• Journal of Service Research and Studies
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• v.13 no.1
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• pp.48-62
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• 2023

As seen in the recent K-pop craze, the size and influence of the Korean music industry is growing even bigger. At least 6,000 songs are released a year in the Korean music market, but not many can be said to have been successful. Many studies and attempts are being made to identify the factors that make the hit music. Commercial factors such as media exposure and promotion as well as the quality of music play an important role in the commercial success of music. Recently, there have been many marketing campaigns using Internet memes in the pop music industry, and Internet memes are activities or trends that spread in various forms, such as images and videos, as cultural units that spread among people. Depending on the Internet environment and the characteristics of digital communication, contents are expanded and reproduced in the form of various memes, which causes a greater response to consumers. Previously, the phenomenon of Internet memes has occurred naturally, but artists who are aware of the marketing effects have recently used it as an element of marketing. In this paper, the mediated effect of Internet memes in relation to the success factors of popular music was analyzed, and a prediction model reflecting them was proposed. As a result of the analysis, the factors with the mediated effect of 'cover effect' and 'challenge effect' were the same. Among the internal success factors, there were mediated effects in "Singer Recognition," the genres of "POP, Dance, Ballad, Trot and Electronica," and among the external success factors, mediated effects in "Planning Company Capacity," "The Number of Music Broadcasting Programs," and "The Number of News Articles." Predictive models reflecting cover effects and challenge effects showed F1-score at 0.6889 and 0.7692, respectively. This study is meaningful in that it has collected and analyzed actual chart data and presented commercial directions that can be used in practice, and found that there are many success factors of popular music and the mediating effects of Internet memes.

• Korean Journal of Remote Sensing
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• v.40 no.4
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• pp.387-396
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• 2024

Most very high-resolution (VHR) satellite images provide rational polynomial coefficients (RPC) data to facilitate the transformation between ground coordinates and image coordinates. However, initial RPC often contains geometric errors, necessitating correction through matching with ground control points (GCPs). A GCP chip is a small image patch extracted from an orthorectified image together with height information of the center point, which can be directly used for geometric correction. Many studies have focused on area-based matching methods to accurately align GCP chips with VHR satellite images. In cases with seasonal differences or changed areas, edge-based algorithms are often used for matching due to the difficulty of relying solely on pixel values. However, traditional edge extraction algorithms,such as canny edge detectors, require appropriate threshold settings tailored to the spectral characteristics of satellite images. Therefore, this study utilizes deep learning-based edge information that is insensitive to the regional characteristics of satellite images for matching. Specifically,we use a pretrained pixel difference network (PiDiNet) to generate the edge maps for both satellite images and GCP chips. These edge maps are then used as input for normalized cross-correlation (NCC) and relative edge cross-correlation (RECC) to identify the peak points with the highest correlation between the two edge maps. To remove mismatched pairs and thus obtain the bias-compensated RPC, we iteratively apply the data snooping. Finally, we compare the results qualitatively and quantitatively with those obtained from traditional NCC and RECC methods. The PiDiNet network approach achieved high matching accuracy with root mean square error (RMSE) values ranging from 0.3 to 0.9 pixels. However, the PiDiNet-generated edges were thicker compared to those from the canny method, leading to slightly lower registration accuracy in some images. Nevertheless, PiDiNet consistently produced characteristic edge information, allowing for successful matching even in challenging regions. This study demonstrates that improving the robustness of edge-based registration methods can facilitate effective registration across diverse regions.

• Journal of Intelligence and Information Systems
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• v.25 no.4
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• pp.1-33
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• 2019

The small and medium sized enterprises (hereinafter SMEs) are already at a competitive disadvantaged when compared to large companies with more abundant resources. Manufacturing SMEs not only need a lot of information needed for new product development for sustainable growth and survival, but also seek networking to overcome the limitations of resources, but they are faced with limitations due to their size limitations. In a new era in which connectivity increases the complexity and uncertainty of the business environment, SMEs are increasingly urged to find information and solve networking problems. In order to solve these problems, the government funded research institutes plays an important role and duty to solve the information asymmetry problem of SMEs. The purpose of this study is to identify the differentiating characteristics of SMEs that utilize the public information support infrastructure provided by SMEs to enhance the innovation capacity of SMEs, and how they contribute to corporate performance. We argue that we need an infrastructure for providing information support to SMEs as part of this effort to strengthen of the role of government funded institutions; in this study, we specifically identify the target of such a policy and furthermore empirically demonstrate the effects of such policy-based efforts. Our goal is to help establish the strategies for building the information supporting infrastructure. To achieve this purpose, we first classified the characteristics of SMEs that have been found to utilize the information supporting infrastructure provided by government funded institutions. This allows us to verify whether selection bias appears in the analyzed group, which helps us clarify the interpretative limits of our study results. Next, we performed mediator and moderator effect analysis for multiple variables to analyze the process through which the use of information supporting infrastructure led to an improvement in external networking capabilities and resulted in enhancing product competitiveness. This analysis helps identify the key factors we should focus on when offering indirect support to SMEs through the information supporting infrastructure, which in turn helps us more efficiently manage research related to SME supporting policies implemented by government funded institutions. The results of this study showed the following. First, SMEs that used the information supporting infrastructure were found to have a significant difference in size in comparison to domestic R&D SMEs, but on the other hand, there was no significant difference in the cluster analysis that considered various variables. Based on these findings, we confirmed that SMEs that use the information supporting infrastructure are superior in size, and had a relatively higher distribution of companies that transact to a greater degree with large companies, when compared to the SMEs composing the general group of SMEs. Also, we found that companies that already receive support from the information infrastructure have a high concentration of companies that need collaboration with government funded institution. Secondly, among the SMEs that use the information supporting infrastructure, we found that increasing external networking capabilities contributed to enhancing product competitiveness, and while this was no the effect of direct assistance, we also found that indirect contributions were made by increasing the open marketing capabilities: in other words, this was the result of an indirect-only mediator effect. Also, the number of times the company received additional support in this process through mentoring related to information utilization was found to have a mediated moderator effect on improving external networking capabilities and in turn strengthening product competitiveness. The results of this study provide several insights that will help establish policies. KISTI's information support infrastructure may lead to the conclusion that marketing is already well underway, but it intentionally supports groups that enable to achieve good performance. As a result, the government should provide clear priorities whether to support the companies in the underdevelopment or to aid better performance. Through our research, we have identified how public information infrastructure contributes to product competitiveness. Here, we can draw some policy implications. First, the public information support infrastructure should have the capability to enhance the ability to interact with or to find the expert that provides required information. Second, if the utilization of public information support (online) infrastructure is effective, it is not necessary to continuously provide informational mentoring, which is a parallel offline support. Rather, offline support such as mentoring should be used as an appropriate device for abnormal symptom monitoring. Third, it is required that SMEs should improve their ability to utilize, because the effect of enhancing networking capacity through public information support infrastructure and enhancing product competitiveness through such infrastructure appears in most types of companies rather than in specific SMEs.

• Asia Marketing Journal
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• v.14 no.2
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• pp.39-63
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• 2012

Previous studies of reward programs have generally focused on designing the best programs for consumers and suggested that consumers' perception of the value of reward programs can vary according to the type of reward program (e.g., hedonic vs. utilitarian and direct vs. indirect) and its timing (e.g., immediate vs. delayed). These studies have typically assumed that consumers' preference for reward programs has a positive effect on brand loyalty. However, Dowling and Uncles (1997) pointed out that this preference does not necessarily foster brand loyalty. In this regard, the present study verifies this assumption by examining the effects of consumers' perception of the value of reward programs on their brand loyalty. Although reward programs are widely used by online shopping malls, most studies have examined the conditions under which consumers are most likely to value loyalty programs in the context of offline shopping. In the context of online shopping, however, consumers' preferences may have little effect on their brand loyalty because they have more opportunities for comparing diverse reward programs offered by many online shopping malls. That is, in online shopping, finding attractive reward programs may require little effort on the part of consumers, who are likely to switch to other online shopping malls. Accordingly, this study empirically examines whether consumers' perception of the value of reward programs influences their brand loyalty in the context of online shopping. Meanwhile, consumers seek utilitarian and/or hedonic value from their online shopping activity(Jones et al., 2006; Barbin et al., 1994). They visit online shopping malls to buy something necessary (utilitarian value) and/or enjoy the process of shopping itself (hedonic value). In this sense, reward programs may reinforce utilitarian as well as hedonic value, and their effect may vary according to the type of reward (utilitarian vs. hedonic). According to Chaudhuri and Holbrook (2001), consumers' perception of the value of a brand can influence their brand loyalty through brand trust and affect. Utilitarian value influences brand loyalty through brand trust, whereas hedonic value influences it through brand affect. This indicates that the effect of this perception on brand trust or affect may be moderated by the type of reward program. Specifically, this perception may have a greater effect on brand trust for utilitarian reward programs than for hedonic ones, whereas the opposite may be true for brand affect. Given the above discussion, the present study is conducted with three objectives in order to provide practical implications for online shopping malls to strategically use reward program for establishing profitable relationship with customers. First, the present study examines whether reward programs can be an effective marketing tool for increasing brand loyalty in the context of online shopping. Second, it investigates the paths through which consumers' perception of the value of reward programs influences their brand loyalty. Third, it analyzes the effects of this perception on brand trust and affect by considering the type of reward program as a moderator. This study suggests and empirically analyzes a new research model for examining how consumers' perception of the value of reward programs influences their brand loyalty in the context of online shopping. The model postulates the following 10 hypotheses about the structural relationships between five constructs: (H1) Consumers' perception of the value of reward programs has a positive effect on their program loyalty; (H2) Program loyalty has a positive effect on brand loyalty; (H3) Consumers' perception of the value of reward programs has a positive effect on their brand trust; (H4) Consumers' perception of the value of reward programs has a positive effect on their brand affect; (H5) Brand trust has a positive effect on program loyalty; (H6) Brand affect has a positive effect on program loyalty; (H7) Brand trust has a positive effect on brand loyalty; (H8) Brand affect has a positive effect on brand loyalty; (H9) Consumers' perception of the value of reward programs is more likely to influence their brand trust for utilitarian reward programs than for hedonic ones; and (H10) Consumers' perception of the value of reward programs is more likely to influence their brand affect for hedonic reward programs than for utilitarian ones. To test the hypotheses, we considered a sample of 220 undergraduate students in Korea (male:113). We randomly assigned these participants to one of two groups based on the type of reward program (utilitarian: transportation card, hedonic: movie ticket). We instructed the participants to imagine that they were offered these reward programs while visiting an online shopping mall. We then asked them to answer some questions about their perception of the value of the reward programs, program loyalty, brand loyalty, brand trust, and brand affect, in that order. We also asked some questions about their demographic backgrounds and then debriefed them. We employed the structural equation modeling (SEM) method with AMOS 18.0. The results provide support for some hypotheses (H1, H3, H4, H7, H8, and H9) while providing no support for others (H2, H5, H6, H10) (see Figure 1). Noteworthy is that the path proposed by previous studies, "value perception → program loyalty → brand loyalty," was not significant in the context of online shopping, whereas this study's proposed path, "value perception → brand trust/brand affect → brand loyalty," was significant. In addition, the results indicate that the type of reward program moderated the relationship between consumers' value perception and brand trust but not the relationship between their value perception and brand affect. These results have some important implications. First, this study is one of the first to examine how consumers' perception of the value of reward programs influences their brand loyalty in the context of online shopping. In particular, the results indicate that the proposed path, "value perception → brand trust/brand affect → brand loyalty," can better explain the effects of reward programs on brand loyalty than existing paths. Furthermore, these results suggest that online shopping malls should place greater emphasis on the type of reward program when devising reward programs. To foster brand loyalty, they should reinforce the type of shopping value that consumers emphasize by providing them with appropriate reward programs. If consumers prefer utilitarian value to hedonic value, then online shopping malls should offer utilitarian reward programs and vice versa.