• Journal of Fashion Business
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• v.19 no.5
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• pp.157-174
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• 2015

This research intends to observe the effects of social capital regarding fashion social enterprises on the community sense of participating consumers, and verify the relationship of the effects that such social capital and community sense have on sustainability formation variable(shared values, suitability of values, behavioral flow, cognitive belief and long-term relationship orientation) of social enterprises. For such analysis, a sample of 400 consumers with experience of purchasing products of fashion social enterprises more than once was utilized, and path analysis was conducted utilizing AMOS 20.0. As a result of this research, first, information sharing, social participation among the characteristic factors of social enterprises' social capital had a meaningful impact on shared values, and self-pursuit and significance meaningfully affected the suitability of values. Second, mutual influence, sense of belonging, satisfaction of needs and emotional bond among the characteristic factors of community sense between social enterprises and consumers meaningfully affected shared values, whereas mutual influence, sense of belonging and emotional bond substantially influenced suitability of values. Third, shared values and suitability of values affected the relationship between behavioral flow and cognitive trust, and behavioral flow and cognitive trust both had meaningful impact on long-term relationship orientation.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.3
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• pp.987-996
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• 2021

The development of Internet technology can affect firm value through the use of social media by business people. Nowadays, social media affect businesses of all sizes in several different ways. Despite the various benefits obtained by using social media, research at the organizational level and its impact on business performance have not grown as fast as desired. This research aims to examine the effect of social media on oil and gas firms' value. The research sample consists of 9 oil and gas firms listed on the Indonesian Stock Exchange 2013-2018. Social media proxies are firms' social media, other social media mentions, and social media sentiment. Firm value is measured by the market value to assets ratio. Data analysis uses a random-effect regression test. Based on the analysis, the social media account of a firm has a positive effect on firm value. It indicates that social media give advantages for oil and gas firms to give a signal of business prospect, make use of opportunities related to industry alliances, recruit employees globally, and c. On the other hand, the positive sentiment on social media has no effect on oil and gas firms' value.

• Journal of Distribution Science
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• v.17 no.10
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• pp.73-81
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• 2019

Purpose - The purpose of this study was to examine the effect of the heuristic type of consumers affecting purchase decision making and the intention of shopping value in their relationship to derive mobile social commerce purchase promotion plans. Research design, data, and methodology - A research model was constructed to relate the mediating effect of shopping value between heuristic types and purchase intentions. A total of 233 valid questionnaires were used for analysis for users using mobile social commerce. The statistical program used SPSS 24.0 and AMOS 24.0, and correlation analysis, regression analysis, and 3-step parametric regression analysis were used for the analysis. Results - The results of the analysis showed that representativeness heuristics, availability heuristics, adjustment heuristics, and affect heuristics had a statistically significant effect on the utilitarian value and the hedonic value. On the other hand, affect heuristics among the heuristic types were found to have the greatest influence not only on the utilitarian value but also on the hedonic value. The two types of shopping value were found to be partially mediated between representativeness heuristics and purchase intentions, between adjustment heuristics and purchase intentions, and fully mediated between availability heuristics and purchase intentions, affect heuristics and purchase intentions. Conclusions - These findings suggest that mobile social commerce companies should check in advance how consumer heuristic types affect purchase intentions. In particular, affect heuristics are caused by consumers' emotional mood such as mood or external stimulus being more important to decision making than rational decision making. Therefore, the result of this study suggests that it can be an important factor to secure the competitiveness that the potential customers who access to use mobile social commerce can feel enough fun and enjoyment in the platform provided by the company. It is also worth paying attention to the utilitarian and hedonic values perceived by consumers. This is because the judgment regarding the economic, convenience and important information provided by the mobile social commerce users affects the purchase intention through the trust of the information, past use, and shopping experience displayed on the mobile social commerce platform.

• International Journal of Internet, Broadcasting and Communication
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• v.15 no.3
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• pp.211-218
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• 2023

Due to the implementation of COVID-19 distancing, interest and users in 'home training' are rapidly increasing. Therefore, the purpose of this study is to identify the perception of 'home training' through big data analysis on social media channels and provide basic data to related business sector. Social media channels collected big data from various news and social content provided on Naver and Google sites. Data for three years from March 22, 2020 were collected based on the time when COVID-19 distancing was implemented in Korea. The collected data included 4,000 Naver blogs, 2,673 news, 4,000 cafes, 3,989 knowledge IN, and 953 Google channel news. These data analyzed TF and TF-IDF through text mining, and through this, semantic network analysis was conducted on 70 keywords, big data analysis programs such as Textom and Ucinet were used for social big data analysis, and NetDraw was used for visualization. As a result of text mining analysis, 'home training' was found the most frequently in relation to TF with 4,045 times. The next order is 'exercise', 'Homt', 'house', 'apparatus', 'recommendation', and 'diet'. Regarding TF-IDF, the main keywords are 'exercise', 'apparatus', 'home', 'house', 'diet', 'recommendation', and 'mat'. Based on these results, 70 keywords with high frequency were extracted, and then semantic indicators and centrality analysis were conducted. Finally, through CONCOR analysis, it was clustered into 'purchase cluster', 'equipment cluster', 'diet cluster', and 'execute method cluster'. For the results of these four clusters, basic data on the 'home training' business sector were presented based on consumers' main perception of 'home training' and analysis of the meaning network.

• Journal of Intelligence and Information Systems
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• v.18 no.4
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• pp.117-127
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• 2012

Due to the recent expansion of the Web 2.0 -based services, along with the widespread of smartphones, online social network services are being popularized among users. Online social network services are the online community services which enable users to communicate each other, share information and expand human relationships. In the social network services, each relation between users is represented by a graph consisting of nodes and links. As the users of online social network services are increasing rapidly, the SNS are actively utilized in enterprise marketing, analysis of social phenomenon and so on. Social Network Analysis (SNA) is the systematic way to analyze social relationships among the members of the social network using the network theory. In general social network theory consists of nodes and arcs, and it is often depicted in a social network diagram. In a social network diagram, nodes represent individual actors within the network and arcs represent relationships between the nodes. With SNA, we can measure relationships among the people such as degree of intimacy, intensity of connection and classification of the groups. Ever since Social Networking Services (SNS) have drawn increasing attention from millions of users, numerous researches have made to analyze their user relationships and messages. There are typical representative SNA methods: degree centrality, betweenness centrality and closeness centrality. In the degree of centrality analysis, the shortest path between nodes is not considered. However, it is used as a crucial factor in betweenness centrality, closeness centrality and other SNA methods. In previous researches in SNA, the computation time was not too expensive since the size of social network was small. Unfortunately, most SNA methods require significant time to process relevant data, and it makes difficult to apply the ever increasing SNS data in social network studies. For instance, if the number of nodes in online social network is n, the maximum number of link in social network is n(n-1)/2. It means that it is too expensive to analyze the social network, for example, if the number of nodes is 10,000 the number of links is 49,995,000. Therefore, we propose a heuristic-based method for finding the shortest path among users in the SNS user graph. Through the shortest path finding method, we will show how efficient our proposed approach may be by conducting betweenness centrality analysis and closeness centrality analysis, both of which are widely used in social network studies. Moreover, we devised an enhanced method with addition of best-first-search method and preprocessing step for the reduction of computation time and rapid search of the shortest paths in a huge size of online social network. Best-first-search method finds the shortest path heuristically, which generalizes human experiences. As large number of links is shared by only a few nodes in online social networks, most nods have relatively few connections. As a result, a node with multiple connections functions as a hub node. When searching for a particular node, looking for users with numerous links instead of searching all users indiscriminately has a better chance of finding the desired node more quickly. In this paper, we employ the degree of user node vn as heuristic evaluation function in a graph G = (N, E), where N is a set of vertices, and E is a set of links between two different nodes. As the heuristic evaluation function is used, the worst case could happen when the target node is situated in the bottom of skewed tree. In order to remove such a target node, the preprocessing step is conducted. Next, we find the shortest path between two nodes in social network efficiently and then analyze the social network. For the verification of the proposed method, we crawled 160,000 people from online and then constructed social network. Then we compared with previous methods, which are best-first-search and breath-first-search, in time for searching and analyzing. The suggested method takes 240 seconds to search nodes where breath-first-search based method takes 1,781 seconds (7.4 times faster). Moreover, for social network analysis, the suggested method is 6.8 times and 1.8 times faster than betweenness centrality analysis and closeness centrality analysis, respectively. The proposed method in this paper shows the possibility to analyze a large size of social network with the better performance in time. As a result, our method would improve the efficiency of social network analysis, making it particularly useful in studying social trends or phenomena.

• Journal of Distribution Science
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• v.17 no.5
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• pp.5-17
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• 2019

Purpose - This study aims to exploratorily analyze relationship among pressure on business failure, social safety net perception, and entrepreneurial intention targeting potential business founders - pre-entrepreneurs and re-entrepreneurs. Research design, data, and methodology - Out of 450 collected surveys, 386 were used for analysis. Among these, 216 were from pre-entrepreneurs and 170 were from re-entrepreneurs. Frequency analysis, reliability and validity analysis, and regression analysis were performed. Results - In analysis of pre-entrepreneur and re-entrepreneur's pressure on business failure and social safety net perception, objective environment perception - a subfactor of social safety net perception - had statistically significant difference between the two potential entrepreneur groups. Conclusions - We categorized potential entrepreneurs into pre-entrepreneurs and re-entrepreneurs. Also, the current study suggests importance of social safety net to vitalize food service business startup by validifying its mediating effect between pressure on business failure and attitude towards restaurant business establishment. This research also established groundwork for future studies on ways to improve entrepreneurial intention or startup business sustainability by deducing social safety net perception difference between pre-entrepreneurs and re-entrepreneurs. This study was able to analyze relationship between those two groups in terms of entrepreneurial intention and startup business sustainability.

• Journal of Korea Society of Digital Industry and Information Management
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• v.17 no.4
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• pp.161-175
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• 2021

This study analyzed the efficiency and influence factors according to the main research institute type of R&D Program for the local community problem-solving. This study applied data envelopment analysis (DEA) method and Tobit regression analysis by using 20 institutions that participated in R&D Program. The results are summarized as follows. First, Analysis results according to the research institute type of R&D project, Efficient DMUs showed more regional innovation institutions than social economy enterprises. But regional innovation institutions were the lowest in the CCR and BCC model. However, efficiency dose not differ between regional innovation institutions and social economy enterprises. Second, as a result of the analysis relation between efficiency and allocation characteristics of R&D input, the participation of regional innovation organizations as participating organizations has a negative effect on efficiency. It was found that the higher the proportion of government subsidies and the higher the employment rate of the vulnerable, which is a social achievement, the positive effect on efficiency. The implication of this study is that the participation of social economy enterprises as the main R&D institution and government R&D support can provide social economy enterprises with opportunities to accumulate R&D capabilities and experience successful commercialization.

• The Journal of Industrial Distribution & Business
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• v.13 no.9
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• pp.37-50
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• 2022

Purpose: The purpose of this study is to explore and compare research trends in Korea and overseas academic papers on social media marketing, and to present new academic perspectives for the future direction in Korea. Research design, data and methodology: We used English abstract of research paper (Korea's: 1,349, overseas': 5,036) for word frequency analysis, topic modeling, and trend analysis for each topic. Results: The results of word frequency and co-occurrence frequency analysis showed that Korea researches focused on the experiential values of users, and overseas researches focused on platforms and content. Next, 13 topics and 12 topics for Korea and overseas researches were derived from topic modeling. And, trend analysis showed that Korean studies were different from overseas in applying marketing methods to specific industries and they were interested in the short-term performance of social media marketing. Conclusions: We found that the long-term strategies of social media marketing and academic interest in the overall industry will necessary in the future researches. Also, data mining techniques will necessary to generate more general results by quantifying various phenomena in reality. Finally, we expected that continuous and various academic approaches for volatile social media is effective to derive practical implications.

• Journal of Korean Society of Transportation
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• v.33 no.1
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• pp.50-60
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• 2015

Pedestrians not only walk along roads, but also pass through buildings or across open spaces. This study defines these unusual walk routes as social path. Social path is an informal pedestrian route that is not considered in a pedestrian network, even though it should be regarded as pedestrian route considering the fact that many people actually use this path. In response, current study related to travel behavior cannot evaluate properly due to lack of consideration for realistic travel behavior such as social path. In order to deal with this situation, this study analyzes the effect of social path at two complex centers in Seoul. Evaluation indices are service area analysis and urban network analysis which is one of the spatial network analysis. In particular, we subdivide the network into three steps by the level of network building and analyze each step. As a result, it is revealed that step three which includes social path shows the greatest improvement in pedestrian accessibility. In this regard, we confirm that social path should be considered when evaluating pedestrian accessibility in further studies. Furthermore, a lot of undervalued facilities will be re-appraised in the field of travel behavior.

• Informatization Policy
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• v.18 no.3
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• pp.25-49
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• 2011

As a way to gather diverse information required for everyday living, the importance of social networks has been growing. Social network services have been spreading rapidly because of diffusion of the Internet, evolution of social network sites, and recognition of the importance of social networks. Recently, the social network service has been evolved based on a new paradigm, Web 2.0, pursuing participation and openness. Following the adoption of Web 2.0 technologies, the social network service allows users to make and maintain new relationships in a more convenient way. Users of the social network service tend to reveal their personal information, and share their ideas and content with other people; in the process they become aware of their existence, feel satisfaction with life and exert influence to others as a member of the society. This study uses higher order factor analysis to analyze factors that affect the intention of using the social network service. A research model was developed with second-order factors including perceived social presence, perceived gratification and perceived social influence. First-order factors are grouped by technical, individual and social factors. Smart PLS 2.0 was used to conduct empirical analysis. The analysis results supported the validity of the research model.