• Title/Summary/Keyword: Game Money

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A study on the regulation of negative emotions in the Ultimatum Game: Comparison between Korean older and young adults (최후통첩게임 상황에서의 부정정서 조절에 관한 연구: 한국 노인과 청년 비교)

  • Jeon, Dasom;Ghim, Hei-Rhee;Hur, Ahjeong;Park, Sunwoo;Kim, Moongeol
    • 한국노년학
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    • v.39 no.4
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    • pp.921-939
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    • 2019
  • According to the social selectivity theory (SST), despite the disadvantages of life conditions, older adults experience less negative emotions because they regulate their emotions by avoiding negative stimuli or situations. Based on the SST, this study attempted to find out whether older adults are better able to regulate negative emotions than young adults in the Ultimatum Game (UG). In an UG, if the proposer proposes to distribute a portion of the money to the responder, the responder must decide whether to accept or reject it. If the responder accepts the offer, the proposer and the responder can each have their own share as proposed, but if s/he reject the offer, both get nothing. Thus, if the responder considers own economic benefits, it is a more reasonable decision to accept the unfair offer no matter how low, than to reject it. To accept an unfair offer, the responder must regulate the anger felt at the proposer. If older adults could regulate anger better than young adults, they would be less likely to reject the unfair offer than young adults. Fifty-seven olders and 60 university students participated in this study. Both the older and young adults accepted most of the fair offers. In contrast, older adults accepted unfair offers at a significantly higher rate than young adults. In addition, compared to young adults, older adults reported anger less frequently at the unfair offers. Accepting unfair offers was negatively correlated with anger report, but positively correlated with the emotion regulation measured by ERQ. The ERQ score was negatively correlated with anger report. Emotion regulation partially mediated the relationship between the age groups and acceptance of unfair offers. The present results showed that older adults accepted the unfair offers at a higher rate than young adults because they could regulate the negative emotions felt at the unfair offer better than young adults. This study provided new evidence for the claim that improving emotional regulation is a major developmental change in adulthood.

A Study on the Effects of User Participation on Stickiness and Continued Use on Internet Community (인터넷 커뮤니티에서 사용자 참여가 밀착도와 지속적 이용의도에 미치는 영향)

  • Ko, Mi-Hyun;Kwon, Sun-Dong
    • Asia pacific journal of information systems
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    • v.18 no.2
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    • pp.41-72
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    • 2008
  • The purpose of this study is the investigation of the effects of user participation, network effect, social influence, and usefulness on stickiness and continued use on Internet communities. In this research, stickiness refers to repeat visit and visit duration to an Internet community. Continued use means the willingness to continue to use an Internet community in the future. Internet community-based companies can earn money through selling the digital contents such as game, music, and avatar, advertizing on internet site, or offering an affiliate marketing. For such money making, stickiness and continued use of Internet users is much more important than the number of Internet users. We tried to answer following three questions. Fist, what is the effects of user participation on stickiness and continued use on Internet communities? Second, by what is user participation formed? Third, are network effect, social influence, and usefulness that was significant at prior research about technology acceptance model(TAM) still significant on internet communities? In this study, user participation, network effect, social influence, and usefulness are independent variables, stickiness is mediating variable, and continued use is dependent variable. Among independent variables, we are focused on user participation. User participation means that Internet user participates in the development of Internet community site (called mini-hompy or blog in Korea). User participation was studied from 1970 to 1997 at the research area of information system. But since 1997 when Internet started to spread to the public, user participation has hardly been studied. Given the importance of user participation at the success of Internet-based companies, it is very meaningful to study the research topic of user participation. To test the proposed model, we used a data set generated from the survey. The survey instrument was designed on the basis of a comprehensive literature review and interviews of experts, and was refined through several rounds of pretests, revisions, and pilot tests. The respondents of survey were the undergraduates and the graduate students who mainly used Internet communities. Data analysis was conducted using 217 respondents(response rate, 97.7 percent). We used structural equation modeling(SEM) implemented in partial least square(PLS). We chose PLS for two reason. First, our model has formative constructs. PLS uses components-based algorithm and can estimated formative constructs. Second, PLS is more appropriate when the research model is in an early stage of development. A review of the literature suggests that empirical tests of user participation is still sparse. The test of model was executed in the order of three research questions. First user participation had the direct effects on stickiness(${\beta}$=0.150, p<0.01) and continued use (${\beta}$=0.119, p<0.05). And user participation, as a partial mediation model, had a indirect effect on continued use mediated through stickiness (${\beta}$=0.007, p<0.05). Second, optional participation and prosuming participation significantly formed user participation. Optional participation, with a path magnitude as high as 0.986 (p<0.001), is a key determinant for the strength of user participation. Third, Network effect (${\beta}$=0.236, p<0.001). social influence (${\beta}$=0.135, p<0.05), and usefulness (${\beta}$=0.343, p<0.001) had directly significant impacts on stickiness. But network effect and social influence, as a full mediation model, had both indirectly significant impacts on continued use mediated through stickiness (${\beta}$=0.11, p<0.001, and ${\beta}$=0.063, p<0.05, respectively). Compared with this result, usefulness, as a partial mediation model, had a direct impact on continued use and a indirect impact on continued use mediated through stickiness. This study has three contributions. First this is the first empirical study showing that user participation is the significant driver of continued use. The researchers of information system have hardly studies user participation since late 1990s. And the researchers of marketing have studied a few lately. Second, this study enhanced the understanding of user participation. Up to recently, user participation has been studied from the bipolar viewpoint of participation v.s non-participation. Also, even the study on participation has been studied from the point of limited optional participation. But, this study proved the existence of prosuming participation to design and produce products or services, besides optional participation. And this study empirically proved that optional participation and prosuming participation were the key determinant for user participation. Third, our study compliments traditional studies of TAM. According prior literature about of TAM, the constructs of network effect, social influence, and usefulness had effects on the technology adoption. This study proved that these constructs still are significant on Internet communities.

An exploration of tour skill factors influential to game results of LPGA players (LPGA 선수들의 시즌성적에 영향을 미치는 경기 기술요인 탐색)

  • Son, Seung Bum;Lee, Chang Jin
    • Journal of the Korean Data and Information Science Society
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    • v.24 no.2
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    • pp.369-377
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    • 2013
  • The purpose of this study was to explore which factors mostly influenced players' tour results employing tour skill factors provided by LPGA. For this study, Top 10 LPGA players' stats during 9 years (2004 2012) were used. As matter of fact, 10 variables were used like average score, top 10 finish, average putt, average birdies, average eagles, driving distance, driving accuracy, greens in regulation, sand saves, putts per GIR. and prize money earning. Stepwise multiple regression was conducted using SPSS win 20.0. Results indicated that the most influential tour skill factor to 9 seasons' results was average score, second influential factor was average putt, and the third factor was driving distance, and then top 10 finish was the fourth. Also on a year on year basis, 2004 was average score, 2005 was GIR., 2006 was average eagles, 2007 was top 10 finish, 2008 was average score, 2009 was average putt, 2010 were average score, GIR. and putt per GIR, 2011 was average birdies and 2012 was putt per GIR.

Convergence Implementing Emotion Prediction Neural Network Based on Heart Rate Variability (HRV) (심박변이도를 이용한 인공신경망 기반 감정예측 모형에 관한 융복합 연구)

  • Park, Sung Soo;Lee, Kun Chang
    • Journal of the Korea Convergence Society
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    • v.9 no.5
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    • pp.33-41
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    • 2018
  • The purpose of this study is to develop more accurate and robust emotion prediction neural network (EPNN) model by combining heart rate variability (HRV) and neural network. For the sake of improving the prediction performance more reliably, the proposed EPNN model is based on various types of activation functions like hyperbolic tangent, linear, and Gaussian functions, all of which are embedded in hidden nodes to improve its performance. In order to verify the validity of the proposed EPNN model, a number of HRV metrics were calculated from 20 valid and qualified participants whose emotions were induced by using money game. To add more rigor to the experiment, the participants' valence and arousal were checked and used as output node of the EPNN. The experiment results reveal that the F-Measure for Valence and Arousal is 80% and 95%, respectively, proving that the EPNN yields very robust and well-balanced performance. The EPNN performance was compared with competing models like neural network, logistic regression, support vector machine, and random forest. The EPNN was more accurate and reliable than those of the competing models. The results of this study can be effectively applied to many types of wearable computing devices when ubiquitous digital health environment becomes feasible and permeating into our everyday lives.