• The Journal of Asian Finance, Economics and Business
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• v.7 no.12
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• pp.951-958
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• 2020

This study examines the relationship between social media marketing and brand loyalty through brand trust. Respondents were drawn from customers of McDonald's, Malang City, East Java Province, Indonesia. For this study, 130 questionnaires were distributed and data were analyzed using the Structure Equation Model (SEM) version 22 of the AMOS (Analysis of Moment Structure) application. The results showed that social media marketing had an impact on increasing McDonald's brand trust and brand loyalty. Brand trust influences brand loyalty and brand trust can mediate the influence of social media marketing on McDonald's brand loyalty. The findings prove that brand trust can mediate the effect of social media marketing on customer loyalty to McDonald's brand. These results can be explained by the fact that marketing strategies through social media marketing, such as making it easy for customers to get information related to McDonald's on social media, can contribute to customer trust and that trust is formed because McDonald's always pays attention to the quality of the products offered. Brand trust can mediate the influence of social media marketing on customer loyalty to McDonald's brand. This means that information related to McDonald's on social media is proportional to the quality of the product offered.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.25 no.3
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• pp.1-8
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• 2017

As many people all over the world increasingly take more time in exchanging with other people or acquiring information on the internet, use of social media becomes a part of their daily lives. A lot of changes of consumer culture, which have been occurring through social media, have significant effects on corporate marketing activities. Since social media's importance to airlines has been continuously increased, this study attempts to examine effects of passengers' uses of social media, who plan to select an airline, on dependence on reliance of electronic word-of mouth(EWOM) and EWOM acceptance. To this end, a questionnaire survey of passengers who use airlines and the airline's social media was conducted, and then effective data of 302 copies were analyzed by using the structural equation modeling. The findings show that social media use intensity has a significant effect on Acceptance of EWOM via reliance of EWOM, while a direct effect of social media use intensity on Acceptance of EWOM is not significant. From this study, it is found that control and management of social media and only EWOM are effective tools for marketing of airline businesses, suggesting that innovative strategies are required to preemptively cope with changes in consumers' behaviors and markets, which continue to evolve.

• Knowledge Management Research
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• v.22 no.4
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• pp.135-155
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• 2021

With the emergence of various types of social media and the diversification of their roles, it has become essential for marketers to understand how different types of social media influence consumers' purchase decisions differently and derive more detailed strategies by social media types. This study classifies social media into two types-expression-focused social media and relationship-focused social media-and investigates the relationship between consumer purchases and social media mentions by type. Using the Seoul bike-sharing data and time-series data for social media mentions, we apply the VAR model with Exogenous Variables (VARX). We find that the increase of product mentions in expression-focused social media positively affects both the number of new customers (customer acquisition) and the number of shared bike rentals, while that in relationship-focused social media negatively affects the number of new customers only. In addition, as new customers increase, the product mentions in both types of social media increase. On the other hand, the number of bike rentals has no significant effect in increasing social media mentions regardless of type. This study contributes to the social media and sharing economy literature and provides managerial implications for establishing sophisticated social media marketing in bike-sharing businesses.

• Journal of Smart Tourism
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• v.1 no.3
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• pp.21-29
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• 2021

This study explored the relationship between post types and linguistic characteristics in marketer-generated content and social media engagement to find the optimized content to enhance social media engagement level. Post data of 23,588 marketer-generated content were collected from 50 states' destination marketing organization Facebook pages in the United States. The collected data were analyzed by employing social media analytics, linguistic analysis, multivariate analysis of variance, and discriminant analysis. The results showed that there are significant differences in both engagement indicators and linguistic scores among the three post types. Based on research findings, this research not only provided researchers with theoretical implications but also suggested practitioners the most effective content designs for travel destination marketing in Facebook.

• Journal of Information Technology Applications and Management
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• v.27 no.6
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• pp.117-139
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• 2020

This research analyzes the factors that affect the consumers' participation of the internet-only banks, and suggests effective financial sales strategies and methods to attract more users. Through prior research review and interviews with experts, the factors affecting the consumers to sign up for the internet banks are identified. The actual user data from the internet banks are used for the analysis, providing more systematic and credible results. The research shows that social media buzz positively affects the user growth, proving Granger Causality relation of increasing social media buzz on K Bank increases K Bank users. The research also shows that marketing activities noticeably impacts K Bank's positive user growth. On the other hand, the event of Kakao Bank's grand opening shows negative effect. The results from the research validates the need for periodical monitoring process of social media buzz. Moreover, the research proves that the integrated analysis of social media buzz and marketing effect is also essential.

• Asia-Pacific Journal of Business
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• v.12 no.2
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• pp.161-174
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• 2021

Purpose - The purpose of this study was to examine the recent popular consumption trend, the hocance phenomenon, using social media big data. The study intended to present practical directions and marketing measures for the recovery and growth of the hotel industry after COVID-19 pandemic. Design/methodology/approach - Big data analysis has been used in various fields, and in this study, it was used to understand the hocance phenomenon. For three years from January 1, 2018 to December 31, 2020, we collected text data including the keyword 'hocance' from the blog and cafe of NAVER and Daum. TEXTOM and UCINET 6 were used to collect and analyze the data. Findings - According to the results of analysis, the words such as 'hocance', 'hotel', 'Seoul', 'travel', 'swimming pool', 'Incheon', 'breakfast', 'child' and 'friend' were identified with high frequency. The results of CONCOR analysis showed similar results in all three years. It has been confirmed that 'swimming pool', 'breakfast', 'child' and 'friend' are important when deciding on the hocance package. Research implications or Originality - The study was differentiated in that it used social media big data instead of traditional research methods. Furthermore, it reflected social phenomena as a consumption trend so there was practical value in establishing marketing strategies for the tourism and hotel industry.

• Smart Media Journal
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• v.2 no.2
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• pp.20-27
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• 2013

The concept of social media is top of the agenda for many business executives and decision makers, as well as consultants try to identify ways where companies can make profitable use of applications such as Netflix, Flixster. The social media is playing an increasingly important role as the information sources for customers making product choices etc. With the flourish of Web 2.0 technology, customer reviews are becoming more and more useful and important information resources for people to save their time and energy on purchasing products that they want. This paper proposes the Bayesian Probabilistic Classification algorithm to mine the social media review, and evaluates it by different splits and cross validation mechanism from the real data set. The explored study experimental results show the robustness and effectiveness of proposed approach for mining the social media review.

• Journal of Korea Society of Industrial Information Systems
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• v.17 no.7
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• pp.149-158
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• 2012

Much attention is being paid to social media because of their potentials to draw collective intelligence. In this context does this study attempt to draw some implications of social media as knowledge creation platform and suggest a conceptual framework of social media management. Information sharing among the public through social media literally produces profound influence throughout the society and thus not only business firms but all levels of public institutions, including government are seeking to take its advantage for various purposes such as public relations, crowd sourcing, etc. Especially considering that social media open the possibility of social knowledge creation platform in the Big Data era, this study is perhaps able to contribute to further development of social media management model together with a series of measuring indexes.

• International Journal of Contents
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• v.13 no.1
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• pp.31-37
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• 2017

Using the network analysis method, this study investigates the communication structure of Open Data on the Twitter sphere. It addresses the communication path by mapping influential activities and comparing the contents of tweets about Open Data. In the years 2015 and 2016, the NodeXL software was applied to collect tweets from the Twitter network, containing the term "opendata". The structural patterns of social media communication were analyzed through several network characteristics. The results indicate that the most common activities on the Twitter network are related to the subjects such as new applications and new technologies in Open Data. The study is the first to focus on the structural and informational pattern of Open Data based on social network analysis and content analysis. It will help researchers, activists, and policy-makers to come up with a major realization of the pattern of Open Data through Twitter.

• Asia pacific journal of information systems
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• v.26 no.1
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• pp.124-142
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• 2016

Companies operating in social network platforms continue to improve and expand their marketing techniques. This study examines the practice of "gating", which involves virtual barriers between social network users and company content. Gates demand mandatory user endorsements, in the form of a Facebook "Likes", Twitter "retweets" etc., to gain access to company content, such as coupons and rewards,. Gating practices demand a mandatory endorsement before any content consumption takes place. Thus, while user endorsements are assumed to arise voluntarily from trusted known sources, gating practices would appear to violate this assumption. However, whether this violation lessens the effectiveness of gating practices still requires empirical validation. We investigate this question through the use of a unique panel data set that includes data on "like" endorsements obtained from a number of real-world Facebook business pages. Results of the study show that gating practices are effective for endorsement solicitation; however, gates may interfere with more traditional marketing activities.