• Journal of Distribution Research
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• v.15 no.2
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• pp.71-99
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• 2010

Most of studies on patriotism in the marketing area have focused on ethnocentric tendencies observed in consumption behaviors. On the contrary, there have been few empirical studies on how patriotism in the general sense, indicating affection for, attachment to, and pride in the country, influences consumers' evaluation of domestic and foreign products. Given the current situation that marketing activities appealing to people's patriotism is increasing, this is somewhat surprising. Thus, this study examined empirically how patriotism influences people's evaluation of domestic and foreign products. In addition, we tested whether consumer ethnocentrism works as an intervening variable in the relation between patriotism and product evaluation. The empirical analysis was conducted through a questionnaire survey of undergraduate and graduate students at universities in Seoul. The survey asked about the respondents' patriotism, consumer ethnocentrism, domestic product evaluation, foreign product evaluation, and demographical characteristics. In foreign product evaluation, the respondents were requested to evaluate Chinese and Japanese products. Email was used to send and recover the questionnaires, and 135 replies were used in the analysis. Major findings from the empirical analysis are as follows. First, a significant relationship was observed between patriotism and domestic product evaluation. That is, patriotic participants evaluated domestic products more favorably. On the other hand, no significant relationship was observed between patriotism and foreign product evaluation(See Table 1-1 and 1-2). Next, the effect of patriotism on domestic product evaluation was mediated by consumer ethnocentrism. However, whether the effect of patriotism on domestic product evaluation is mediated by consumer ethnocentrism partially or fully was different according to product(See Table 2-1 and 2-2). Lastly, we tried to analyze the relation between consumer ethnocentrism and product evaluation and comparing the results with findings of previous researches. According to the results, a significant relationship was observed between consumer ethnocentrism and domestic product evaluation but not between consumer ethnocentrism and foreign product evaluation. The meanings of this study are as follows. First, there have been few marketing studies that investigated the relation between patriotism and product evaluation. Thus, this study is meaningful in that it supplemented the limitation of previous research. Second, consumer ethnocentrism was found to mediate the relation between patriotism and domestic product evaluation. Considering the absence of previous research that examined the role of consumer ethnocentrism as an intervening variable, this study is significant in that it expanded the scope of research on consumer ethnocentrism. Third, from the practical aspect, the results of this study suggest that marketing appealing to patriotism is effective in stimulating consumers' purchase and consumption of domestic products. Accordingly, such a marketing strategy is expected to be effective in protecting domestic markets from imported goods and overseas brands and to increase demands for domestic products and brands. However, there is the question of whether the effect of patriotism based marketing strategies in promoting demand for domestic products would persist. That is, this study could not find a significant relation between patriotism and foreign product evaluation, and this means that the increase in patriotism for the home country does not damage people's view to the quality of foreign products negatively. Accordingly, without change in people's perception of foreign products, it is highly likely that the increase in demand for domestic products or brands induced by patriotism elevated at a specific time or situation may not last long. Fourth, the results of this study suggest that the patriotism level may influence consumers' choice behavior toward retailers strongly connected to a specific country or region. That is, consumers with high level patriotism may hesitate or avoid using a retailer associated with some foreign country. Fifth, according to the results of this study, when people's patriotism is stimulated by a specific social situation or event, it can be an opportunity for domestic franchise brands to increase their market performance such as sales and market share and, at the same time, for foreign franchise brands to experience adversities. Therefore, during a period like the Olympic Games or the World Cup when people's sense of belonging or attachment to their country is heightened, domestic franchise brands need to make marketing activities that may lead market opportunities to substantial results and foreign franchise brands to cope with such adversities. Sixth, consumers' brand choice is often made in retail stores. It has been demonstrated by numerous studies that in store stimuli such as point of purchase display can affect consumers' behavior. Considering this, domestic brands facing competition with foreign brands should make continuous efforts to enhance the market performance of their products through developing in store stimuli that can stimulate consumers' patriotism. Finally, based on the major findings of this study, both academic and practical issues were discussed. Suggestions for future studies were provided.

• Journal of Intelligence and Information Systems
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• v.18 no.4
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• pp.43-57
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• 2012

To enhance the competitive advantage in a constantly changing business environment, an enterprise management must make the right decision in many business activities based on both internal and external information. Thus, providing accurate information plays a prominent role in management's decision making. Intuitively, historical data can provide a feasible estimate through the forecasting models. Therefore, if the service department can estimate the service quantity for the next period, the service department can then effectively control the inventory of service related resources such as human, parts, and other facilities. In addition, the production department can make load map for improving its product quality. Therefore, obtaining an accurate service forecast most likely appears to be critical to manufacturing companies. Numerous investigations addressing this problem have generally employed statistical methods, such as regression or autoregressive and moving average simulation. However, these methods are only efficient for data with are seasonal or cyclical. If the data are influenced by the special characteristics of product, they are not feasible. In our research, we propose a forecasting framework that predicts service demand of manufacturing organization by combining Case-based reasoning (CBR) and leveraging an unsupervised artificial neural network based clustering analysis (i.e., Self-Organizing Maps; SOM). We believe that this is one of the first attempts at applying unsupervised artificial neural network-based machine-learning techniques in the service forecasting domain. Our proposed approach has several appealing features : (1) We applied CBR and SOM in a new forecasting domain such as service demand forecasting. (2) We proposed our combined approach between CBR and SOM in order to overcome limitations of traditional statistical forecasting methods and We have developed a service forecasting tool based on the proposed approach using an unsupervised artificial neural network and Case-based reasoning. In this research, we conducted an empirical study on a real digital TV manufacturer (i.e., Company A). In addition, we have empirically evaluated the proposed approach and tool using real sales and service related data from digital TV manufacturer. In our empirical experiments, we intend to explore the performance of our proposed service forecasting framework when compared to the performances predicted by other two service forecasting methods; one is traditional CBR based forecasting model and the other is the existing service forecasting model used by Company A. We ran each service forecasting 144 times; each time, input data were randomly sampled for each service forecasting framework. To evaluate accuracy of forecasting results, we used Mean Absolute Percentage Error (MAPE) as primary performance measure in our experiments. We conducted one-way ANOVA test with the 144 measurements of MAPE for three different service forecasting approaches. For example, the F-ratio of MAPE for three different service forecasting approaches is 67.25 and the p-value is 0.000. This means that the difference between the MAPE of the three different service forecasting approaches is significant at the level of 0.000. Since there is a significant difference among the different service forecasting approaches, we conducted Tukey's HSD post hoc test to determine exactly which means of MAPE are significantly different from which other ones. In terms of MAPE, Tukey's HSD post hoc test grouped the three different service forecasting approaches into three different subsets in the following order: our proposed approach > traditional CBR-based service forecasting approach > the existing forecasting approach used by Company A. Consequently, our empirical experiments show that our proposed approach outperformed the traditional CBR based forecasting model and the existing service forecasting model used by Company A. The rest of this paper is organized as follows. Section 2 provides some research background information such as summary of CBR and SOM. Section 3 presents a hybrid service forecasting framework based on Case-based Reasoning and Self-Organizing Maps, while the empirical evaluation results are summarized in Section 4. Conclusion and future research directions are finally discussed in Section 5.

• KDI Journal of Economic Policy
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• v.30 no.1
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• pp.1-31
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• 2008

Various opinions have been suggested to explain the slump in equipment investment, such as increased government regulations, shareholder-oriented management by expanded foreign equity investment, response against M&A threats, conservative investment trends seen after a series of bankruptcy of large conglomerates (amidst crumbling myth of "Too Big to Fail"), and financial restructuring. Some also argued that the increased uncertainty in business environment is mainly responsible for conservative management, though there are few domestic studies made regarding the situation. But, in other countries, including the U.S., studies have shown that more volatility is seen now surrounding stock prices, profitability, and sales growth rate reflecting business performance. Also, there are other studies showing such expanded volatility have led to conservative management by businesses. In this regard, this study reviews the volatility conditions of business performance of Korean companies based on profitability, and then attempts to analyze the impact on investment brought on by increased volatility. Each company's profitability volatility used here is from the standard deviation of companies for the past five years. As a profitability indicator, the ROA (= operating profit/total asset) is used. According to the analysis, profitability volatility has remarkably increased from the mid 3% in 1994 to low 5% in 2005. Profitability volatility of the Korean companies has expanded to a great extent since the financial crisis. The crisis might have served to raise the volatility in the macroeconomic conditions. If increased volatility observed during the economic crisis had gradually declined after the crisis, the situation could be interpreted as a temporary phenomenon, not to be too concerned over. But, this was not the case for Korea. The volatility level, after the crisis, has not dropped back to its pre-crisis level. Hence, in the Korea's case, high volatility cannot be explained by the impact of financial crisis. Not only that, the fact that such expansion is seen in every industrial sector indicates that this phenomenon cannot be explained by the composition change of industries alone. An undergoing study shows that with a rapid spread of globalization, industries fiercely competing with China experience more volatility. Such increased volatility tends to contract investment, and since the crisis the impact of volatility on investment has slightly increased. It is noteworthy that this study only includes a part of 'uncertainty' that could be measured statistically. For instance, the profitability volatility indicator used in this study is unable to reflect all the effects that the tacit reduction of protection by the government or regulations might have made. So, the result here also indicates that other 'uncertain' factors not mentioned in this study may have served to contract investment sentiment. It would be impossible for policies to completely remove uncertainties measured by profitability volatility, but at least it is necessary to put effort to reduce the macroeconomic volatility in the future economic management. Stabilized macroeconomic management may not be enough to diminish all volatility that occurs within each company, but it would make a meaningful contribution in encouraging investment.

• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.123-136
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• 2014

Recently, online shopping has further developed as the use of the Internet and a variety of smart mobile devices becomes more prevalent. The increase in the scale of such shopping has led to the creation of many Internet shopping malls. Consequently, there is a tendency for increasingly fierce competition among online retailers, and as a result, many Internet shopping malls are making significant attempts to attract online users to their sites. One such attempt is keyword marketing, whereby a retail site pays a fee to expose its link to potential customers when they insert a specific keyword on an Internet portal site. The price related to each keyword is generally estimated by the keyword's frequency of appearance. However, it is widely accepted that the price of keywords cannot be based solely on their frequency because many keywords may appear frequently but have little relationship to shopping. This implies that it is unreasonable for an online shopping mall to spend a great deal on some keywords simply because people frequently use them. Therefore, from the perspective of shopping malls, a specialized process is required to extract meaningful keywords. Further, the demand for automating this extraction process is increasing because of the drive to improve online sales performance. In this study, we propose a methodology that can automatically extract only shopping-related keywords from the entire set of search keywords used on portal sites. We define a shopping-related keyword as a keyword that is used directly before shopping behaviors. In other words, only search keywords that direct the search results page to shopping-related pages are extracted from among the entire set of search keywords. A comparison is then made between the extracted keywords' rankings and the rankings of the entire set of search keywords. Two types of data are used in our study's experiment: web browsing history from July 1, 2012 to June 30, 2013, and site information. The experimental dataset was from a web site ranking site, and the biggest portal site in Korea. The original sample dataset contains 150 million transaction logs. First, portal sites are selected, and search keywords in those sites are extracted. Search keywords can be easily extracted by simple parsing. The extracted keywords are ranked according to their frequency. The experiment uses approximately 3.9 million search results from Korea's largest search portal site. As a result, a total of 344,822 search keywords were extracted. Next, by using web browsing history and site information, the shopping-related keywords were taken from the entire set of search keywords. As a result, we obtained 4,709 shopping-related keywords. For performance evaluation, we compared the hit ratios of all the search keywords with the shopping-related keywords. To achieve this, we extracted 80,298 search keywords from several Internet shopping malls and then chose the top 1,000 keywords as a set of true shopping keywords. We measured precision, recall, and F-scores of the entire amount of keywords and the shopping-related keywords. The F-Score was formulated by calculating the harmonic mean of precision and recall. The precision, recall, and F-score of shopping-related keywords derived by the proposed methodology were revealed to be higher than those of the entire number of keywords. This study proposes a scheme that is able to obtain shopping-related keywords in a relatively simple manner. We could easily extract shopping-related keywords simply by examining transactions whose next visit is a shopping mall. The resultant shopping-related keyword set is expected to be a useful asset for many shopping malls that participate in keyword marketing. Moreover, the proposed methodology can be easily applied to the construction of special area-related keywords as well as shopping-related ones.

• Journal of Intelligence and Information Systems
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• v.21 no.1
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• pp.161-177
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• 2015

With the rapid evolution of technology, the size, number, and the type of databases has increased concomitantly, so data mining approaches face many challenging applications from databases. One such application is discovery of fraud patterns from agricultural product wholesale transaction instances. The agricultural product wholesale market in Korea is huge, and vast numbers of transactions have been made every day. The demand for agricultural products continues to grow, and the use of electronic auction systems raises the efficiency of operations of wholesale market. Certainly, the number of unusual transactions is also assumed to be increased in proportion to the trading amount, where an unusual transaction is often the first sign of fraud. However, it is very difficult to identify and detect these transactions and the corresponding fraud occurred in agricultural product wholesale market because the types of fraud are more intelligent than ever before. The fraud can be detected by verifying the overall transaction records manually, but it requires significant amount of human resources, and ultimately is not a practical approach. Frauds also can be revealed by victim's report or complaint. But there are usually no victims in the agricultural product wholesale frauds because they are committed by collusion of an auction company and an intermediary wholesaler. Nevertheless, it is required to monitor transaction records continuously and to make an effort to prevent any fraud, because the fraud not only disturbs the fair trade order of the market but also reduces the credibility of the market rapidly. Applying data mining to such an environment is very useful since it can discover unknown fraud patterns or features from a large volume of transaction data properly. The objective of this research is to empirically investigate the factors necessary to detect fraud transactions in an agricultural product wholesale market by developing a data mining based fraud detection model. One of major frauds is the phantom transaction, which is a colluding transaction by the seller(auction company or forwarder) and buyer(intermediary wholesaler) to commit the fraud transaction. They pretend to fulfill the transaction by recording false data in the online transaction processing system without actually selling products, and the seller receives money from the buyer. This leads to the overstatement of sales performance and illegal money transfers, which reduces the credibility of market. This paper reviews the environment of wholesale market such as types of transactions, roles of participants of the market, and various types and characteristics of frauds, and introduces the whole process of developing the phantom transaction detection model. The process consists of the following 4 modules: (1) Data cleaning and standardization (2) Statistical data analysis such as distribution and correlation analysis, (3) Construction of classification model using decision-tree induction approach, (4) Verification of the model in terms of hit ratio. We collected real data from 6 associations of agricultural producers in metropolitan markets. Final model with a decision-tree induction approach revealed that monthly average trading price of item offered by forwarders is a key variable in detecting the phantom transaction. The verification procedure also confirmed the suitability of the results. However, even though the performance of the results of this research is satisfactory, sensitive issues are still remained for improving classification accuracy and conciseness of rules. One such issue is the robustness of data mining model. Data mining is very much data-oriented, so data mining models tend to be very sensitive to changes of data or situations. Thus, it is evident that this non-robustness of data mining model requires continuous remodeling as data or situation changes. We hope that this paper suggest valuable guideline to organizations and companies that consider introducing or constructing a fraud detection model in the future.

• Journal of Global Scholars of Marketing Science
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• v.17 no.4
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• pp.23-49
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• 2007

Salespeople act at the point of MOT with customers and deliver the enterprise's message to the customers. They build up relationships with customers as well as deliver the customer's message to the enterprise. The salespeople's activity at the point of MOT with the customers and the degree of satisfaction of the customers' needs will affect the customers' attitude toward the enterprise, brand loyalty, and retention intention. Ultimately, it will influence the enterprise's financial performance. The control of salespe1ople is one of the most interesting topics of marketing. This research investigates the relationships of the control types over salespeople(positive/negative outcome control, positive/negative behavior control) and job satisfaction and their mediating variables. The mediating variables in the relationships have been identified as outcome/behavior-related role clarity and self-efficacy. The purpose of this study is more specifically as follows: First, it investigate how the perception of salespeople control types affect role-clarity. Second, it examines how the perception of salespeople control types influence self-efficacy. Third, it investigate the mediating role of role-clarity between the perception of salespeople control types and self-efficacy. Fourth, it investigates how role-clarity affect self-efficacy and job satisfaction. Finally, it will investigates how self-efficacy influences job satisfaction. Data were collected from the pharmaceutical industry salespeople and analyzed by SPSS 12.0 and AMOS　6.0. The data were collected by 400 respondents and 377 valid questionnaires were analyzed. The results are summarized as follows: First, positive/negative outcome controls had a positive relationship with outcome-related role clarity. Also positive behavior control had a positive effect on behavior-related role clarity, but negative behavior control didn't influence behavior-related role clarity. Second, positive outcome control influenced self-efficacy positively, but positive behavior control didn't have a positive effect on self-efficacy. In addition negative outcome control and negative behavior control had a positive effect on self-efficacy due to the mediating role of outcome-related and behavior-related role clarity. Third, outcome-related role clarity and behavior-related role clarity influenced self-efficacy positively. Behavior-related role clarity had a positive effect on job satisfaction, but outcome-related role clarity didn't influence job satisfaction. Finally, self-efficacy didn't have any effect on job satisfaction. The contributions of this study are as follows: First, existing studies have investigated the direct causal relationship between salespeoples' control type and performance, but this study investigates the structural causality between salespeoples' control types, responses, and performances. Second, this study found the mediating role of outcome-related/behavior-related role-clarity between outcome/behavior control and self-efficacy. Finally, the findings of this study further insight to existing studies on the relationship between job satisfaction and self-efficacy. The confidence of salespeoples' task influenced job satisfaction positively in existing articles,field studies, but the relationship between these two variables was not significant in this study. This means that there can be a different relationship between confidence and job satisfaction according to salespeoples' business. That is, the business environment may not be satisfying, even if the salespeople say that they have ability and confidence about their business. This means that able salespeople who have ability and confidence about their business are not satisfied with their job advancement in the company. Therefore, enterprise need to provide training that can establish a business environment that can satisfy the salespeole's expectation level which will secure good salespeople. This study may have limitation when applied to future studies. First,in this study as with existing studies it investigates the control level that salespeople feel is being measured. Actuality, the control level that a manager enforces and the control level that salespeople perceive when one is late can be different. There is need to measure lateness from both the perspective of the manager and salespeople should be done to supplement this study in the future Second, this study used variables that were connected with action result but salespeople's job satisfaction is due to the result of control. But, focusing on result of control can provide a more important financial result than sales performance. This study is also limited in that it did not consider financial result by result of control. Further studies on this will need to be done in the future. Third, this study may have a further limitation,because the investigation was restricted to pharmaceutical salespeople selling to hospitals. It is necessary to execute investigations in various industries to increase the generalization of the study findings Fourth, in this study, role clarity and self-efficacy by response variable for control and considered job satisfaction by outcome variable of control was considered. But, can other variables be considered beside response variable and result variable for control? For example, can financial affairs and change of post by outcome variable along with business stress by response variable for control be considered? Therefore, future studies need to consider various control variables. Finally, there is limited supporting research in the field of marketing which restricts the generalization of the study finding along with collecting material through random sampling of a limited size. This research summarizes the research in this area, the difference from the previous research, and provides a discussion of its limitations and the need and direction for further future research.

• Journal of Intelligence and Information Systems
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• v.22 no.1
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• pp.63-82
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• 2016

Individuals gather information online to resolve problems in their daily lives and make various decisions about the purchase of products or services. With the revolutionary development of information technology, Web 2.0 has allowed more people to easily generate and use online reviews such that the volume of information is rapidly increasing, and the usefulness and significance of analyzing the unstructured data have also increased. This paper presents an analysis on the lexical features of expert product reviews to determine their influence on consumers' purchasing decisions. The focus was on how unstructured data can be organized and used in diverse contexts through text mining. In addition, diverse lexical features of expert reviews of contents provided by a third-party review site were extracted and defined. Expert reviews are defined as evaluations by people who have expert knowledge about specific products or services in newspapers or magazines; this type of review is also called a critic review. Consumers who purchased products before the widespread use of the Internet were able to access expert reviews through newspapers or magazines; thus, they were not able to access many of them. Recently, however, major media also now provide online services so that people can more easily and affordably access expert reviews compared to the past. The reason why diverse reviews from experts in several fields are important is that there is an information asymmetry where some information is not shared among consumers and sellers. The information asymmetry can be resolved with information provided by third parties with expertise to consumers. Then, consumers can read expert reviews and make purchasing decisions by considering the abundant information on products or services. Therefore, expert reviews play an important role in consumers' purchasing decisions and the performance of companies across diverse industries. If the influence of qualitative data such as reviews or assessment after the purchase of products can be separately identified from the quantitative data resources, such as the actual quality of products or price, it is possible to identify which aspects of product reviews hamper or promote product sales. Previous studies have focused on the characteristics of the experts themselves, such as the expertise and credibility of sources regarding expert reviews; however, these studies did not suggest the influence of the linguistic features of experts' product reviews on consumers' overall evaluation. However, this study focused on experts' recommendations and evaluations to reveal the lexical features of expert reviews and whether such features influence consumers' overall evaluations and purchasing decisions. Real expert product reviews were analyzed based on the suggested methodology, and five lexical features of expert reviews were ultimately determined. Specifically, the "review depth" (i.e., degree of detail of the expert's product analysis), and "lack of assurance" (i.e., degree of confidence that the expert has in the evaluation) have statistically significant effects on consumers' product evaluations. In contrast, the "positive polarity" (i.e., the degree of positivity of an expert's evaluations) has an insignificant effect, while the "negative polarity" (i.e., the degree of negativity of an expert's evaluations) has a significant negative effect on consumers' product evaluations. Finally, the "social orientation" (i.e., the degree of how many social expressions experts include in their reviews) does not have a significant effect on consumers' product evaluations. In summary, the lexical properties of the product reviews were defined according to each relevant factor. Then, the influence of each linguistic factor of expert reviews on the consumers' final evaluations was tested. In addition, a test was performed on whether each linguistic factor influencing consumers' product evaluations differs depending on the lexical features. The results of these analyses should provide guidelines on how individuals process massive volumes of unstructured data depending on lexical features in various contexts and how companies can use this mechanism from their perspective. This paper provides several theoretical and practical contributions, such as the proposal of a new methodology and its application to real data.

• Cartoon and Animation Studies
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• s.33
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• pp.597-616
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• 2013

Character industry is not only knowledge-based industry chiefly with copyrights but also motive power for creative economy to take a role functionally over the fields of industries because it has industrial characteristic as complement product to promote sale value in manufacturing industry and service industry and increase profit on sales. Since 2003, the national policy related to character has aimed to maximize effect among connected industries, extend its business abroad, enforce copyrights through the improvement of marketing system, develop industrial infrastructure through raising quality of character products. With the result of this policy, the successful cases of connected contents have been crystallized and domestic character industry has stepped up methodically since 2007. It is needed to reset the scales of character industry and industrial stats because there are more know-how of self industry promotion and more related characters through strategy of market departmentalization starting with cartoon, animation, games, novels, movies and musicals. Especially, The Korea government set our target for 'Global Top Five Character Power' since 2009 and has started to carry out to find global star characters, support to establish network among connected industries, diversify promotion channels, and develop licensing business. Particularly, since 2013, There have been prospered the indoor character theme park with time management just like character experimental marketing or Kids cafes using characters, the demand market of digital character focusing on SNS emoticon, and the performance market for character musical consistently. Moreover, The domestic and foreign illegal black markets on off-line have been enlarged, so we need another policy alternative. To prepare for the era of exploding character demand market and diversifying platform, it is needed to set up a solid strategy that is required the elements of policy changes in character industry to vitalize character industry and support new character design and connected contents. the following shows that the elements of policy changes related to the existing policy, the current position of market. Nowadays, the elements of policy changes in domestic character industry are that variety of consumers in the digital character market according to platform diversification, Convergence contents of character goods for the Korean waves, legalization of the illegal black contents market, and controling the tendency of consumers in departmentalized market. This can help find the policy issue entirely deferent with the existing character powers like US, Japan or Europe. In its final analysis, the alternatives are the promotion of models with contract copyrights of domestic and foreign connected contents, the diversification of profit models of platform economy, the additive development of target market related to enlarging the Korean waves, and the strategy of character market for the age-specific tendency according to developing character demand market.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.13 no.3
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• pp.125-140
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• 2018

According to statistics, it is shown that domestic SMEs rely on bank loans for the majority of fund procurement. From financial information shortage (Thin file) that does not provide information necessary for credit evaluation from banks such as financial statements. In order to overcome these problems, recently, in alternative finance such as P2P, using differentiated information such as demographics, trading information and the like utilizing Fintech instead of existing financial information, small funds A new credit evaluation method has been expanding to provide SMEs with small amounts of money. In this paradigm of environmental change, in this research, credit evaluation which can expand fund supply to SMEs by utilizing big data based on trade area information such as sales fluctuation, location conditions etc. In this research, we try to find such a solution. By analyzing empirically the big data generated in the trade area, we verify the effectiveness as a credit evaluation factor and try to derive the main parameters necessary for the business performance evaluation of the founder of SMEs. In this research, for 17,116 material businesses in Seoul City that operate the service industry from 2009 to February 2018, we collect trade area information generated for each business location from Big Data specialized company NICE Zini Data Co., Ltd.. We collected and analyzed the data on the locations and commercial areas of the facilities that were difficult to obtain from SMEs and analyzed the data that affected the Corporate financial Distress. It is possible to refer to the variable of the existing unused big data and to confirm the possibility of utilizing it for efficient financial support for SMEs, This is to ensure that commercial lenders, even in general commercial banks, are made to be more prominent in one sector of the financing of SMEs. In this research, it is not the traditional financial information about raising fund of SMEs who have basically the problem of information asymmetry, but a trade area analysis variable is derived, and this variable is evaluated by credit evaluation There is differentiation of research in that it verified through analysis of big data from Trading-area whether or not there is an effect on.

• Korean Security Journal
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• no.36
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• pp.177-200
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• 2013

As we enter a high industrial society that widens the gap between the rich and poor, demand for the security services has grown explosively. With the growth in quantitative expansion of security services, people have also placed increased requirements on more sophisticated and diversified security services. Consequently, market outlook for private security services industry is positive. However, Korea's private security services companies are experiencing difficulties in finding a direction to capture this new market opportunity due to their small sizes and lack of management-strategic thinking skills. Therefore, we intend to offer a direction of development for our private security services industry using a management-strategy theory and the Analytic Hierarchy Process(AHP), a structured decision-making method. A resource-based theory is one of the important management strategy theories. It explains that a company's overall performance is primarily determined by its competitive resources. Using this theory, we could analyze a company's unique resources and core competencies and set a strategic direction for the company accordingly. The usefulness and validity of this theory has been demonstrated as it has often been subject to empirical verification since 1990s. Based on this theory, we outlined a set of basic procedures to establish a management strategy for the private security services companies. We also used the AHP method to identify competitive resources, core competencies, and strategies from private security services companies in contrast with public companies. The AHP method is a technique that can be used in the decision making process by quantifying experts' knowledge and unstructured problems. This is a verified method that has been used in the management decision making in the corporate environment as well as for the various academic studies. In order to perform this method, we gathered data from 11 experts from academic, industrial, and research sectors and drew distinctive resources, competencies, and strategic direction for private security services companies vis-a-vis public organizations. Through this process, we came to the conclusion that private security services companies generally have intangible resources as their distinctive resources compared with public organization. Among those intangible resources, relational resources, customer information, and technologies were analyzed as important. In contrast, tangible resources such as equipment, funds, distribution channels are found to be relatively scarce. We also found the competencies in sales and marketing and new product development as core competencies. We chose a concentration strategy focusing on a particular market segment as a strategic direction considering these resources and competencies of private security services companies. A concentration strategy is the right fit for smaller companies as a strategy to allow them to focus all of their efforts on target customers in a single segment. Thus, private security services companies would face the important tasks such as developing a new market and appropriate products for such market segment and continuing marketing activities to manage their customers. Additionally, continuous recruitment is required to facilitate the effective use of human resources in order to strengthen their marketing competency in a long term.