• Journal of the Korean Geographical Society
• /
• v.44 no.4
• /
• pp.532-543
• /
• 2009

The foodservice franchise is preferred by the founders who inaugurate a business enterprise, because it is not difficult to convert into money more than other private enterprise. The success or failure of the foodservice franchise depends 80 percent on its location. Therefore, this research aimed to study the location factors of the first shops of foodservice franchise in Seoul through the analyses of nearest neighborhood effect and statistical relationship between variables. According to there results, the location characteristics of the first shops of foodservice franchise are summarized as in the following three items. First, the spatial distribution pattern of the first shops is a clustered type. Second, the first shops relate to the 15 variables which are the number of financial facilities, the number of business service offices, and the number of hotels and restaurants, etc. Third, the main location factor of the first shops is the number of financial facilities. In conclusion, it is estimated that Gangnam-gu and Jung-gu might be good for the location of the first shops of foodservice franchise in Seoul, because these two places have many financial buildings.

• CRM연구
• /
• v.2 no.2
• /
• pp.41-51
• /
• 2009

VIP marketing has recently become the main concern in the field of marketing, which could increase customer loyalty and sales through providing customers in the top 20% with customized services. In this study, some cases of RFID (Radio Frequency Identification) technology based VIP channel management are introduced and analyzed in the technology point of view. As a result of case studies, it has been shown what the companies may consider when applying RFID technology in customer relationship management (CRM) and its general scenario. As one of the AIDC(Automatic Identification and Data Capture) technologies, RFID can enable to identify humans or objects with radio frequency and is being widely used to many industrial areas such as logistics, delivery, inventory management, and so on. If this technology is applied to CRM as a new channel for customer management, it will be possible to provide an individual customer with various types of intelligent services customized to his or her spending habits. RFID for CRM channel management is still in its early stages, but it is sure that RFID technology will be an useful tool to manage customers including especially VIP in many businesses and capture important information applicable to marketing campaign in the near future.

• Journal of Service Research and Studies
• /
• v.6 no.3
• /
• pp.91-105
• /
• 2016

Today the beauty industry has reached a point of saturation, and competition has become fiercer than ever. Furthermore, customer needs and expectations have become increasingly sophisticated and diversified. In particular, it has become more difficult for small beauty salons to maintain customer loyalty by staying competitive and satisfying customer needs and demand. In fact, beauty salon customers want to get individualized services as well as a wide variety of hairstyles. Therefore, this study attempted to analyze the sustainability management of beauty salons. It looked at how an increase in sales and in customer loyalty can be achieved by enhancing awareness of the fact that small beauty salons' competitiveness stems from strenuous efforts for the best customer service, individualized hairstyling services, professional skills and customer trust. The study results found that beauty salons need to keep promoting development and improvement for the following: advanced skills, excellent services, reasonable price, convenient locations, advertisement and PR, development of an exclusive manual, intensive staff training and character education plan, complaint management and follow-up and decrease in customer migration.

• Smart Media Journal
• /
• v.11 no.4
• /
• pp.62-68
• /
• 2022

To prevent the spread of disease in aquaculture, it is a need for a system to predict fish diseases while monitoring the water quality environment and the status of growing fish in real time. The existing research in predicting fish disease were image processing techniques. Recently, there have been more studies on disease prediction methods through deep learning techniques. This paper introduces the research results on how to predict diseases of Paralichthys Olivaceus with deep learning technology in aquaculture. The method enhances the performance of disease detection rates by including data augmentation and pre-processing in camera images collected from aquaculture. In this method, it is expected that early detection of disease fish will prevent fishery disasters such as mass closure of fish in aquaculture and reduce the damage of the spread of diseases to local aquaculture to prevent the decline in sales.

• Journal of Intelligence and Information Systems
• /
• v.20 no.4
• /
• pp.1-23
• /
• 2014

Market forecasting aims to estimate the sales volume of a product or service that is sold to consumers for a specific selling period. From the perspective of the enterprise, accurate market forecasting assists in determining the timing of new product introduction, product design, and establishing production plans and marketing strategies that enable a more efficient decision-making process. Moreover, accurate market forecasting enables governments to efficiently establish a national budget organization. This study aims to generate a market growth curve for ICT (information and communication technology) goods using past time series data; categorize products showing similar growth patterns; understand markets in the industry; and forecast the future outlook of such products. This study suggests the useful and meaningful process (or methodology) to identify the market growth pattern with quantitative growth model and data mining algorithm. The study employs the following methodology. At the first stage, past time series data are collected based on the target products or services of categorized industry. The data, such as the volume of sales and domestic consumption for a specific product or service, are collected from the relevant government ministry, the National Statistical Office, and other relevant government organizations. For collected data that may not be analyzed due to the lack of past data and the alteration of code names, data pre-processing work should be performed. At the second stage of this process, an optimal model for market forecasting should be selected. This model can be varied on the basis of the characteristics of each categorized industry. As this study is focused on the ICT industry, which has more frequent new technology appearances resulting in changes of the market structure, Logistic model, Gompertz model, and Bass model are selected. A hybrid model that combines different models can also be considered. The hybrid model considered for use in this study analyzes the size of the market potential through the Logistic and Gompertz models, and then the figures are used for the Bass model. The third stage of this process is to evaluate which model most accurately explains the data. In order to do this, the parameter should be estimated on the basis of the collected past time series data to generate the models' predictive value and calculate the root-mean squared error (RMSE). The model that shows the lowest average RMSE value for every product type is considered as the best model. At the fourth stage of this process, based on the estimated parameter value generated by the best model, a market growth pattern map is constructed with self-organizing map algorithm. A self-organizing map is learning with market pattern parameters for all products or services as input data, and the products or services are organized into an $N{\times}N$ map. The number of clusters increase from 2 to M, depending on the characteristics of the nodes on the map. The clusters are divided into zones, and the clusters with the ability to provide the most meaningful explanation are selected. Based on the final selection of clusters, the boundaries between the nodes are selected and, ultimately, the market growth pattern map is completed. The last step is to determine the final characteristics of the clusters as well as the market growth curve. The average of the market growth pattern parameters in the clusters is taken to be a representative figure. Using this figure, a growth curve is drawn for each cluster, and their characteristics are analyzed. Also, taking into consideration the product types in each cluster, their characteristics can be qualitatively generated. We expect that the process and system that this paper suggests can be used as a tool for forecasting demand in the ICT and other industries.

• Cross-Cultural Studies
• /
• v.50
• /
• pp.395-424
• /
• 2018

The purpose of this paper is to examine the current situation and background of the Russian consumer music market, where digital music sources are making great strides in the noted recent years. In addition, music storage technology, media and change are considered together in this report. Moreover, Russia is the 12th largest music market in the world. The Russian music industry is following the recent trend of the global music industry, where the digital music market is growing rapidly on many different levels. The explosive growth of the digital sound sources in Russia's music industry is attributed to the explosive increase in available consumer downloads, streaming sound source service, and the increase in the number of digital sound sources using mobile technologies due to the development of the Internet. In particular, the sales of the available and accessible streaming sound sources are expected to grow explosively by the year 2020, which is expected to account for more than 85% of total digital music sales. In other words, the spread of smartphones and the resulting changes in the lifestyle of the Russians have created these changes for the global consumer of music. In other words, the time has come for anyone to easily access music and listen to music without a separate audio or digital player. And the fact that the Russian government's strong policy on the eradication of illegal copying of music is becoming an effective deterrent, as is also the factor that led to the increase of the share of the digital sound source to increase sales in Russia. Today, the Russian music industry is leading this change through the age and process of simply adapting to the digital age. Music is the most important element of cultural assets, and it is the beneficial content, which drives the overall growth of the digital economy. In addition, if the following five improvements(First, strengthen the consciousness of the Russian people about copyright protection; Second, utilizing the Big Data Internet resources in the digital music industry; Third, to improve the monopoly situation of digital music distributors; Fourth, distribution of fair music revenues; and Fifth, revitalization of a re-investment in the current Russian music industry) are effective and productive, Russia's role and position in the world music market is likely to expand.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
• /
• v.9 no.5
• /
• pp.103-114
• /
• 2014

The concept of entrepreneurial orientation has been recognized as a key driver for success of business ventures. Since small and medium-sized business ventures usually lack in business experience, firm level entrepreneurship seems to play an important role in generating firm performance. Following those logics, traditional approaches assumed that the relationship between entrepreneurial orientation and firm performance is linear, but recently studies start to report non-linear relationships. However, only a few researches examines and compares the performance effects of entrepreneurial orientation with diverse performance indicators. Current study explores the effects of entrepreneurial orientation both on financial and innovative performance with 1,497 Korean small and medium-sized business ventures. This study finds that there is a linear relationship between entrepreneurial orientation and financial performance, but inverted U-shaped relationships between entrepreneurial orientation and innovative performance, measured by product novelty and patent issued. Also those relationship patterns are consistent with different measurement of entrepreneurial orientation. Based on these results, theoretical implications with some limitations are discussed.

• Journal of the Economic Geographical Society of Korea
• /
• v.14 no.3
• /
• pp.307-324
• /
• 2011

The culture industry is viewed as a driving industry in the 21th century. Korea has experienced the rapid growth rate of the cultural industry in terms of sale amounts for the period of 2004-2009. The purposes of this study are to analyze the spatial pattern of the cultural industry and to empirically examine the effect of municipalities' cultural industries on regional economy using SUR model. The major findings are as follows: First, cultural industries are concentrated in the capital region and several metropolitan areas. Secondly, the estimated result of SUR model shows that there is inter-relationship between cultural industry and regional economy. The effect of the cultural industry on GRDP is that the cultural industry increased 1%, GRDP increased by 0.46%. In turn, GRDP increased 1%, cultural industry increased by 0.75%. Thirdly, the elasticity of the cultural industry on GRDP is much higher than that of labor or capital stock, showing that the cultural industry has a more powerful influence on its regional economy. Fourth, the elasticity of the cultural industry on GRDP of Gun is higher than that of shi, indicating that it is rational for Gun to develop strategies to promote competitive power of the cultural Industry for regional economic growth.

• Journal of Digital Convergence
• /
• v.15 no.6
• /
• pp.133-143
• /
• 2017

Data is the most important asset in the financial sector. On average, 71 percent of financial institutions generate competitive advantage over data analysis. In particular, in the card industry, the card transaction data is widely used in the development of merchant information, economic fluctuations, and information services by analyzing patterns of consumer behavior and preference trends of all customers. However, creation of new value through fusion of data is insufficient. This study introduces the analysis and forecasting of consumption trends of credit card companies which convergently analyzed the social data and the sales data of the company's own. BC Card developed an algorithm for linking card and social data with trend profiling, and developed a visualization system for analysis contents. In order to verify the performance, BC card analyzed the trends related to 'Six Pocket' and conducted th pilot marketing campaign. As a result, they increased marketing multiplier by 40~100%. This study has implications for creating a methodology and case for analyzing the convergence of structured and unstructured data analysis that have been done separately in the past. This will provide useful implications for future trends not only in card industry but also in other industries.

• The Journal of Bigdata
• /
• v.8 no.1
• /
• pp.131-156
• /
• 2023

The traditional retail industry significantly changed over the past decade due to the mobile and online technologies. This change has been accompanied by a shift in consumer behavior regarding purchasing patterns. Despite the rise of online shopping, there are still specific categories of products, such as "Processed food" in Mongolia, for which traditional shopping remains the preferred purchase method. To prepare for the inevitable future of retail businesses, firms need to closely analyze the performance of their offline stores to plan their further actions in a new multi-channel environment. Retailers must integrate diverse channels into their operations to stay relevant and adjust to the shifting market. In this research, we have analyzed the performance data such as sales, profit, and amount of sales of offline stores by using clustering approach. From the clustering, we have found the several distinct insights by comparing the circumstances and performance of retail stores. For the certain retail stores, we have proposed three different strategies: a fulfillment hub store between online and offline channels, an experience store to elongate customers' time on the premises, and a merge between two non-related channels that could complement each other to increase traffic based on the store characteristics. With the proposed strategies, it may enhance the user experience and profit at the same time.