• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.16 no.4
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• pp.195-209
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• 2021

According to the 2019-2020 social media usage survey conducted by the Seoul e-commerce center, 5 out of 10 consumers have experienced shopping through social media. The cost of traditional advertising media has been reduced and advertising spending on social media has risen by 74%, indicating that social media is becoming a more important marketing element. While the number of users of social media has increased and corporate marketing activities have increased accordingly, research has been conducted in various aspects of marketing such as user motivation for social media, satisfaction, and purchase intention. There was no subdivided study on the differences in the social media usage frequency of consumers in actual purchasing behavior. This study attempted to identify differences in consumer characteristics by cluster in the agrifood purchase situation by grouping them by type according to the frequency of use of social media for consumers who purchase agri-food online. Product involvement, product need, and online purchase channel Consumer characteristics such as demographic distribution, perceived risk, and eating and lifestyle in each cluster were checked for the three agrifood purchase situations including choice, and types for each cluster were presented. To this end, questionnaire data on the frequency of social media use and online agrifood purchase behavior were collected from 245 consumers, and the validity of the measurement variables was secured through factor analysis and reliability analysis. As a result of cluster analysis according to the frequency of social media use, it was divided into three clusters. The first cluster was a group that mainly used open social media, and the second cluster was a group that used both open and closed social media and online shopping malls; The third cluster was a group with low online media usage overall, and the characteristics of each cluster appeared. Through regression analysis, the effect on product involvement, product need, and purchase channel selection when purchasing agri-food online through each of the three clusters was confirmed through regression analysis. As a result of the regression analysis, the characteristic of cluster 1 in the situation of purchasing agri-food online is a male in his 30s living in a rural area who has no reluctance to purchase agri-food on social media or online shopping malls. The characteristics of cluster 2 are mainly consumers who are interested in purchasing health food, and the consumer characteristics are represented. In the case of cluster 3, when purchasing products online, they purchase after considering quality and price a lot, and the consumer characteristics are represented as people who are more confident in purchasing offline than online. Through this study, it is judged that by identifying the differences in consumer characteristics that appear in the agri-food purchase situation according to the frequency of social media use, it can be helpful in strategic judgments in marketing practice on social media customer targeting and customer segmentation.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.16 no.4
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• pp.85-99
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• 2021

Due to the continuous unemployment problem, the number of jobs is gradually decreasing, and entrepreneurship is emerging as an alternative. This is because, despite the government operating various start-up support programs to build a start-up-friendly culture, young entrepreneurs cannot endure the valley of death and disappear. Therefore, through this study, we intend to provide implications by analyzing the impact on Entrepreneurial satisfaction, which is essential for continuously running a business, and life satisfaction, which can act as a social awareness. This study was conducted with 573 non-wage workers who belonged to the founders among the participants of the 'College Graduation Occupational Migration Path Survey(GOMS)' survey provided by the Korea Employment Information Service. In order to analyze the relationship between entrepreneurial competency and job fit, Entrepreneurial satisfaction, and life satisfaction, the analysis was conducted using the SPSS 23.0 program. The main research results are summarized as follows. First, entrepreneurial competency has a positive effect on Entrepreneurial satisfaction and life satisfaction. Second, job fit indicates a moderating role in the relationship between entrepreneurial competency and Entrepreneurial satisfaction. Third, start-up satisfaction appears to have a partial mediating role in the relationship between entrepreneurial competency and life satisfaction. Fourth, as a result of analyzing the difference between groups according to the type of start-up(single/partnership), the group that worked together showed higher Entrepreneurial satisfaction and life satisfaction. The main implications of this study are: First, in order to increase the Entrepreneurial satisfaction and life satisfaction of university graduates who are the subject of the study, it will be necessary to design a program that can diagnose and enhance the entrepreneurial competency of students at the university level. Second, entrepreneurial competency is a basic intrinsic factor that founders must have, and it should act as an important evaluation factor when selecting founders for support programs from start-up support organizations as well as founders. Third, it is necessary to maintain mutual trust by documenting problems (positions, wages, management rights, distribution of profits, etc.) that may occur in joint ventures with objective data. Fourth, it is necessary to establish an environment in which the MZ generation, armed with the challenging spirit and creativity, can continue to take on challenges even if they fail.

• Journal of Intelligence and Information Systems
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• v.27 no.3
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• pp.157-173
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• 2021

With the development of information technology, the amount of available information increases daily. However, having access to so much information makes it difficult for users to easily find the information they seek. Users want a visualized system that reduces information retrieval and learning time, saving them from personally reading and judging all available information. As a result, recommendation systems are an increasingly important technologies that are essential to the business. Collaborative filtering is used in various fields with excellent performance because recommendations are made based on similar user interests and preferences. However, limitations do exist. Sparsity occurs when user-item preference information is insufficient, and is the main limitation of collaborative filtering. The evaluation value of the user item matrix may be distorted by the data depending on the popularity of the product, or there may be new users who have not yet evaluated the value. The lack of historical data to identify consumer preferences is referred to as data sparsity, and various methods have been studied to address these problems. However, most attempts to solve the sparsity problem are not optimal because they can only be applied when additional data such as users' personal information, social networks, or characteristics of items are included. Another problem is that real-world score data are mostly biased to high scores, resulting in severe imbalances. One cause of this imbalance distribution is the purchasing bias, in which only users with high product ratings purchase products, so those with low ratings are less likely to purchase products and thus do not leave negative product reviews. Due to these characteristics, unlike most users' actual preferences, reviews by users who purchase products are more likely to be positive. Therefore, the actual rating data is over-learned in many classes with high incidence due to its biased characteristics, distorting the market. Applying collaborative filtering to these imbalanced data leads to poor recommendation performance due to excessive learning of biased classes. Traditional oversampling techniques to address this problem are likely to cause overfitting because they repeat the same data, which acts as noise in learning, reducing recommendation performance. In addition, pre-processing methods for most existing data imbalance problems are designed and used for binary classes. Binary class imbalance techniques are difficult to apply to multi-class problems because they cannot model multi-class problems, such as objects at cross-class boundaries or objects overlapping multiple classes. To solve this problem, research has been conducted to convert and apply multi-class problems to binary class problems. However, simplification of multi-class problems can cause potential classification errors when combined with the results of classifiers learned from other sub-problems, resulting in loss of important information about relationships beyond the selected items. Therefore, it is necessary to develop more effective methods to address multi-class imbalance problems. We propose a collaborative filtering model using CGAN to generate realistic virtual data to populate the empty user-item matrix. Conditional vector y identify distributions for minority classes and generate data reflecting their characteristics. Collaborative filtering then maximizes the performance of the recommendation system via hyperparameter tuning. This process should improve the accuracy of the model by addressing the sparsity problem of collaborative filtering implementations while mitigating data imbalances arising from real data. Our model has superior recommendation performance over existing oversampling techniques and existing real-world data with data sparsity. SMOTE, Borderline SMOTE, SVM-SMOTE, ADASYN, and GAN were used as comparative models and we demonstrate the highest prediction accuracy on the RMSE and MAE evaluation scales. Through this study, oversampling based on deep learning will be able to further refine the performance of recommendation systems using actual data and be used to build business recommendation systems.

• Knowledge Management Research
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• v.22 no.2
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• pp.119-144
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• 2021

Recently, as competition in the market evolves from the competition among companies to the competition among their supply chains, companies are struggling to enhance their supply chain management (hereinafter SCM). In particular, as blockchain technology with various technical advantages is combined with SCM, a lot of domestic manufacturing and distribution companies are considering the adoption of blockchain-oriented SCM (BOSCM) services today. Thus, it is an important academic topic to examine the factors affecting the use of blockchain-oriented SCM. However, most prior studies on blockchain and SCMs have designed their research models based on Technology Acceptance Model (TAM) or the Unified Theory of Acceptance and Use of Technology (UTAUT), which are suitable for explaining individual's acceptance of information technology rather than companies'. Under this background, this study presents a novel model of blockchain-oriented SCM acceptance model based on the Technology-Organization-Environment (TOE) framework to consider companies as the unit of analysis. In addition, Value-based Adoption Model (VAM) is applied to the research model in order to consider the benefits and the sacrifices caused by a new information system comprehensively. To validate the proposed research model, a survey of 126 companies were collected. Among them, by applying PLS-SEM (Partial Least Squares Structural Equation Modeling) with data of 122 companies, the research model was verified. As a result, 'business innovation', 'tracking and tracing', 'security enhancement' and 'cost' from technology viewpoint are found to significantly affect 'perceived value', which in turn affects 'intention to use blockchain-oriented SCM'. Also, 'organization readiness' is found to affect 'intention to use' with statistical significance. However, it is found that 'complexity' and 'regulation environment' have little impact on 'perceived value' and 'intention to use', respectively. It is expected that the findings of this study contribute to preparing practical and policy alternatives for facilitating blockchain-oriented SCM adoption in Korean firms.

• Journal of Intelligence and Information Systems
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• v.28 no.1
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• pp.69-88
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• 2022

One of the characteristics of South Korea's economic structure is that it is highly dependent on exports. Thus, many businesses are closely related to the global economy and diplomatic situation. In addition, small and medium-sized enterprises(SMEs) specialized in exporting are struggling due to the spread of COVID-19. Therefore, this study aimed to develop a model to forecast exports for next year to support SMEs' export strategy and decision making. Also, this study proposed a strategy to recommend promising export countries of each item based on the forecasting model. We analyzed important variables used in previous studies such as country-specific, item-specific, and macro-economic variables and collected those variables to train our prediction model. Next, through the exploratory data analysis(EDA) it was found that exports, which is a target variable, have a highly skewed distribution. To deal with this issue and improve predictive performance, we suggest a separated learning method. In a separated learning method, the whole dataset is divided into homogeneous subgroups and a prediction algorithm is applied to each group. Thus, characteristics of each group can be more precisely trained using different input variables and algorithms. In this study, we divided the dataset into five subgroups based on the exports to decrease skewness of the target variable. After the separation, we found that each group has different characteristics in countries and goods. For example, In Group 1, most of the exporting countries are developing countries and the majority of exporting goods are low value products such as glass and prints. On the other hand, major exporting countries of South Korea such as China, USA, and Vietnam are included in Group 4 and Group 5 and most exporting goods in these groups are high value products. Then we used LightGBM(LGBM) and Exponential Moving Average(EMA) for prediction. Considering the characteristics of each group, models were built using LGBM for Group 1 to 4 and EMA for Group 5. To evaluate the performance of the model, we compare different model structures and algorithms. As a result, it was found that the separated learning model had best performance compared to other models. After the model was built, we also provided variable importance of each group using SHAP-value to add explainability of our model. Based on the prediction model, we proposed a second-stage recommendation strategy for potential export countries. In the first phase, BCG matrix was used to find Star and Question Mark markets that are expected to grow rapidly. In the second phase, we calculated scores for each country and recommendations were made according to ranking. Using this recommendation framework, potential export countries were selected and information about those countries for each item was presented. There are several implications of this study. First of all, most of the preceding studies have conducted research on the specific situation or country. However, this study use various variables and develops a machine learning model for a wide range of countries and items. Second, as to our knowledge, it is the first attempt to adopt a separated learning method for exports prediction. By separating the dataset into 5 homogeneous subgroups, we could enhance the predictive performance of the model. Also, more detailed explanation of models by group is provided using SHAP values. Lastly, this study has several practical implications. There are some platforms which serve trade information including KOTRA, but most of them are based on past data. Therefore, it is not easy for companies to predict future trends. By utilizing the model and recommendation strategy in this research, trade related services in each platform can be improved so that companies including SMEs can fully utilize the service when making strategies and decisions for exports.

• Journal of Global Scholars of Marketing Science
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• v.17 no.3
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• pp.83-108
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• 2007

Since the 1992 UN Conference for Environment and Development held in Rio de Jaineiro, Sustainable Development has become the global thesis. More than 170 countries signed the Agenda 21 for the sustainable action plan, and adopted the sustainability concept as the key concept of dealing with the environmental, social, ethical, and economic problem. Sustainability is one of the main marketing challenges in the 21st century. By integrating social and ecological criteria, marketing may can make valuable contributions to sustainable development. Regarding the sustainability marketing, it is difficult to find the domestic marketing research on the thesis of sustainable development, and this is the definite evidence that the Korean marketing researchers do not realize the importance of the thesis of sustainable development which is internationally suggested as the new paradigm of change. The purpose of this study is to build the conceptual background and explore the research direction in order to introduce and adopt the concept of sustainable development in the domestic marketing research field. The present paper proposes a comprehensive conception of sustainability marketing, defined by six step: analysis of social-ecological problems; analysis of consumer behavior; normative sustainability marketing; strategic sustainability marketing; instrumental sustainability marketing; and transformative sustainability marketing. The aim of the paper are to clarify the concept of sustainability marketing. To accomplish this research purpose we discuss the sustainable development which is the conceptual background of sustainability marketing, analyze the characteristics of the sustainability marketing, and finally summarize the research results and present the suggestions for further research. Sustainability marketing embraces the idea of sustainable development, a development that meets the needs of the present without compromising the ability of future generation to meet their own needs. Sustainability Marketing goes beyond conventional marketing thinking. If marketing is about satisfying customer needs and building profitable relationships with customers, sustainability marketing may be defined as building and maintaining sustainable relationships with customers, the social environment and natural environment. By creating social and environmental value, sustainability marketing tries to deliver and increase customer value. Sustainability Marketing aims at creating customer value, social value and environmental value. Sustainability marketing integrates social and ecological criteria into the whole process of marketing, and can be differentiated in six steps: (1) Analysis of the social and ecological problems, generally and specifically with respect to products which satisfy customer needs and wants; (2) Analysis of customer behavior with special aspect to social and ecological concerns; (3) Corporate commitments to sustainable development in the mission statement, development of sustainability visions, formulation of sustainable principles and guideline, setting of socio-ecological marketing objectives and goals (normative aspects of sustainability marketing); (4) Sustainability segmentation, targeting and positioning, and timing of market entry(strategic aspects of sustainability marketing); (5)Integration of social and ecological criteria into the marketing-mix, i.e. products, services and brands, pricing, distribution and communication(instrumental aspects of sustainability marketing); (6) Participation in public and political change processes, which transform existing institutions towards sustainability(transformative aspects of sustainability marketing). The first two steps begin with an analysis of the company situation. In sustainability marketing it is crucial not just to know consumer needs and wants, but also to find out about the ecological and social problems of products along their whole life cycle. The intersection of socio-ecological problems and consumer wants sets the ground for sustainability marketing. Step three to five describe the implementation of sustainability marketing. Social and ecological criteria are fully integrated into the mission statement, strategies and marketing-mix. Step six is one of the specifics of sustainability marketing. It is about the commitment of company to sustainable development and their active participation in public and political processes in order to change the existing framework in favor of sustainability.

• Journal of Distribution Science
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• v.10 no.3
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• pp.43-50
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• 2012

This study sets out to examine how a brand image that matches the advertising model has a positive impact on brand attitude and price fairness perceptions. We reviewed the constructs on the basis of previous studies and each of the concepts has been redefined. One such concept, "image congruence," refers to the harmony, fitness, and matching quality of images. For example, how well celebrity advertising model is matches the brand image shows image congruence. Results are summarized as follows: First, the congruence of brand image and sports advertising model has no significant impact on brand attitude certainty and persistence. Second, the individual's brand attitude certainty and brand attitude persistence has a positive impact on the perceptions of price fairness. Third, the congruence of brand image and sports advertising model has a positive impact on the perceptions of price fairness. The first and the third results suggest that the positive impact on the price fairness perceptions is temporary but it has insignificant effects on the formation of brand attitude causing ongoing purchases. In other words, in order to influence consumers' long-term confidence on the brand, improving the quality of products or services has to precede promotional strategies such as advertising. When an advertising model is inappropriate for the brand image, consumers perceive product price changes as a negative issue in the short term. However, in the long term, attitude formation such as consumers' repurchase intentions and word of mouth will be not affected. The second result suggests that an already existing positive brand attitude can contribute more positively to change the perceptions of price fairness. In particular, attitude persistence has greater influence than attitude certainty on the price fairness. It suggests that persistence issues such as the trading period and the frequency of transactions must be managed and controlled because they are more important than the certainty issues such as strength of belief or trust. For example, when a commercial model for expensive sporting goods matches up with the brand image, consumer feels less pressure on the price changes. However, it does not determine the consumer's repeated purchases or sustainable transactions and it also has no absolute impact on the brand trust. In other words, consumer brand attitude should be recognized and approached as a routine strategy in view of the result that it is of great value as a causal variable in the process of consumer decision-making.

• Journal of Distribution Science
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• v.8 no.3
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• pp.37-47
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• 2010

CRM refers to the operating activities that always maintain and promote good relationship with customers to ultimately maximize the company's profits by understanding the value of customers to meet their demands, establishing a strategy which may maximize the Life Time Value and successfully operating the business by integrating the customer management processes. In our country, many big businesses are introducing CRM initiatively to use it in marketing strategy however, most medium and small sized companies do not understand CRM clearly or they feel difficult to introduce it due to huge investment needed. This study is intended to present CRM promotion strategy and activities plan fit for the medium and small sized companies by analyzing the success factors of the leading companies those have already executed CRM by surveying the precedents to make the distributors out of the industries have close relation with consumers to overcome their weakness in scale and strengthen their competitiveness in such a rapidly changing and fiercely competing market. There are 5 stages to build CRM such as the recognition of the needs of CRM establishment, the establishment of CRM integrated database, the establishment of customer analysis and marketing strategy through data mining, the practical use of customer analysis through data mining and the implementation of response analysis and close loop process. Through the case study of leading companies, CRM is needed in types of businesses where the companies constantly contact their customers. To meet their needs, they assertively analyze their customer information. Through this, they develop their own CRM programs personalized for their customers to provide high quality service products. For customers helping them make profits, the VIP marketing strategy is conducted to keep the customers from breaking their relationships with the companies. Through continuous management, CRM should be executed. In other words, through customer segmentation, the profitability for the customers should be maximized. The maximization of the profitability for the customers is the key to CRM. These are the success factors of the CRM of the distributors in Korea. Firstly, the top management's will power for CS management is needed. Secondly, the culture across the company should be made to respect the customers. Thirdly, specialized customer management and CRM workers should be trained. Fourthly, CRM behaviors should be developed for the whole staff members. Fifthly, CRM should be carried out through systematic cooperation between related departments. To make use of the case study for CRM, the company should understand the customer and establish customer management programs to set the optimal CRM strategy and continuously pursue it according to a long-term plan. For this, according to collected information and customer data, customers should be segmented and the responsive customer system should be designed according to the differentiated strategy according to the class of the customers. In terms of the future CRM, integrated CRM is essential where the customer information gathers together in one place. As the degree of customers' expectation increases a lot, the effective way to meet the customers' expectation should be pursued. As the IT technology improved rapidly, RFID (Radio Frequency Identification) appears. On a real-time basis, information about products and customers is obtained massively in a very short time. A strategy for successful CRM promotion should be improving the organizations in charge of contacting customers, re-planning the customer management processes and establishing the integrated system with the marketing strategy to keep good relation with the customers according to a long-term plan and a proper method suitable to the market conditions and run a company-wide program. In addition, a CRM program should be continuously improved and complemented to meet the company's characteristics. Especially, a strategy for successful CRM for the medium and small sized distributors should be as follows. First, they should change their existing recognition in CRM and keep in-depth care for the customers. Second, they should benchmark the techniques of CRM from the leading companies and find out success points to use. Third, they should seek some methods best suited for their particular conditions by achieving the ideas combining their own strong points with marketing. Fourth, a CRM model should be developed that will promote relationship with individual customers just like the precedents of small sized businesses in Switzerland through small but noticeable events.

• Journal of Distribution Science
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• v.10 no.5
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• pp.37-44
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• 2012

In this paper, we investigate several factors that affect the locational decision of discount stores by using previous studies on the marketing area and the location of commercial facilities. We selected 21 primary variables that are expected to influence the decision of store location and, by factor analysis, grouped them into five underlying factors. Among these, the demographic factor, which shows the potential purchasing power level, had the greatest impact on the locational decision for the store. However, we found individual stores positioned according to unique locational characteristics in addition to the demographic factor. It means that we have to additionally consider if the vicinity of the market is based on any physical properties. Many previous studies proposed four decision factors for store location: the economic factor, the demographic factor, the land utilization factor, and traffic factor. However, the fivefold factors-our distinctive contribution-are more concrete and persuasive according to Korean reality. We show that location preference is based on the following criteria: (1) the area is densely populated, (2) houses stand close together, (3) residents have a high income level, (4) road traffic is developed and easy to access, and (5) public transportation is well developed. The demographic factor has the greatest impact on the location of a discount store. The number of households has a greater relevance to the demographic factor than does the individual consumer. Second, discount stores relatively prefer places where houses are located close together because such places offer easy access to the market. Third, a place whose residents have a high income level will be preferred, with its large cars and excellent traffic conditions. Fourth, a location would be highly rated if the roads around commercial facilities are well developed and their accessibility is good. Finally, discount stores must be located close to bus stops because female consumers, including housewives-the most important customers-evaluate stores based on distance. In this research, the variable of consumer attitude and preference was excluded, and the location factors of discount stores were analyzed according to a microscopic view through physical spatial data. In the future, the opening of new discount stores based on the five factors indicated above will require a comparatively shorter time from the first project feasibility analysis. In addition, the result of our study can be applied to the field of public policy for constructing and attracting large-scale distribution facilities.

• KDI Journal of Economic Policy
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• v.14 no.2
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• pp.55-75
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• 1992

At the outset of import liberalization, most economists expected a significant drop in the prices of domestic goods that faced foreign competition. However, it is now generally acknowledge that a significant drop in prices of those goods has not occurred. A common claim is that the prices did not drop significantly because the major importers of many imported goods were also the domestic producers of competing goods. The objective of this paper is to analyze the welfare effect of importation by domestic firms that produce competing goods, to identify the factors that facilitate such business practices, and to formulate a policy that could improve the welfare. We proved that importation by competing domestic firms definitely raises the prices of both imported and domestic goods compared to the situation where foreign goods are imported by non-producers, ceteris paribus. The intuition behind this result is that since a producer-importer is essentially a cartel, its overall profit maximization requires reduced competition between the products that it sells. On the other hand, if a producer-importer is more efficient at distrinbution than a simple importer, the comparison between the two cases is a priori indeterminate. We also find that the industries in which domestic producers are actively involved in importing competing goods are the ones in which the distribution channels are tightly controlled by importer-producers. This finding suggests that exclusive dealing contracts, which work as an entry barrier, may be the source of importing by domestic producers. We argue that in a country such as Korea, where financial market is highly incomplete, tight control of the distribution channels by oligopolistic manufacturers is likely to be an effective entry barrier that leads to importing by domestic producers of similar goods. We further argue that seemingly superior distribution costs of importer-producers is likely to be a result of market foreclosure which would disappear once the entry barrier of exclusive dealing contracts is removed. Above findings suggest that market imperfections are the source of importation by domestic competitors, which in turn constitutes a market imperfection in itself and reduces consumer welfare. As potential remedies, we considered three alternatives; direct price control by the government over the imported goods sold by major domestic producers, regulation of trade itself between major producers, and regulation of exclusive dealing contracts. For reasons both theoretical and pratical, we find that the last alternative is the most attrative. Prohibiting exclusive contracts between manufacturers and dealers in industries where exclusive dealing contracts are a significant entry barrier is expected to break up the importer-producer cartel and improve the welfare.