• Journal of Intelligence and Information Systems
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• v.29 no.3
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• pp.145-165
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• 2023

Recommendation system plays a significant role on relieving difficulties of selecting information among rapidly increasing amount of information caused by the development of the Internet and on efficiently displaying information that fits individual personal interest. In particular, without the help of recommendation system, E-commerce and OTT companies cannot overcome the long-tail phenomenon, a phenomenon in which only popular products are consumed, as the number of products and contents are rapidly increasing. Therefore, the research on recommendation systems is being actively conducted to overcome the phenomenon and to provide information or contents that are aligned with users' individual interests, in order to induce customers to consume various products or contents. Usually, collaborative filtering which utilizes users' historical behavioral data shows better performance than contents-based filtering which utilizes users' preferred contents. However, collaborative filtering can suffer from cold-start problem which occurs when there is lack of users' historical behavioral data. In this paper, hybrid music recommendation system, which can solve cold-start problem, is proposed based on the playlist data of Melon music streaming service that is given by Kakao Arena for music playlist continuation competition. The goal of this research is to use music tracks, that are included in the playlists, and metadata of music tracks and playlists in order to predict other music tracks when the half or whole of the tracks are masked. Therefore, two different recommendation procedures were conducted depending on the two different situations. When music tracks are included in the playlist, LightFM is used in order to utilize the music track list of the playlists and metadata of each music tracks. Then, the result of Item2Vec model, which uses vector embeddings of music tracks, tags and titles for recommendation, is combined with the result of LightFM model to create final recommendation list. When there are no music tracks available in the playlists but only playlists' tags and titles are available, recommendation was made by finding similar playlists based on playlists vectors which was made by the aggregation of FastText pre-trained embedding vectors of tags and titles of each playlists. As a result, not only cold-start problem can be resolved, but also achieved better performance than ALS, BPR and Item2Vec by using the metadata of both music tracks and playlists. In addition, it was found that the LightFM model, which uses only artist information as an item feature, shows the best performance compared to other LightFM models which use other item features of music tracks.

• Journal of Korean Society of Transportation
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• v.18 no.4
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• pp.51-62
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• 2000

The objective of this study was to reevaluate current Korean design values for lane width widenings on horizontal currie sections and to develop a new method for derivation of design values based on low-speed offtracking. For this purpose, earlier research were reviewed and necessary equations were derived. Also, the method for derivation of widening values of Korea was compared with that for other countries. The result showed that present Korean method could not consider the variation of lane widths and design speeds of roads. In this Paper, to solve such problems, the new concept of widening was developed. That is the current concept of widening which concerns only the dimension of vehicles and radius of curves was replaced by a new concept that lane width widenings on horizontal curve sections is the difference between the width required on curries and tangents. The width required on a curve consists of the swept Path of a vehicle, lateral clearance, and additional allowance. The width of a tangent is calculated by multiplying lane width by the number of lanes The result of applying new concept shows that the values derived from new concept are higher than current design values for curries have same radius. This study was based only on low-speed offtracking. Therefor, it is recommended that further studies which consider the superelevation and high-speed effect on offtracking be made to derive more accurate widening values .

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.14 no.4
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• pp.199-209
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• 2019

The importance of business strategy for successful social media engagement has quickly increased as more businesses engage in social media. The importance is even greater for startup companies because startup companies are genuinely new to business, and they need to increase their presence in the market, and quickly access future customers. The objective of this paper lies in exploring key indicators of social media engagements by selected startup companies. The key indicators include two aspects of social media usages by the companies: i) overall social media activities, and ii) properties of network structure of the information flow platform provided by social media service. To better assess and evaluate the key indicators of social media usages by startup companies, the indicators will be compared with those of selected large established companies. Twitter is selected as a social media service for the analysis of this paper, and using Twitter REST API, data regarding the key indicators of overall Twitter activities and the Twitter follower-network of each company in the sample are collected. Then, the data are analyzed using social network analysis and hierarchical clustering analysis to examine the characteristics of the follower-network structures and to compare the characteristics between startup companies and established companies. The results show that most indicators are significantly different across startup companies and established companies. One key interesting finding is that the startup companies have proportionally more influencers in their follower-networks than the established companies have. Another interesting finding is that the follower-networks of startup companies in the sample have higher modularity and higher transitivity, suggesting that the startup companies tend to have a proportionally larger number of communities of users in their follower-networks, and the users in the networks are more tightly connected and cohesive internally. The key business implication for the future social media engagement efforts by startup companies in general is that startup companies may need to focus on getting more attention from influencers and promoting more cohesive communities in their follower-networks to appreciate the potential benefits of social media in the early stage of business of startup companies.

• Journal of Distribution Science
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• v.10 no.2
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• pp.19-28
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• 2012

Rapidly growing sales amount and the number of discount stores caused many side effects and sensitive issues in Korea. Because these severe competition due to more expensive cost just like excessive increase in advertising and location selection, and these caused completely ruined small merchants as well as passed on to the consumer. This Study focused on competitiveness of discount store in Korea to the perspective of college students, as explored the relationships between marketing communication and store loyalty. And, examined for two moderating effect, 1) consumers' value separated by hedonic value and utilitarian value between marketing communication and store loyalty, and 2) consumers' value separated by hedonic value and utilitarian value between marketing communication and consumption emotion. Finally, this study examined for mediating effect of consumption emotion between marketing communication and store loyalty. In order to verify the relationship, moderating and mediating effects, data were collected from 130 college students in Whasung, Gyeonggi Province to test theoretical model and its hypotheses. Findings are as followed : First, analysis showed that factors such as advertisement(β =.221, p<.05), publicity(β =.513, p<.01), sales promotion(β =.234, p<.01), word of mouth(β =.627, p<.01) and physical environment(β =.339, p<.01) for marketing communication in the discount store have statistically significant positive effect on store loyalty. But the result of regression analysis for which factors are more impact in marketing communication between store loyalty showed that word of mouth(β =.53, p<.01) is only statistically significant. Second, publicity(β =-.895, p<.05), the sub-dimension of marketing communication shows only statistically significant negative moderating effect on store loyalty. But, the results of the moderating effect of value between marketing communication and consumption emotion verified that utilitarian value show statistically significant, specifically advertisement(β =.294, p<.01), physical environment(β =.418, p<.01), sales promotion(β =.245, p<.01), word of mouth(β =.414, p<.01) and publicity(β =1.137, p<.05), respectively. And hedonic value show statistically significant, specifically advertisement(β =.286, p<.01), physical environment (β =.418, p<.01), sales promotion(β =.236, p<.01) and word of mouth(β =.420, p<.01), respectively. But publicity(β =.145, p=.119) is not statistically significant. Finally, the results verified mediating effect for consumption emotion between all factors for marketing communication and store loyalty showed that factors such as advertisement, publicity, word of mouth and physical environment for marketing communication except sales promotion were statistically significant fully mediated in advertisement, and partially mediated in publicity, word of mouth and physical environment. This testified that the consumption emotion had the most important factor to enhance store loyalty to the perspective of College students. These results can provide important implications and invaluable tips for planning marketing strategies and gaining access to new potential customers. Implications and future research directions are also discussed.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.8
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• pp.236-250
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• 2016

This study was conducted to provide baseline data regarding functional cosmetics so that Inula. based cosmetics can increase its competitiveness in the market as well as to understand current trends to enable anticipation of demands for future product development. For this research, general consumers over the age of 20 residing in Seoul and the Gyeonggi district were surveyed. The results show consumers preferred serum-type products among various types of cosmetics, and that they purchased these once every 1-3 months. Consumers also preferred these products in less than 10-30ml capacity, and at costs of less than 30,000-50,000 KRW. For whitening, functional cosmetics consumers also preferred the serum type, in less than 30-50ml capacity and priced less than 30,000-50,000 KRW. Consumers preferred to purchase functional cosmetics in single units. The major purchasing location, with a high preference rate, was cosmetic stores, and the major sources of information, also with high preference rates, were 'experienced reviews from family, friends and acquaintances' and 'TV advertisements'. Respondents selected 'over 50,000 KRW' the most for all items when responding to 'Purchase Intent for Functional Cosmetics containing Inula', and responded that they were willing to pay 10%-30% more for functional cosmetics containing Inula compared to standard functional cosmetics. These results show that businesses in the cosmetics industry need to take consumer demand into account when developing new functional cosmetic products, as well as establish plans to create specialized spaces that provide better quality service and increase word of mouth effect through better utilization of various types of offline media, social media, and blogs. The study also shows a need for businesses to develop products fully utilizing the Inula flower, which has been shown to be effective as a natural skin whitener, wrinkle reducer and skin moisturizer, to appeal to the increasing number of customers interested in health and beauty.

• Asia pacific journal of information systems
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• v.18 no.1
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• pp.145-162
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• 2008

One of the big concerns in e-society is privacy issue. In special, in developing robust ubiquitous smart space and corresponding services, user profile and preference are collected by the service providers. Privacy issue would be more critical in context-aware services simply because most of the context data themselves are private information: user's current location, current schedule, friends nearby and even her/his health data. To realize the potential of ubiquitous smart space, the systems embedded in the space should corporate personal privacy preferences. When the users invoke a set of services, they are asked to allow the service providers or smart space to make use of personal information which is related to privacy concerns. For this reason, the users unhappily provide the personal information or even deny to get served. On the other side, service provider needs personal information as rich as possible with minimal personal information to discern royal and trustworthy customers and those who are not. It would be desirable to enlarge the allowable personal information complying with the service provider's request, whereas minimizing service provider's requiring personal information which is not allowed to be submitted and user's submitting information which is of no value to the service provider. In special, if any personal information required by the service provider is not allowed, service will not be provided to the user. P3P (Platform for Privacy Preferences) has been regarded as one of the promising alternatives to preserve the personal information in the course of electronic transactions. However, P3P mainly focuses on preserving the buyers' personal information. From time to time, the service provider's business data should be protected from the unintended usage from the buyers. Moreover, even though the user's privacy preference could depend on the context happened to the user, legacy P3P does not handle the contextual change of privacy preferences. Hence, the purpose of this paper is to propose a mutual P3P-based negotiation mechanism. To do so, service provider's privacy concern is considered as well as the users'. User's privacy policy on the service provider's information also should be informed to the service providers before the service begins. Second, privacy policy is contextually designed according to the user's current context because the nomadic user's privacy concern structure may be altered contextually. Hence, the methodology includes mutual privacy policy and personalization. Overall framework of the mechanism and new code of ethics is described in section 2. Pervasive platform for mutual P3P considers user type and context field, which involves current activity, location, social context, objects nearby and physical environments. Our mutual P3P includes the privacy preference not only for the buyers but also the sellers, that is, service providers. Negotiation methodology for mutual P3P is proposed in section 3. Based on the fact that privacy concern occurs when there are needs for information access and at the same time those for information hiding. Our mechanism was implemented based on an actual shopping mall to increase the feasibility of the idea proposed in this paper. A shopping service is assumed as a context-aware service, and data groups for the service are enumerated. The privacy policy for each data group is represented as APPEL format. To examine the performance of the example service, in section 4, simulation approach is adopted in this paper. For the simulation, five data elements are considered: $\cdot$ UserID $\cdot$ User preference $\cdot$ Phone number $\cdot$ Home address $\cdot$ Product information $\cdot$ Service profile. For the negotiation, reputation is selected as a strategic value. Then the following cases are compared: $\cdot$ Legacy P3P is considered $\cdot$ Mutual P3P is considered without strategic value $\cdot$ Mutual P3P is considered with strategic value. The simulation results show that mutual P3P outperforms legacy P3P. Moreover, we could conclude that when mutual P3P is considered with strategic value, performance was better than that of mutual P3P is considered without strategic value in terms of service safety.

• Journal of Venture Innovation
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• v.7 no.1
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• pp.1-15
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• 2024

This study aims to elucidate the characteristics of big tech platform companies' sports content business in an environment of rapid digital transformation. Specifically, this study examines the market structure of big tech platform companies with a focus on Amazon, revealing the role of sports content within this structure through an analysis of Amazon's sports marketing business and provides an outlook on the sports content business of big tech platform companies. Based on two-sided market platform business models, big tech platform companies incorporate sports content as a strategy to enhance the value of their platforms. Therefore, sports content is used as a tool to enhance the value of their platforms and to consolidate their monopoly position by maximizing profits by increasing the synergy of platform ecosystems such as infrastructure. Amazon acquires popular live sports broadcasting rights on a continental or national basis and supplies them to its platforms, which not only increases the number of new customers and purchasing effects, but also provides IT solution services to sports organizations and teams while planning and supplying various promotional contents, thus creates synergy across Amazon's platforms including its advertising business. Amazon also expands its business opportunities and increases its overall value by supplying live sports contents to Amazon Prime Video and Amazon Prime, providing technical services to various stakeholders through Amazon Web Services, and offering Amazon Marketing Cloud services for analyzing and predicting advertisers' advertising and marketing performance. This gives rise to a new paradigm in the sports marketing business in the digital era, stemming from the difference in market structure between big tech companies based on two-sided market platforms and legacy global companies based on one-sided markets. The core of this new model is a business through the development of various contents based on live sports streaming rights, and sports content marketing will become a major field of sports marketing along with traditional broadcasting rights and sponsorship. Big tech platform global companies such as Amazon, Apple, and Google have the potential to become new global sports marketing companies, and the current sports marketing and advertising companies, as well as teams and leagues, are facing both crises and opportunities.

• Iberoamérica
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• v.22 no.1
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• pp.73-109
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• 2020

In the tourism industry, emotional labor-related problems are highly likely because workers cannot avoid frequent face-to-face contacts with customers. Emotional labor, however, is not always recognized in the same pattern by every worker in similar situations. As can be see in this research, emotional labor appears to vary depending on individual characteristics and sociocultural and economic conditions. In fact, there are so many factors affecting emotional labor, and the level of influence concerning these factors can vary depending on when and where they are. Psychological and mental pains and stress from emotional labor depend on a number of factors. The expression of emotional labor, depending on age, length of employment and gender, shows a clear difference. In particular, for those who are planning to participate in international labor migration to the United States in the future, emotional labor was often not recognized as a serious problem or rather a positive social and cultural experience. In fact, there are various types of tourism workers in Oaxaca, and their experiences vary greatly depending on individual and economic and sociocultural environments. The emotional labor of the workers in the tourism sector of Oaxaca also has various forms depending on various conditions. Positive or negative perceptions and consequences of emotional labor vary depending on the circumstances of the individual and working conditions. In other words, socioeconomic conditions, individual personality or experiences, sociocultural characteristics, and autonomy in the workplace, have a significant impact. As a result, the forms and effects of emotional labor expressed and understood by tourism workers vary considerably and may vary depending on the situations. Considering these problems, the way emotional labor emerges is greatly influenced by sociocultural or personal factors as well as economic factors. In addition, rather than considering the existence and seriousness of emotional labor as given depending on the nature of a particular industry or work, it should also be recognized that the expression of emotional labor differ considerably from individual to individual. Also, the seriousness of problems caused by emotional labor can be diversified. In this sense, it is necessary to clearly understand the meanings of the dynamism, diversity and multidimensionality of emotional labor from a new perspective.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.15 no.6
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• pp.27-42
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• 2020

Startup accelerators have emerged as new investment entities that help early startups, which are not easy to survive continuously due to lack of funds, commercialization capabilities, and experiences. As their positive performance on early startups and the ecosystem has been proven, the number of early startups which want to receive their investment is also increasing. However, they are vaguely preparing to attract accelerators' investment because they do not have any information on what factors the accelerators consider important. In addition, researches on startup accelerators are also at an early level, so there are no remarkable prior studies on factors that decide on investment. Therefore, this study aims to help startups prepare for investment attraction by looking at what factors are important for accelerators to invest, and to provide meaningful implications to academia. In the preceding study, we derived five upper level categories, 26 lower level accelerators' investment determinants through the qualitative meta-synthesis method, secondary data analysis, observation on US accelerators and in-depth interviews. In this study, we want to derive important implications by deriving priorities of the accelerators' investment determinants. Therefore, we used AHP that are evaluated as the suitable methodology for deriving importance and priority. The analysis results show that accelerators value market-related factors most. This means that startups that are subject to investment by accelerators are early-stage startups, and many companies have not fully developed their products or services. Therefore, market-related factors that can be evaluated objectively seem to be more important than products (or services) that are still ambiguous. Next, it was found that the factors related to the internal workforce of startups are more important. Since accelerators want to develop their businesses together with start-ups and team members through mentoring, ease of collaboration with them is very important, which seems to be important. The overall priority analysis results of the 26 investment determinants show that 'customer needs' and 'founders and team members' understanding of customers and markets' (0.62) are important and high priority factors. The results also show that startup accelerators consider the customer-centered perspective very important. And among the factors related to startups, the most prominent factor was the founder's openness and execution ability. Therefore, it can be confirmed that accelerators consider the ease of collaboration with these startups very important.

• Journal of Distribution Science
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• v.10 no.5
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• pp.37-44
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• 2012

In this paper, we investigate several factors that affect the locational decision of discount stores by using previous studies on the marketing area and the location of commercial facilities. We selected 21 primary variables that are expected to influence the decision of store location and, by factor analysis, grouped them into five underlying factors. Among these, the demographic factor, which shows the potential purchasing power level, had the greatest impact on the locational decision for the store. However, we found individual stores positioned according to unique locational characteristics in addition to the demographic factor. It means that we have to additionally consider if the vicinity of the market is based on any physical properties. Many previous studies proposed four decision factors for store location: the economic factor, the demographic factor, the land utilization factor, and traffic factor. However, the fivefold factors-our distinctive contribution-are more concrete and persuasive according to Korean reality. We show that location preference is based on the following criteria: (1) the area is densely populated, (2) houses stand close together, (3) residents have a high income level, (4) road traffic is developed and easy to access, and (5) public transportation is well developed. The demographic factor has the greatest impact on the location of a discount store. The number of households has a greater relevance to the demographic factor than does the individual consumer. Second, discount stores relatively prefer places where houses are located close together because such places offer easy access to the market. Third, a place whose residents have a high income level will be preferred, with its large cars and excellent traffic conditions. Fourth, a location would be highly rated if the roads around commercial facilities are well developed and their accessibility is good. Finally, discount stores must be located close to bus stops because female consumers, including housewives-the most important customers-evaluate stores based on distance. In this research, the variable of consumer attitude and preference was excluded, and the location factors of discount stores were analyzed according to a microscopic view through physical spatial data. In the future, the opening of new discount stores based on the five factors indicated above will require a comparatively shorter time from the first project feasibility analysis. In addition, the result of our study can be applied to the field of public policy for constructing and attracting large-scale distribution facilities.