able to mark all areas correctly. In the experiment, we found that users who are not able to distinguish between the two results types choose ads around twice as often as users who can recognize the ads. The implications are that models of search engine advertising and of information seeking need to be amended, and that there is a severe need for regulating search-based advertising.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.12 no.3
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• pp.23-28
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• 2012

Recently, due to the increasing demand for mobile devices, mobile searching market is rapidly growing. However, there is the limit of screen size, when searching for mobile devices, various results should be shown at a glance. The reason is that results are important given that up to 43 percent of people tend to check only first page. In this paper, a set of keywords for searching will be used to find out the users' interests. Users were divided into groups after going through Collaboration filtering. Therefore, the result of this experiment, reduced time for searching and improved quality of searching were confirmed.

• Journal of the Korea Society of Computer and Information
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• v.15 no.6
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• pp.147-152
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• 2010

The Internet has become a major channel of business marketing and sales, and there is a core competitive object between websites for a high position ranking in search engine results. There are various ways to maintain the high position ranking of website involving the development of componental coding or the expensive investment for the search engine optimization. The purpose of this paper is proposed to identify and rank the negative elements of website visibility to get rid of those elements when website designer designs the webpage. Website can be removed from indices of search engines when they are not satisfied for search engine optimization. The proposed experiments that are identified and ranked the negative elements of website visibility in this paper are based on the theories and experiments of existing website visibility models. The experimental analyses in this paper are scored and normalized based on methodologies of those models and 10 highest negative elements are ranked through the analyses. Therefore when website is designed, these highest negative elements should be avoided so website can not be removed in the indices of search engines.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2019.05a
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• pp.79-82
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• 2019

This study aims to design and implement automated SEO tools that has applied the artificial intelligence techniques for search engine optimization (SEO; Search Engine Optimization). Traditional Search Engine Optimization (SEO) on-page optimization show limitations that rely only on knowledge of webpage administrators. Thereby, this paper proposes the metadata generation system. It introduces three approaches for recommending metadata; i) Downloading the metadata which is the top of webpage ii) Generating terms which is high relevance by using bi-directional Long Short Term Memory (LSTM) based on attention; iii) Learning through the Generative Adversarial Network (GAN) to enhance overall performance. It is expected to be useful as an optimizing tool that can be evaluated and improve the online marketing processes.

• International Commerce and Information Review
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• v.15 no.3
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• pp.411-430
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• 2013

Overseas marketing before the conclusion of a contract is a huge obstacle to enter the global market because it has needed the company's maximum capacities which are some cost, time and human resources. Thus it required a reestablishment about the education fields and research schemes. Due to the advancements in ICT and internet, a subject of e-trade is becoming a critical issue with a subject of a practice of international trade. However, since the mid-2000s, e-trade research articles and educational materials such as textbooks, research papers are being gradually reduced. Therefore the purpose of this study, from an oversea marketing point of view among the various e-trade fields, is to measure an education performance and an academic research scheme. And this study will suggest direction of improvement about research scheme and educational performance in the overseas marketing. According to the result, to establish the education and research scheme about SEM(Search Engine Marketing), SEO(Search Engine Optimization) and SNA(Social Network Analysis) which are introduced in the industry among the education and research field related the e-trade is urgent. And some subjects need a capstone-design reconcile theory and practice.

• Journal of Smart Tourism
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• v.3 no.3
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• pp.29-40
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• 2023

This research aims to understand the role of online reviews in the local search context by examining the effects of reviews on the representation of tourism businesses on local search platforms (LSPs). By simulating tourists' local searches for restaurants on three LSPs, namely Google, Bing, and Yelp, this study examines how different ranking results are generated across the platforms and how online reviews contribute to the differences. The findings suggest that online reviews are incorporated into LSPs as ranking factors and, thus, affect tourists' decision-making by influencing the information search results in the local search context. As one of the earliest studies on local search, this study discusses how the existing knowledge about the role of online reviews in tourists' decision-making needs to be reevaluated in mobile and more dynamic environments, and offers practical implications for tourism businesses' search engine marketing.