• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.1
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• pp.159-172
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• 2023

The purpose of this study is to explore a collaborative start-up space(Co-Space) configuration plan in terms of university-regional linkage through demand analysis on the composition of university-regional linkage startup space. To this end, a survey was conducted for request analysis, and the collected data were analyzed through the t-test, The Lotus for Focus model. In addition, FGI was implemented for entrepreneurs, and the direction of the composition of the university-region Co-Space was derived from various aspects. The results of this study are as follows. First, as a result of the analysis of the necessity of university-community Co-Space, the necessity of opening up the start-up space recognized by local residents and the necessity of building the start-up space in the region were high. In addition, men recognized the need to build a space for start-ups in the community more highly than women did women. Second, as a result of analysis of demands for university-regional Co-Space, the difference between current importance and future necessity of university-regional Co-Space was statistically significant. Third, as a result of analysis on the composition of the startup space by cooperation between universities and regions, different demands were made for composition of the startup space considering openness and closeness, and for composition of the startup space size. The implications of the study are as follows. First, Co-Spaces need to be constructed in conjunction with universities in accordance with the demands of start-up companies in the region by stage of development. Second, it is necessary to organize a customized Co-Space that takes into account the size and operation of the start-up space. Third, it is necessary to establish an experience-based open space for local residents in the remaining space of the university. Fourth, it is necessary to establish a Co-Space that enables an organic network between local communities, start-up investment companies, start-up support institutions, and start-up companies. This study is significant in that it proposed the regional startup ecosystem and the cooperative start-up space structure for strengthening start-up sustainability through cooperation between universities and local communities. The results of this study are expected to be used as useful basic data for Co-Space construction to build a regional start-up ecosystem in a trend emphasizing the importance of start-up space, which is a major factor affecting start-up companies.

• 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 .

• Journal of Environmental Impact Assessment
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• v.27 no.4
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• pp.367-377
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• 2018

A cultural ecosystem service(CES), which is non-material benefit that human gains from ecosystem, has been recently further recognized as gross national income increases. Previous researches proposed to quantify the value of CES, which still remains as a challenging issue today due to its social and cultural subjectivity. This study proposes new way of assessing CES which is called Cultural Service Opportunity Spectrum(CSOS). CSOS is accessibility based CES assessment methodology for regional scale and it is designed to be applicable for any regions in Korea for supporting decision making process. CSOS employed public spatial data which are road network and population density map. In addition, the results of 'Rapid Assessment of Natural Assets' implemented by National Institute of Ecology, Korea were used as a complementary data. CSOS was applied to Namyangju-si and the methodology resulted in revealing specific areas with great accessibility to 'Natural Assets' in the region. Based on the results, the advantages and limitations of the methodology were discussed with regard to weighting three main factors and in contrast to Scenic Quality model and Recreation model of InVEST which have been commonly used for assessing CES today due to its convenience today.

• Journal of the Korean Institute of Landscape Architecture
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• v.41 no.6
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• pp.158-170
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• 2013

With the recent 'Creative economy' and 'Cultural prosperity' coming to the fore as a new code to build up a city or a region, it is necessary to focus on strengthening the regional creative capacity as well as developing spontaneous regional culture. In such trend this research aims to explore the Kyunglidan-gil, Seoul, Korea in which creative-class are appearing autogenously in clusters and forming new cultural landscape, to identify the factors of their accumulation and changing aspect of cultural landscape. This study has the following purposes: First, Investigating the historical context of the Kyunglidan-gil's landscape. Second, considering the process of the creative-class being flowed into the Kyunglidan-gil as the subject leading to the modification of the region. Third, their activity was analyzed to consider the unique aspect of forming the cultural landscape at the Kyunglidan-gil. Regarding why the creative-class should flow in, results of the study drew five factors including region in issue compared to inexpensive rents, coexistence with nature, quiet atmosphere seeming isolated from the urban confusion, location possible to test and share individual materials one likes, and a site with synergy effect of activity through the network with acquaintances. Also, five characteristics of cultural landscape forming by the people's activity were drawn - space of communication for increasing creativity, temporary and flexible spatial use, expression of one's identity and taste, distinguishing, and positive use of the existing facilities. Like this, by exposing the 'creative-class', a subject of the leader in changing process of the Kyunglidan-gil, this research identified the aspect of forming cultural landscape.

• Journal of Korean Society of Transportation
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• v.25 no.4
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• pp.123-133
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• 2007

This study analyzed whether a transit network with hierarchy is efficient or not, and if transit network hierarchy has cost efficiency, then which condition guarantees the efficiency of the transit network hierarchy. The authors modeled the total cost of the transit network and suggested the conditions in which the transit network hierarchy has cost efficiency through comparing the cost of the transit network with and without hierarchy. The efficiency of transit network hierarchy is guaranteed when the travel cost savings induced by using a higher hierarchy transit network is larger than the increasing non-travel cost, which is the sum of access cost, waiting cost, and operating cost, induced by the introduction of a higher hierarchy transit network. This result is consistent with common sense and with the concept of cost and benefit analysis. If a passenger traveling within the area divided by a higher hierarchy transit network uses only a lower hierarchy transit network and the passenger traveling out of the area divided by the higher hierarchy transit network uses both lower and higher hierarchy transit networks, the travel demand using the higher hierarchy transit network is inversely proportional to the square of the line spacing. This means that the transit network becomes more efficient and small increases of travel demand guarantee the efficiency of the transit network hierarchy as the connectivity of the network becomes higher. This result shows that transit networks have economies of aggregation. This study is the first analytical research on transit network hierarchy and is expected to be a basis for numerical research. However, numerical research should complement this study, since analytical research has some limitations for considering a real network.

• Journal of Intelligence and Information Systems
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• v.16 no.4
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• pp.159-172
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• 2010

The recommender system is one of the possible solutions to assist customers in finding the items they would like to purchase. To date, a variety of recommendation techniques have been developed. One of the most successful recommendation techniques is Collaborative Filtering (CF) that has been used in a number of different applications such as recommending Web pages, movies, music, articles and products. CF identifies customers whose tastes are similar to those of a given customer, and recommends items those customers have liked in the past. Numerous CF algorithms have been developed to increase the performance of recommender systems. Broadly, there are memory-based CF algorithms, model-based CF algorithms, and hybrid CF algorithms which combine CF with content-based techniques or other recommender systems. While many researchers have focused their efforts in improving CF performance, the theoretical justification of CF algorithms is lacking. That is, we do not know many things about how CF is done. Furthermore, the relative performances of CF algorithms are known to be domain and data dependent. It is very time-consuming and expensive to implement and launce a CF recommender system, and also the system unsuited for the given domain provides customers with poor quality recommendations that make them easily annoyed. Therefore, predicting the performances of CF algorithms in advance is practically important and needed. In this study, we propose an efficient approach to predict the performance of CF. Social Network Analysis (SNA) and Artificial Neural Network (ANN) are applied to develop our prediction model. CF can be modeled as a social network in which customers are nodes and purchase relationships between customers are links. SNA facilitates an exploration of the topological properties of the network structure that are implicit in data for CF recommendations. An ANN model is developed through an analysis of network topology, such as network density, inclusiveness, clustering coefficient, network centralization, and Krackhardt's efficiency. While network density, expressed as a proportion of the maximum possible number of links, captures the density of the whole network, the clustering coefficient captures the degree to which the overall network contains localized pockets of dense connectivity. Inclusiveness refers to the number of nodes which are included within the various connected parts of the social network. Centralization reflects the extent to which connections are concentrated in a small number of nodes rather than distributed equally among all nodes. Krackhardt's efficiency characterizes how dense the social network is beyond that barely needed to keep the social group even indirectly connected to one another. We use these social network measures as input variables of the ANN model. As an output variable, we use the recommendation accuracy measured by F1-measure. In order to evaluate the effectiveness of the ANN model, sales transaction data from H department store, one of the well-known department stores in Korea, was used. Total 396 experimental samples were gathered, and we used 40%, 40%, and 20% of them, for training, test, and validation, respectively. The 5-fold cross validation was also conducted to enhance the reliability of our experiments. The input variable measuring process consists of following three steps; analysis of customer similarities, construction of a social network, and analysis of social network patterns. We used Net Miner 3 and UCINET 6.0 for SNA, and Clementine 11.1 for ANN modeling. The experiments reported that the ANN model has 92.61% estimated accuracy and 0.0049 RMSE. Thus, we can know that our prediction model helps decide whether CF is useful for a given application with certain data characteristics.

• Management & Information Systems Review
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• v.39 no.1
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• pp.93-114
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• 2020

Platform is considered as an alternative strategy to the traditional linear pipeline based business. Moreover, in the 4th industrial revolution period, efficiency driven pipeline business model needs to be changed to platform business. We have such success stories about platform as Apple, Google, Amazon, Uber, and so on. However, for those smaller corporations, it is not easy to find out the transformation strategy. The essence of platform business is to leverage network effect in management. Thus platform based management can be rephrased as network management across the business functions. Research on platform business is popular and related to diverse facets. But few scholars cover what the research trend of the domain is. The main purpose of this paper is to identify the research trend on platform business in Korea. To do that we first propose the analytical model for platform architecture whose components are consumers, suppliers, artifacts, and IT platform system. We conjecture that mapping of the research work on platform to the components of the model will make us understand the hidden domain of platform research. We propose three hypotheses regarding the characteristics of research and one proposition for the transitional path from pipeline to platform business model. The mapping is based on the research articles filtered from the Korea Citation Index, using keyword search. Research papers are searched through the keywords provided by authors using the word of "platform". The filtered articles are summarized in terms of the attributes such as major component of platform considered, platform type, main purpose of the research, and research method. Using the filtered data, we test the hypotheses in exploratory ways. The contribution of our research is as follows: First, based on the findings, scholars can find the areas of research on the domain: areas where research has been matured and territory where future research is actively sought. Second, the proposition provided can give business practitioners the guideline for changing their strategy from pipeline to platform oriented. This research needs to be considered as exploratory not inferential since subjective judgments are involved in data collection, classification, and interpretation of research articles.

• Journal of Intelligence and Information Systems
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• v.25 no.4
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• pp.67-88
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• 2019

Webtoon is a Korean-style digital comics platform that distributes comics content produced using the characteristic elements of the Internet in a form that can be consumed online. With the recent rapid growth of the webtoon industry and the exponential increase in the supply of webtoon content, the need for effective webtoon content recommendation measures is growing. Webtoons are digital content products that combine pictorial, literary and digital elements. Therefore, webtoons stimulate consumer sentiment by making readers have fun and engaging and empathizing with the situations in which webtoons are produced. In this context, it can be expected that the sentiment that webtoons evoke to consumers will serve as an important criterion for consumers' choice of webtoons. However, there is a lack of research to improve webtoons' recommendation performance by utilizing consumer sentiment. This study is aimed at developing consumer sentiment pattern maps that can support effective recommendations of webtoon content, focusing on consumer sentiments that have not been fully discussed previously. Metadata and consumer sentiments data were collected for 200 works serviced on the Korean webtoon platform 'Naver Webtoon' to conduct this study. 488 sentiment terms were collected for 127 works, excluding those that did not meet the purpose of the analysis. Next, similar or duplicate terms were combined or abstracted in accordance with the bottom-up approach. As a result, we have built webtoons specialized sentiment-index, which are reduced to a total of 63 emotive adjectives. By performing exploratory factor analysis on the constructed sentiment-index, we have derived three important dimensions for classifying webtoon types. The exploratory factor analysis was performed through the Principal Component Analysis (PCA) using varimax factor rotation. The three dimensions were named 'Immersion', 'Touch' and 'Irritant' respectively. Based on this, K-Means clustering was performed and the entire webtoons were classified into four types. Each type was named 'Snack', 'Drama', 'Irritant', and 'Romance'. For each type of webtoon, we wrote webtoon-sentiment 2-Mode network graphs and looked at the characteristics of the sentiment pattern appearing for each type. In addition, through profiling analysis, we were able to derive meaningful strategic implications for each type of webtoon. First, The 'Snack' cluster is a collection of webtoons that are fast-paced and highly entertaining. Many consumers are interested in these webtoons, but they don't rate them well. Also, consumers mostly use simple expressions of sentiment when talking about these webtoons. Webtoons belonging to 'Snack' are expected to appeal to modern people who want to consume content easily and quickly during short travel time, such as commuting time. Secondly, webtoons belonging to 'Drama' are expected to evoke realistic and everyday sentiments rather than exaggerated and light comic ones. When consumers talk about webtoons belonging to a 'Drama' cluster in online, they are found to express a variety of sentiments. It is appropriate to establish an OSMU(One source multi-use) strategy to extend these webtoons to other content such as movies and TV series. Third, the sentiment pattern map of 'Irritant' shows the sentiments that discourage customer interest by stimulating discomfort. Webtoons that evoke these sentiments are hard to get public attention. Artists should pay attention to these sentiments that cause inconvenience to consumers in creating webtoons. Finally, Webtoons belonging to 'Romance' do not evoke a variety of consumer sentiments, but they are interpreted as touching consumers. They are expected to be consumed as 'healing content' targeted at consumers with high levels of stress or mental fatigue in their lives. The results of this study are meaningful in that it identifies the applicability of consumer sentiment in the areas of recommendation and classification of webtoons, and provides guidelines to help members of webtoons' ecosystem better understand consumers and formulate strategies.

• Journal of Life Science
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• v.23 no.11
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• pp.1325-1335
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• 2013

Working dogs, such as rescue dogs, military watch dogs, guide dogs, and search dogs, are selected by in-training examination of desired traits, including concentration, possessiveness, and boldness. In recent years, genetic information has been considered to be an important factor for the outstanding abilities of working dogs. To characterize the molecular features of the canine genes related to phenotypes for working dogs, we investigated the 24 previously reported genes (AR, BDNF, DAT, DBH, DGCR2, DRD4, MAOA, MAOB, SLC6A4, TH, TPH2, IFT88, KCNA3, TBR2, TRKB, ACE, GNB1, MSTN, PLCL1, SLC25A22, WFIKKN2, APOE, GRIN2B, and PIK3CG) that were categorized to personality, olfactory sense, and athletic/learning ability. We analyzed the chromosomal location, gene-gene interactions, Gene Ontology, and expression patterns of these genes using bioinformatic tools. In addition, variable numbers of tandem repeat (VNTR) or microsatellite (MS) polymorphism in the AR, MAOA, MAOB, TH, DAT, DBH, and DRD4 genes were reviewed. Taken together, we suggest that the genetic background of the canine genes associated with various working dog behaviors and skill performance attributes could be used for proper selection of superior working dogs.

• Journal of Intelligence and Information Systems
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• v.26 no.4
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• pp.67-86
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• 2020

Recommender Systems have been huge influence users and business more and more. Recently the importance of E-commerce has been reached rapid growth greatly in world-wide COVID-19 pandemic. Recommender system is the center of E-commerce lively. Top ranked E-commerce managers mentioned that recommender systems have a major influence on customer's purchase such as about 50% of Netflix, Amazon sales from their recommender systems. Most algorithms have been focused on improving accuracy of recommender system regardless of novelty, diversity, serendipity etc. Recommender systems with only high accuracy cannot satisfy business long-term profit because of generating sales polarization. In addition, customers do not experience enjoyment of shopping from only focusing accuracy recommender system because customer's preference is changed constantly. Therefore, recommender systems with various values need to be developed for user's high satisfaction. Reranking is the most useful methodology to realize diversity of recommender system. In this paper, diversity of recommender system is represented through constructing high similarity with users who have different preference using each user's purchased item's category algorithm. It is distinguished from past research approach which is changing the algorithm of recommender system without user's diversity preference level. We tried to discover user's diversity preference level and observed the results how the effect was different according to user's diversity preference level. In addition, graph-based recommender system was used to show diversity through user's network, not collaborative filtering. In this paper, Amazon Grocery and Gourmet Food data was used because the low-involvement product, such as habitual product, foods, low-priced goods etc., had high probability to show customer's diversity. First, a bipartite graph with users and items simultaneously is constructed to make graph-based recommender system. However, each users and items unipartite graph also need to be established to show diversity of recommender system. The weight of each unipartite graph has played crucial role changing Jaccard Distance of item's category. We can observe two important results from the user's unipartite network. First, the user's diversity preference level is observed from the network and second, dissimilar users can be discovered in the user's network. Through the research process, diversity of recommender system is presented highly with small accuracy loss and optimalization for higher accuracy is possible controlling diversity ratio. This paper has three important theoretical points. First, this research expands recommender system research for user's satisfaction with various values. Second, the graph-based recommender system is developed newly. Third, the evaluation indicator of diversity is made for diversity. In addition, recommender systems are useful for corporate profit practically and this paper has contribution on business closely. Above all, business long-term profit can be improved using recommender system with diversity and the recommender system can provide right service according to user's diversity level. Lastly, the corporate selling low-involvement products have great effect based on the results.