Due to the Covid-19 pandemic, the home-training app market is growing rapidly and numerous apps are entering the market. It is becoming more difficult for an app to secure the profitability. In this study, by analyzing actual user data of a reward-based home-training app, we propose a model that predicts cash-cow users of the app. Cash-cow users are the users who watch in-stream ads to watch training videos although they cannot earn any rewards by doing so. Thus, these users make profits for the app yet do not incur any costs. The results of this study show that the users who irregularly watch training videos are more likely to be cash-cow users than the users who regularly watch training videos. This result suggests that, paradoxically, for sustainable profitability, home-training apps may need to find a way to retain the users who watch training videos irregularly so that they can be satisfied with the service and continue use the apps.
Thanks to the remarkable success of Artificial Intelligence (A.I.) techniques, a new possibility for its application on the real-world problem has begun. One of the prominent applications is the bankruptcy prediction model as it is often used as a basic knowledge base for credit scoring models in the financial industry. As a result, there has been extensive research on how to improve the prediction accuracy of the model. However, despite its impressive performance, it is difficult to implement machine learning (ML)-based models due to its intrinsic trait of obscurity, especially when the field requires or values an explanation about the result obtained by the model. The financial domain is one of the areas where explanation matters to stakeholders such as domain experts and customers. In this paper, we propose a novel approach to incorporate financial domain knowledge into local rule generation to provide explanations for the bankruptcy prediction model at instance level. The result shows the proposed method successfully selects and classifies the extracted rules based on the feasibility and information they convey to the users.
Though there have been a lot of studies about online product review, the effects of highlighted reviewhave not been examined enough. Highlighted review is a type of review that the platform designer changes its size or position in order to highlight without any sponsorship or incentive. The main subject of this study is about how highlighted review type affects consumer's perception and behavior in online information acquisition. We collected data from 171 subjects to test hypotheses. Using three different types of screen captures, we compared three groups - general review group, positive highlighted review only group, and both positive and negative highlighted review group. As a result, disclosing both of positiveand negative highlighted review was perceived more useful than disclosing only positive highlighted review. However, correlation between highlighted review type and review skepticism was not statistically significant. The impacts of review usefulness and skepticism on platform credibility were statistically significant, and the correlation between platform credibility and usage intention was also significant. All of results is almost similar across two product types, search goods and experiential goods. This research provides practical implications to online shopping platform designers when they design review systems to make people use their platforms.
The purpose of this study was to analyze the effect of SNS marketing characteristics on hair shop image formation and visit intention in the hair beauty industry. SNS marketing is a strategy to carry out marketing activities through interaction with customers, information provision, information trust, and playfulness using modern social media platforms. It was intended to analyze how these characteristics of SNS marketing affect the formation of hair shop images and visit intention to customers in the hair beauty industry. For the study, a total of 307 customers with experience using hair-related SNS were surveyed. The questionnaire included items related to SNS marketing characteristics, hair shop images, and visit intention, and the collected data was statistically analyzed using SPSS 26.0. The results of the research problem were derived by applying analysis methods such as frequency analysis, factor analysis, reliability analysis, correlation analysis, simple regression analysis, multiple regression analysis, and mediated regression analysis. As a result of the study, it was found that information provision, information reliability, playfulness, and interaction, which are characteristics of SNS marketing, have a positive effect on the formation of hair shop images. In addition, it was confirmed that the hair shop image had a positive effect on the intention to visit. In addition, it was found that the hair shop image plays a mediating role between the SNS marketing characteristics and the intention to visit. This provides important insights that can improve image formation and customer visit intention in the hair beauty industry through SNS marketing.
Journal of the Korea Society of Computer and Information
/
v.29
no.4
/
pp.91-103
/
2024
This study conducted surveys and in-depth interviews to explore the perception of sports psychology counseling among athletes. The participants included a total of 8 individuals: 307 athletes surveyed, 4 athletes who had received counseling, and 4 who had not. The survey investigated athletes' perceptions and management of psychological training, the perceived necessity of seeking advice for everyday concerns, willingness to use and perceived need for sports psychology counseling, prior experiences, and pre-engagement considerations. According to the survey results, 69.1% of athletes recognized the importance of mental training, but only 33.2% actually underwent psychological training. Furthermore, while 67.8% expressed a desire to receive education on psychological training from professionals, only 19.9% reported having searched for related information. When asked about their willingness to pay for sports psychology counseling services, 55.7% expressed willingness. Reasons for wanting to receive counseling, reasons for not wanting to receive counseling, and preferences or considerations for counseling sessions were listed as well. In the in-depth interviews, participants were classified into those who had received counseling and those who had not, delving deeply into motivations for seeking counseling or reasons for not doing so, perceptions during counseling sessions, considerations, preferred types of counselors, and program preferences. Based on this research, discussions and recommendations were provided with the perspective of utilizing sports psychology counseling as foundational data for providing high-quality services to users.
This study aims to identify various service innovation patterns in the service industry and understand the main differences among them. We attempt to create a new typology of service innovation by analyzing its patterns based on the four major dimensions of service innovation (i.e., service concept, service delivery, customer interaction, and technology). We then investigate whether firms pursuing different service innovation patterns significantly differ from one another in terms of their performance (high and low performance). Based on empirical data collected from 198 Korean firms in the knowledge-intensive business service sector, four major clusters composed of different service innovation dimensions are identified. These four clusters can be interpreted as specific service innovation patterns, including "technology based high customer interaction," "high technology based high service delivery," "service delivery and high customer interaction-integrated," and "strongly balanced" innovators. High firm performance does not depend on the individual service innovation dimension but on the specific configurations of such service dimensions. Customer interaction also has an important role in achieving innovation success and improving firm performance, while technology has a key role in enhancing firm performance. This study sheds new light on service innovation research by developing a new typology of service innovation, identifying four major clusters as service innovation patterns, and exploring the relationship between service innovation patterns and firm performance.
This study analyzed the factors that affect acceptance of online direct marketing in agricultural companies. Empirical analysis was conducted using the research model based on the individual's technology acceptance model (TAM) and the information technology adoption models in organizations. These models have four dimensions: 1) technology characteristics, which include perceived usefulness and perceived ease of use of TAM 2) CEO characteristics, which including the innovativeness and IT capability of CEOs; 3) organizational readiness, which include financial, technological, and human resources capabilities and 4) environment and external pressure, which include government support and changes to the Internet environment. These concepts were empirically tested. A total of 209 valid data were collected through questionnaires and analyzed using confirmatory factor analysis and path analysis through the application of structural equation modeling. Results show that perceived usefulness, IT capability of CEOs, and changes to the Internet environment have significant effects on the adoption intention of online direct marketing. However, perceived ease of use, CEO innovativeness, government support, and the variables of organizational readiness dimension did not have significant effects on adoption intention. This study suggests practical implications for adoption of online direct marketing in agricultural companies.
Individuals often receive smishing campaigns (mobile phishing messages), which they treat as spam. Thus, firms should understand how their customers distinguish their promotion messages from smishing. However, only a few studies examined this important issue. The present study employs the elaboration likelihood model to develop research hypotheses on the relationship between message cue and message credibility. The message cue in this study is classified as content cue, which is found in the content of promotion messages, and as leakage cue, which is found in peripheral information in the message. Leakage cue includes orthography (inclusion of special characters)and an abbreviated link sent by a faithless sender. We also propose that contextualization has a moderating effect on the relationship between content cue and credibility. We conducted a survey experiment to examine the effect of message cues on message credibility in the context of respondents receiving discount coupons through mobile messages. The result of data analysis based on 166 responses suggests that leakage cue had a negative effect on message credibility. A message with defective content cue has a marginally negative effect on message credibility. In particular, defective content cue in a high-contextual message has a strong negative impact on message credibility. This effect was not observed in low-contextual messages. Moreover, message credibility is significantly low regardless of the degree of contextualization if there is a leakage cue in the message. Our findings suggest that mobile promotion messages should be customized for message receivers and should have no leakage cues.
Climate change has been intensifying drought frequency and severity. Such prolonged droughts reduce reservoir levels, thereby exacerbating drought impacts. While previous studies have focused on optimizing reservoir operations using historical data to mitigate these impacts, their scope is limited to analyzing past events, highlighting the need for predictive methods for future droughts. This research introduces a novel approach for predicting minimum inflow at the Seomjingang dam which has experienced significant droughts. This study utilized the Stochastic Analysis Modeling and Simulation (SAMS) 2007 to generate inflow sequences for the same period of observed inflow. Then we simulate reservoir operations to assess firm yield and predict minimum inflow through synthetic inflow analysis. Minimum inflow is defined as the inflow where firm yield is less than 95% of the synthetic inflow in many sequences during periods matching observed inflow. The results for each case indicated the firm yield for the minimum inflow is on average 9.44 m3/s, approximately 1.07 m3/s lower than the observed inflow's firm yield of 10.51 m3/s. The minimum inflow estimation can inform reservoir operation standards, facilitate multi-reservoir system reviews, and assess supplementary capabilities. Estimating minimum inflow emerges as an effective strategy for enhancing water supply reliability and mitigating shortages.
As Internet usage is becoming more common worldwide and smartphone become necessity in daily life, technologies and applications related to mobile Internet are developing rapidly. The results of the Internet usage patterns of consumers around the world imply that there are many potential new business opportunities for mobile Internet technologies and applications. The location-based service (LBS) is a service based on the location information of the mobile device. LBS has recently gotten much attention among many mobile applications and various LBSs are rapidly developing in numerous categories. However, even with the development of LBS related technologies and services, there is still a lack of empirical research on the intention to use LBS. The application of previous researches is limited because they focused on the effect of one particular factor and had not shown the direct relationship on the intention to use LBS. Therefore, this study presents a research model of factors that affect the intention to use and actual use of LBS whose market is expected to grow rapidly, and tested it by conducting a questionnaire survey of 330 users. The results of data analysis showed that service customization, service quality, and personal innovativeness have a positive effect on the intention to use LBS and the intention to use LBS has a positive effect on the actual use of LBS. These results implies that LBS providers can enhance the user's intention to use LBS by offering service customization through the provision of various LBSs based on users' needs, improving information service qualities such as accuracy, timeliness, sensitivity, and reliability, and encouraging personal innovativeness. However, privacy concerns in the context of LBS are not significantly affected by service customization and personal innovativeness and privacy concerns do not significantly affect the intention to use LBS. In fact, the information related to users' location collected by LBS is less sensitive when compared with the information that is used to perform financial transactions. Therefore, such outcomes on privacy concern are revealed. In addition, the advantages of using LBS are more important than the sensitivity of privacy protection to the users who use LBS than to the users who use information systems such as electronic commerce that involves financial transactions. Therefore, LBS are recommended to be treated differently from other information systems. This study is significant in the theoretical point of contribution that it proposed factors affecting the intention to use LBS in a multi-faceted perspective, proved the proposed research model empirically, brought new insights on LBS, and broadens understanding of the intention to use and actual use of LBS. Also, the empirical results of the customization of LBS affecting the user's intention to use the LBS suggest that the provision of customized LBS services based on the usage data analysis through utilizing technologies such as artificial intelligence can enhance the user's intention to use. In a practical point of view, the results of this study are expected to help LBS providers to develop a competitive strategy for responding to LBS users effectively and lead to the LBS market grows. We expect that there will be differences in using LBSs depending on some factors such as types of LBS, whether it is free of charge or not, privacy policies related to LBS, the levels of reliability related application and technology, the frequency of use, etc. Therefore, if we can make comparative studies with those factors, it will contribute to the development of the research areas of LBS. We hope this study can inspire many researchers and initiate many great researches in LBS fields.
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