• Journal of Distribution Science
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• v.14 no.4
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• pp.47-53
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• 2016

Purpose - The objective of this study is to investigate the dynamic relationships among Advertising Cost (AD), Newly Registered Users(NRU), and Buying Users(BU) of Social Network Game(SNG). SNG is getting pervasive mainly due to the rapid growth of mobile game and Social Network Service(SNS). It would be helpful for marketing researchers interested in SNG and related practitioners to understand the changes in AD, NRU, and BU with time as well as the effects on one another in mutual and dynamic way. Research Design, Data, and Methodology - Necessary data were collected from Social Network Game(SNG) company. AD, NRU, and BU are endogenous variables, but new event such as launching (event) and holidays(holiday) are exogenous dummy variables. Vector Auto regression (VAR) model is generally used to examine and capture the dynamic relationships among endogenous variables. VAR model can easily capture dynamic and endogenous relationships among time-series variables. Vector Auto regression with Exogenous variables(VARX) is a model in which exogenous variables are added to VAR. To investigate this study, VARX is applied. Result - By estimating the VARX model, the author finds that the past periods' NRU affect negatively and significantly the present AD, and past periods' BU have a positive and significant impact on the increase of AD. In addition, the author shows that the past periods' AD and BU have a positive and significant effect on the increase of NRU, and the past periods' AD affect positively and significantly BU. While the impact of AD on NRU happens after 3 or 4 days (carryover effect), that of AD on BU comes about within just 1 or 2 days (immediate effect). The effect of BU on NRU can be considered as word of mouth (WOM effect). Therefore, SNG companies can obtain not only the growth of revenue but also the increase of NRU by increasing BU. Through those results, the author can also find that there are significant interactions between endogenous variables. Conclusion - This study intends to investigate endogenous and dynamic relationships between AD, NRU, and BU. They also give managerial implications to practitioners for SNS and SNG firms. Through this study, it is found that there exist significant interactions and dynamic relationships between those three endogenous variables. The results of this study can have meaningful implications for practitioners and researchers of SNG. This research is unique in that it deals with "actual" field data and intend to find "actual" relationships among variables unlike other related existing studies which intend to investigate psychological factors affecting the intention of game usage and the intention of purchasing game items. This study is also meaningful by showing that the increase of BU can be a good strategy for "killing birds with one stone" (i.e., revenue growth and NRU increase). Although there are some limitations related with future research topics, this research contributes to the current research on SNG marketing in the above mentioned ways.

• Journal of Intelligence and Information Systems
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• v.21 no.2
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• pp.49-67
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• 2015

Recently, emerging the notion of big data and social media has led us to enter data's big bang. Social networking services are widely used by people around the world, and they have become a part of major communication tools for all ages. Over the last decade, as online social networking sites become increasingly popular, companies tend to focus on advanced social media analysis for their marketing strategies. In addition to social media analysis, companies are mainly concerned about propagating of negative opinions on social networking sites such as Facebook and Twitter, as well as e-commerce sites. The effect of online word of mouth (WOM) such as product rating, product review, and product recommendations is very influential, and negative opinions have significant impact on product sales. This trend has increased researchers' attention to a natural language processing, such as a sentiment analysis. A sentiment analysis, also refers to as an opinion mining, is a process of identifying the polarity of subjective information and has been applied to various research and practical fields. However, there are obstacles lies when Korean language (Hangul) is used in a natural language processing because it is an agglutinative language with rich morphology pose problems. Therefore, there is a lack of Korean natural language processing resources such as a sentiment lexicon, and this has resulted in significant limitations for researchers and practitioners who are considering sentiment analysis. Our study builds a Korean sentiment lexicon with collective intelligence, and provides API (Application Programming Interface) service to open and share a sentiment lexicon data with the public (www.openhangul.com). For the pre-processing, we have created a Korean lexicon database with over 517,178 words and classified them into sentiment and non-sentiment words. In order to classify them, we first identified stop words which often quite likely to play a negative role in sentiment analysis and excluded them from our sentiment scoring. In general, sentiment words are nouns, adjectives, verbs, adverbs as they have sentimental expressions such as positive, neutral, and negative. On the other hands, non-sentiment words are interjection, determiner, numeral, postposition, etc. as they generally have no sentimental expressions. To build a reliable sentiment lexicon, we have adopted a concept of collective intelligence as a model for crowdsourcing. In addition, a concept of folksonomy has been implemented in the process of taxonomy to help collective intelligence. In order to make up for an inherent weakness of folksonomy, we have adopted a majority rule by building a voting system. Participants, as voters were offered three voting options to choose from positivity, negativity, and neutrality, and the voting have been conducted on one of the largest social networking sites for college students in Korea. More than 35,000 votes have been made by college students in Korea, and we keep this voting system open by maintaining the project as a perpetual study. Besides, any change in the sentiment score of words can be an important observation because it enables us to keep track of temporal changes in Korean language as a natural language. Lastly, our study offers a RESTful, JSON based API service through a web platform to make easier support for users such as researchers, companies, and developers. Finally, our study makes important contributions to both research and practice. In terms of research, our Korean sentiment lexicon plays an important role as a resource for Korean natural language processing. In terms of practice, practitioners such as managers and marketers can implement sentiment analysis effectively by using Korean sentiment lexicon we built. Moreover, our study sheds new light on the value of folksonomy by combining collective intelligence, and we also expect to give a new direction and a new start to the development of Korean natural language processing.

• Asia Marketing Journal
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• v.14 no.1
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• pp.99-130
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• 2012

Service failure and a poor service recovery may lead loyal customers to try to aggressively punish the service firm. We use perceived betrayal and desire for vengeance as the key constructs to understand customer retaliation. Perceived betrayal is defined as a customer's belief that a firm has intentionally violated what is normative in the context of their relationship. And the desire for vengeance is defined as the retaliatory feelings that consumers feel toward a firm, such as the desire to exert harm on the firm. The perceived betrayal and the desire for vengeance are key antecedents of retaliatory behaviors such as vindictive complaining, negative WOM and third-party complaining for publicity. The empirical results suggest that betrayal is a key motivational factor that lead customers to restore fairness by making use of all means, including retaliation. We also find that relationship quality has effect on a customer's response to a failure in service recovery. As the levels of relationship increases, a violation of the proper fairness has a stronger effect on the sense of betrayal experienced by customers. Considerable research has investigated consumer responses to dissatisfaction. But our study examine the response of outraged and highly frustrated consumers. We focus on emotional and behavioral processes that have not been covered by previous dissatisfaction researches and which are unique to outraged consumers caused by extremely dissatisfied purchase experience. It has recently been pointed out by various mass media that the customers not only have positive effects on the company performance but also put the company in crisis. It has often been reported that one customer's dissatisfaction, for example, never ends as it is, and it tends to grow for retaliating upon the company, depending on the level of seriousness of the dissatisfaction. This sometimes leads to a lawsuit against the company. Our study focuses on the customers' emotional and behavioral responses induced by their extreme dissatisfactions. We divided the customer groups into the customers with high relationship quality and the customers with low relationship quality, and the difference between two groups is examined. The objective of this study is to comprehend the causal relationship between the feeling of betrayal caused by the service failure and the retaliatory behavior triggered by the desire of revenge. Our study is divided into three parts. First, a causal relationship between perceived unfairness and the perceived betrayal and desire for revenge. Second, the effect of the perceived betrayal and desire for revenge on the retaliatory behavior is investigated. Finally, the moderating role of relationship quality in the causal relationship between the unfairness in service recovery and the perceived betrayal is analyzed. This study finds the following empirical results. The distributive unfairness, procedural unfairness and interactional unfairness had significant effects on the perceived betrayal. Especially, the perceived distributive unfairness results in the highest perceived betrayal. When the service company does not provide customers proper and sufficient compensation for the failure, they feel the strong sense of betrayal. And in the causal relationship between the perceived betrayal, desire for revenge and retaliatory behavior, the perceived betrayal has significant effects on e desire for revenge. In addition desire for revenge has significant effects on negative word of mouth, retaliatory complaining behavior and publicity of complaints through third group. Therefore the perceived unfairness has effects on retaliatory behavior through the mediation of the perceived betrayal and desire for revenge. Finally the moderating role of relationship quality was examined in the relationship between the unfairness and perceived betrayal. If the customers experienced the perceived unfairness in the process of service recovery, the customers with high relationship quality feel the stronger perceived betrayal than the customers with low relationship quality do. When they experience the double service failure, the customer group with high relationship quality accumulating the sense of trust feel the more perceived betrayal than the customer with low relationship quality who do not have strong trust. The contribution of this study is to find the effect of the service failure on the retaliatory behavior with the moderating roles of relationship quality. The dimensions of unfairness in service recovery is found to have differential effects on the perceived betrayal, desire for revenge. And these differential effect is moderated by the level of relationship quality.