• Journal of Intelligence and Information Systems
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• v.23 no.1
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• pp.1-22
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• 2017

Analysis of future business or investment opportunities, such as business feasibility analysis and company or technology valuation, necessitate objective estimation on the relevant market and expected sales. While there are various ways to classify the estimation methods of these new sales or market size, they can be broadly divided into top-down and bottom-up approaches by benchmark references. Both methods, however, require a lot of resources and time. Therefore, we propose a data-based intelligent demand forecasting system to support evaluation of new business. This study focuses on analogical forecasting, one of the traditional quantitative forecasting methods, to develop sales forecasting intelligence systems for new businesses. Instead of simply estimating sales for a few years, we hereby propose a method of estimating the sales of new businesses by using the initial sales and the sales growth rate of similar companies. To demonstrate the appropriateness of this method, it is examined whether the sales performance of recently established companies in the same industry category in Korea can be utilized as a reference variable for the analogical forecasting. In this study, we examined whether the phenomenon of "mean reversion" was observed in the sales of start-up companies in order to identify errors in estimating sales of new businesses based on industry sales growth rate and whether the differences in business environment resulting from the different timing of business launch affects growth rate. We also conducted analyses of variance (ANOVA) and latent growth model (LGM) to identify differences in sales growth rates by industry category. Based on the results, we proposed industry-specific range and linear forecasting models. This study analyzed the sales of only 150,000 start-up companies in Korea in the last 10 years, and identified that the average growth rate of start-ups in Korea is higher than the industry average in the first few years, but it shortly shows the phenomenon of mean-reversion. In addition, although the start-up founding juncture affects the sales growth rate, it is not high significantly and the sales growth rate can be different according to the industry classification. Utilizing both this phenomenon and the performance of start-up companies in relevant industries, we have proposed two models of new business sales based on the sales growth rate. The method proposed in this study makes it possible to objectively and quickly estimate the sales of new business by industry, and it is expected to provide reference information to judge whether sales estimated by other methods (top-down/bottom-up approach) pass the bounds from ordinary cases in relevant industry. In particular, the results of this study can be practically used as useful reference information for business feasibility analysis or technical valuation for entering new business. When using the existing top-down method, it can be used to set the range of market size or market share. As well, when using the bottom-up method, the estimation period may be set in accordance of the mean reverting period information for the growth rate. The two models proposed in this study will enable rapid and objective sales estimation of new businesses, and are expected to improve the efficiency of business feasibility analysis and technology valuation process by developing intelligent information system. In academic perspectives, it is a very important discovery that the phenomenon of 'mean reversion' is found among start-up companies out of general small-and-medium enterprises (SMEs) as well as stable companies such as listed companies. In particular, there exists the significance of this study in that over the large-scale data the mean reverting phenomenon of the start-up firms' sales growth rate is different from that of the listed companies, and that there is a difference in each industry. If a linear model, which is useful for estimating the sales of a specific company, is highly likely to be utilized in practical aspects, it can be explained that the range model, which can be used for the estimation method of the sales of the unspecified firms, is highly likely to be used in political aspects. It implies that when analyzing the business activities and performance of a specific industry group or enterprise group there is political usability in that the range model enables to provide references and compare them by data based start-up sales forecasting system.

• Journal of Global Scholars of Marketing Science
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• v.17 no.3
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• pp.39-59
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• 2007

The international involvement of a firm has been described as a gradual development process "a process in which the enterprise gradually increases its international involvement in many studies. This process evolves in the interplay between the development of knowledge about foreign markets and operations on one hand and increasing commitment of resources to foreign markets on the other." On the basis of Uppsala internationalization model, many studies strengthen strong theoretical and empirical support. According to the predictions of the classic stages theory, the internationalization process of firms have been recognized and characterized gradual evolution to foreign markets, so called stage theory: indirect & direct export, strategic alliance and foreign direct investment. However, termed "international new ventures" (McDougall, Shane, and Oviatt 1994), "born globals" (Knight 1997; Knight and Cavusgil 1996; Madsen and Servais 1997), "instant internationals" (Preece, Miles, and Baetz 1999), or "global startups" (Oviatt and McDougall 1994) have been used and come into spotlight in internationalization study of technology intensity venture companies. Recent researches focused on venture company have suggested the phenomenons of 'born global' firms as a contradiction to the stages theory. Especially the article by Oviatt and McDougall threw the spotlight on international entrepreneurs, on international new ventures, and on their importance in the globalising world economy. Since venture companies have, by definition. lack of economies of scale, lack of resources (financial and knowledge), and aversion to risk taking, they have a difficulty in expanding their market to abroad and pursue internalization gradually and step by step. However many venture companies have pursued 'Born Global Strategy', which is different from process strategy, because corporate's environment has been rapidly changing to globalization. The existing studies investigate that (1) why the ventures enter into overseas market in those early stage, even in infancy, (2) what make the different international strategy among ventures and the born global strategy is better to the infant ventures. However, as for venture's performance(growth and profitability), the existing results do not correspond each other. They also, don't include marketing strategy (differentiation, low price, market breadth and market pioneer) that is important factors in studying of BGV's performance. In this paper I aim to delineate the appearance of international new ventures and the phenomenons of venture companies' internationalization strategy. In order to verify research problems, I develop a resource-based model and marketing strategies for analyzing the effects of the born global venture firms. In this paper, I suggested 3 research problems. First, do the korean venture companies take some advantages in the aspects of corporate's performances (growth, profitability and overall market performances) when they pursue internationalization from inception? Second, do the korean BGV have firm specific assets (foreign experiences, foreign orientation, organizational absorptive capacity)? Third, What are the marketing strategies of korean BGV and is it different from others? Under these problems, I test then (1) whether the BGV that a firm started its internationalization activity almost from inception, has more intangible resources(foreign experience of corporate members, foreign orientation, technological competences and absorptive capacity) than any other venture firms(Non_BGV) and (2) also whether the BGV's marketing strategies-differentiation, low price, market diversification and preemption strategy are different from Non_BGV. Above all, the main purpose of this research is that results achieved by BGV are indeed better than those obtained by Non_BGV firms with respect to firm's growth rate and efficiency. To do this research, I surveyed venture companies located in Seoul and Deajeon in Korea during November to December, 2005. I gather the data from 200 venture companies and then selected 84 samples, which have been founded during 1999${\sim}$2000. To compare BGV's characteristics with those of Non_BGV, I also had to classify BGV by export intensity over 50% among five or six aged venture firms. Many other researches tried to classify BGV and Non_BGV, but there were various criterion as many as researchers studied on this topic. Some of them use time gap, which is time difference of establishment and it's first internationalization experience and others use export intensity, ration of export sales amount divided by total sales amount. Although using a mixed criterion of prior research in my case, I do think this kinds of criterion is subjective and arbitrary rather than objective, so I do mention my research has some critical limitation in the classification of BGV and Non_BGV. The first purpose of research is the test of difference of performance between BGV and Non_BGV. As a result of t-test, the research show that there are statistically efficient difference not only in the growth rate (sales growth rate compared to competitors and 3 years averaged sales growth rate) but also in general market performance of BGV. But in case of profitability performance, the hypothesis that is BGV is more profit (return on investment(ROI) compared to competitors and 3 years averaged ROI) than Non-BGV was not supported. From these results, this paper concludes that BGV grows rapidly and gets a high market performance (in aspect of market share and customer loyalty) but there is no profitability difference between BGV and Non_BGV. The second result is that BGV have more absorptive capacity especially, knowledge competence, and entrepreneur's international experience than Non_BGV. And this paper also found BGV search for product differentiation, exemption strategy and market diversification strategy while Non_BGV search for low price strategy. These results have never been dealt with other existing studies. This research has some limitations. First limitation is concerned about the definition of BGV, as I mentioned above. Conceptually speaking, BGV is defined as company pursue internationalization from inception, but in empirical study, it's very difficult to classify between BGV and Non_BGV. I tried to classify on the basis of time difference and export intensity, this criterions are so subjective and arbitrary that the results are not robust if the criterion were changed. Second limitation is concerned about sample used in this research. I surveyed venture companies just located in Seoul and Daejeon and also use only 84 samples which more or less provoke sample bias problem and generalization of results. I think the more following studies that focus on ventures located in other region, the better to verify the results of this paper.

• 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 Intelligence and Information Systems
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• v.24 no.3
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• pp.67-88
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• 2018

Until recently, as we recognize the significance of sustainable growth and competitiveness of small-and-medium sized enterprises (SMEs), governmental support for tangible resources such as R&D, manpower, funds, etc. has been mainly provided. However, it is also true that the inefficiency of support systems such as underestimated or redundant support has been raised because there exist conflicting policies in terms of appropriateness, effectiveness and efficiency of business support. From the perspective of the government or a company, we believe that due to limited resources of SMEs technology development and capacity enhancement through collaboration with external sources is the basis for creating competitive advantage for companies, and also emphasize value creation activities for it. This is why value chain network analysis is necessary in order to analyze inter-company deal relationships from a series of value chains and visualize results through establishing knowledge ecosystems at the corporate level. There exist Technology Opportunity Discovery (TOD) system that provides information on relevant products or technology status of companies with patents through retrievals over patent, product, or company name, CRETOP and KISLINE which both allow to view company (financial) information and credit information, but there exists no online system that provides a list of similar (competitive) companies based on the analysis of value chain network or information on potential clients or demanders that can have business deals in future. Therefore, we focus on the "Value Chain Network System (VCNS)", a support partner for planning the corporate business strategy developed and managed by KISTI, and investigate the types of embedded network-based analysis modules, databases (D/Bs) to support them, and how to utilize the system efficiently. Further we explore the function of network visualization in intelligent value chain analysis system which becomes the core information to understand industrial structure ystem and to develop a company's new product development. In order for a company to have the competitive superiority over other companies, it is necessary to identify who are the competitors with patents or products currently being produced, and searching for similar companies or competitors by each type of industry is the key to securing competitiveness in the commercialization of the target company. In addition, transaction information, which becomes business activity between companies, plays an important role in providing information regarding potential customers when both parties enter similar fields together. Identifying a competitor at the enterprise or industry level by using a network map based on such inter-company sales information can be implemented as a core module of value chain analysis. The Value Chain Network System (VCNS) combines the concepts of value chain and industrial structure analysis with corporate information simply collected to date, so that it can grasp not only the market competition situation of individual companies but also the value chain relationship of a specific industry. Especially, it can be useful as an information analysis tool at the corporate level such as identification of industry structure, identification of competitor trends, analysis of competitors, locating suppliers (sellers) and demanders (buyers), industry trends by item, finding promising items, finding new entrants, finding core companies and items by value chain, and recognizing the patents with corresponding companies, etc. In addition, based on the objectivity and reliability of the analysis results from transaction deals information and financial data, it is expected that value chain network system will be utilized for various purposes such as information support for business evaluation, R&D decision support and mid-term or short-term demand forecasting, in particular to more than 15,000 member companies in Korea, employees in R&D service sectors government-funded research institutes and public organizations. In order to strengthen business competitiveness of companies, technology, patent and market information have been provided so far mainly by government agencies and private research-and-development service companies. This service has been presented in frames of patent analysis (mainly for rating, quantitative analysis) or market analysis (for market prediction and demand forecasting based on market reports). However, there was a limitation to solving the lack of information, which is one of the difficulties that firms in Korea often face in the stage of commercialization. In particular, it is much more difficult to obtain information about competitors and potential candidates. In this study, the real-time value chain analysis and visualization service module based on the proposed network map and the data in hands is compared with the expected market share, estimated sales volume, contact information (which implies potential suppliers for raw material / parts, and potential demanders for complete products / modules). In future research, we intend to carry out the in-depth research for further investigating the indices of competitive factors through participation of research subjects and newly developing competitive indices for competitors or substitute items, and to additively promoting with data mining techniques and algorithms for improving the performance of VCNS.