• Journal of Distribution Science
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• v.15 no.2
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• pp.79-90
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• 2017

Purpose - Cargo Distribution O2O Business Model is the form of business that connects the cargo and empty cargo-truck based on mobile online platform. In Korean cargo distribution market, FIN(Freight Information Network) is the only model that represents O2O Business Model. The purpose of this paper is investigating the recognition of driver who is the only source of income toward cargo distribution O2O Business Model, and based on the investigated recognition of trucker, suggesting strategic implication. Research design, data, and methodology - PESTLE methodology which is massive environment analysis, and 5 Forces Model when analyze the present and future of cargo distribution O2O business market of industrial structure analysis were used as investigation methodology. Also structured questionnaire was used for trucker's recognition investigation. Based on collected 196 structured effective questionnaires organized with 26 questions were analyzed using statistics package. Results - 51.3% of responded driver is non-differentiated, deprofessionalize form that transport all types of cargo. 95.4% recognize cargo distribution O2O Business Model, FIN is needed, especially during back-hall(94.7%). As a payment method, monthly due is preferred(73%), but it is also needed to pay annual due and pay whenever cargo and cargo-truck are connected(24.5%). Trucker prefer FIN operation corporation which has rich supply(85.2%), and is liberal in supply in any domestic area(75.5%). Conclusions - First, 91% was the member of FIN, and 95% of non-member recognized FIN is needed. 83% of them has the intent to be the member of FIN. Second, besides of monthly due as payment method of FIN, 25% has positive recognition toward new payment method. The new payment method means paying annual due and pay whenever cargo and cargo-truck are connected. Third, because of information imbalance about the cargo and cargo-truck among, operators whose business goal is FIN, it was investigated that transportation fee is low and commission charge of broker is high. The core of Korean Cargo Distribution O2O Business Model, FIN, is online platform that matches cargo and cargo-truck. Therefore, FIN operator should minimize the amount of single transportation of trucker. This study suggests the development of shipper using FIN, diversify distribution channel, suggesting backhaul toward trucker as solution to FIN operator.

• Management & Information Systems Review
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• v.39 no.3
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• pp.17-35
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• 2020

The purpose of this study is to develop business models for current situational scenarios reflecting customer needs emphasize the need for implementing a logistics cooperation system by analyzing big data to strengthen SCM competitiveness capacities. For healthcare SCM competitiveness needed for the logistics cooperation usage intent, they were divided into product quality, price leadership, hand-over speed, and process flexibility for examination. The wordcloud results that analyzed major considerations to realize work efficiency between medical institutes, words like unexpected situations, information sharing, delivery, real-time, delivery, convenience, etc. were mentioned frequently. It can be analyzed as expressing the need to construct a system that can immediately respond to emergency situations on the weekends. Furthermore, in addition to pursuing communication and convenience, the importance of real-time information sharing that can share to the efficiency of inventory management were evident. Accordingly, it is judged that it is necessary to aim for a business model that can enhance visibility of the logistics pipeline in real-time using big data analysis on site. By analyzing the effects of the adaptability of a supply chain network for healthcare SCM competitiveness, it was revealed that obtaining competitive capacities is possible through the implementation of logistics cooperation. Stronger partnerships such as logistics cooperation will lead to SCM competitive capacities. It will be necessary to strengthen SCM competitiveness by searching for a strategic approach among companies in a direction that can promote mutual partnerships among companies using the joint logistics system of medical institutes. In particular, it will be necessary to search for ways to utilize HCSM through big data analysis according to the construction of a logistics cooperation system.

• Management & Information Systems Review
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• v.38 no.3
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• pp.113-125
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• 2019

This study empirically analyzes the effect of SNS informativeness, playfulness and reliability on purchase intention and the effect of consumer's purchase intention on business performance through structural equation model, In doing so, this study aims to suggest ways to enhance consumers' purchase intention and consequently increase the business performance through various SNS marketing strategies that can efficiently manage consumers. The questionnaires were distributed to adult men and women who are in their 20s through 60s, actively use SNS, and primarily reside in Daegu and Gyeongbukdo. The 400 copies of questionnaire were distributed from September 15 to October 1, 2018, of which 364 (91%) were used for the empirical analysis, except for 36 of the questionnaires that were unfaithful or unresponsive. Basic statistical analysis including frequency analysis was performed using SPSS 22.0 and AMOS 24.0, reliability and validity analysis were also performed, and finally hypotheses were tested by performing confirmatory factor analysis and path analysis of structural equation model. All of the SNS informativeness, playfulness and reliability were shown to have positive effects on the purchase intention. In addition, the effect of purchase intention on business performance was found to be significant. Companies should come up with a strategic SNS marketing plan to encourage consumers to enhance the willingness to purchase their products and services through SNS, and to make actual purchases, thereby improving business performance.

• Proceedings of the Korea Contents Association Conference
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• 2019.05a
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• pp.109-110
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• 2019

자본주의 사회에서 기업은 이윤의 극대화라는 목표를 이루기 위해, 인간을 하나의 자원으로 간주하여 도구화 하는 경향이 있다. 그 결과 인간소외(alienation) 및 부의 양극화 현상이 심각한 사회적 문제로 거론되고 있다. 오늘날 경제성장에 따른 물질적 풍요와 번영이 인류사회에 행복을 가져다 줄 것이라는 통념은 '물질적 풍요 속의 정신적 빈곤'이라는 문제제기에 의해 그 위상이 흔들리고 있다. 자본주의가 인류사회의 행복과 공동번영에 기여하는 경제체제로서 역할을 다하려면, 자본주의 역시 시대의 변화에 맞추어 진화해야 한다. 본 논문에서는 새 시대에 걸 맞는 자본주의의 대안을 논의하고자, 저자 이재윤이 창시한 깨달음경영학(MOSEE;Management Of allSelves' Enlightenment and Empowerment)의 새로운 과학적 학문연구를 통해 새로운 실현성 영역을 추구하는 동시에, 깨달음경영의 새로운 5차원 요소인 의식(영성) 자원 및 자산(SRA:Spirit Resource and Asset)과 본질적으로 무(無)에서 유(有)를 창조하는 진성 창조경영(MOC:Management Of Creation)의 연구 및 인간의식 성장 방법론에 대하여 발표 하고자 한다. 이로써 현대의 주요한 여러 경영철학들 예컨대 CSV(마이클 포터) SI(개리 함멜) 복잡계 철학 美德경영 등의 내재된 구조적 제약들을 분석 평가하고 한계를 극복하는 방안들을 제시함으로써 21세기 우주 인류 신문명 창달을 위한 5차원의 깨달음경영 혁명을 성취 하고자 한다. 즉 2040년 전에 지구 인류의 고도 영성 초 과학기술 문명을 넘어서 우주 인류의 초 영성 초 과학기술 문명 창달을 선도하는 학문연구 교육 인류 사회활동을 지속적으로 해갈 것이다. 위와 같이 21세기 우주 인류의 영원한 평화 자유 지속적 번영을 이루고자 한다. 본 연구는 통섭 고찰 제2회로 미국의 마이클 포토와 막 클램머의 공유가치(CSV)와 영국의 게리 함멜과 프라할라드의 전략적 의도와 브라이언 아서의 복잡계 경영경제 이론을 통섭을 고찰한다.

• Journal of Intelligence and Information Systems
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• v.26 no.4
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• pp.111-126
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• 2020

Most industries have recently become aware of the importance of customer lifetime value as they are exposed to a competitive environment. As a result, preventing customers from churn is becoming a more important business issue than securing new customers. This is because maintaining churn customers is far more economical than securing new customers, and in fact, the acquisition cost of new customers is known to be five to six times higher than the maintenance cost of churn customers. Also, Companies that effectively prevent customer churn and improve customer retention rates are known to have a positive effect on not only increasing the company's profitability but also improving its brand image by improving customer satisfaction. Predicting customer churn, which had been conducted as a sub-research area for CRM, has recently become more important as a big data-based performance marketing theme due to the development of business machine learning technology. Until now, research on customer churn prediction has been carried out actively in such sectors as the mobile telecommunication industry, the financial industry, the distribution industry, and the game industry, which are highly competitive and urgent to manage churn. In addition, These churn prediction studies were focused on improving the performance of the churn prediction model itself, such as simply comparing the performance of various models, exploring features that are effective in forecasting departures, or developing new ensemble techniques, and were limited in terms of practical utilization because most studies considered the entire customer group as a group and developed a predictive model. As such, the main purpose of the existing related research was to improve the performance of the predictive model itself, and there was a relatively lack of research to improve the overall customer churn prediction process. In fact, customers in the business have different behavior characteristics due to heterogeneous transaction patterns, and the resulting churn rate is different, so it is unreasonable to assume the entire customer as a single customer group. Therefore, it is desirable to segment customers according to customer classification criteria, such as loyalty, and to operate an appropriate churn prediction model individually, in order to carry out effective customer churn predictions in heterogeneous industries. Of course, in some studies, there are studies in which customers are subdivided using clustering techniques and applied a churn prediction model for individual customer groups. Although this process of predicting churn can produce better predictions than a single predict model for the entire customer population, there is still room for improvement in that clustering is a mechanical, exploratory grouping technique that calculates distances based on inputs and does not reflect the strategic intent of an entity such as loyalties. This study proposes a segment-based customer departure prediction process (CCP/2DL: Customer Churn Prediction based on Two-Dimensional Loyalty segmentation) based on two-dimensional customer loyalty, assuming that successful customer churn management can be better done through improvements in the overall process than through the performance of the model itself. CCP/2DL is a series of churn prediction processes that segment two-way, quantitative and qualitative loyalty-based customer, conduct secondary grouping of customer segments according to churn patterns, and then independently apply heterogeneous churn prediction models for each churn pattern group. Performance comparisons were performed with the most commonly applied the General churn prediction process and the Clustering-based churn prediction process to assess the relative excellence of the proposed churn prediction process. The General churn prediction process used in this study refers to the process of predicting a single group of customers simply intended to be predicted as a machine learning model, using the most commonly used churn predicting method. And the Clustering-based churn prediction process is a method of first using clustering techniques to segment customers and implement a churn prediction model for each individual group. In cooperation with a global NGO, the proposed CCP/2DL performance showed better performance than other methodologies for predicting churn. This churn prediction process is not only effective in predicting churn, but can also be a strategic basis for obtaining a variety of customer observations and carrying out other related performance marketing activities.

• The Journal of Small Business Innovation
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• v.19 no.2
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• pp.53-68
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• 2016

Motivation and activities for technological learning, entrepreneurship, innovation, and creativity are driving forces of economic development in Asian countries. In the early stages of technological development, technological learning and entrepreneurship are efficient ways in which to catch up with advanced countries because firms can accumulate skills and knowledge quickly at relatively low risk. In the later stages of technological development, however, innovation and creativity become more important. This study aims to identify a) the factors (learning capabilities) that influence technological learning performance and b) barriers to enhancing innovation capabilities for the creative economy and organizations. The major part of this study is related to learning capabilities in the post-catch-up era. Based on a literature review and observations from Korean experiences, this study proposes a technological learning model composed of various influencing factors on technological learning. Three hypotheses are derived, and data are collected from Korean machine tool manufacturers. Intense interviews with CEOs and R&D directors are conducted using structured questionnaires. Statistical analysis, such as correlation and ANOVA are then carried out. Furthermore, this study addresses how to enhance innovation capabilities to move forward. Innovation enablers and barriers are identified by case studies and policy analysis. The results of the empirical study identify several levels of firms' learning capabilities and activities such as a) stock of technology, b) potential of technical labor, c) explicit technological efforts, d) readiness to learn, e) top management support, f) a formal technological learning system, g) high learning motivation, h) appropriate technology choice, and i) specific goal setting. These learning capabilities determine firms' learning performance, especially in the early stages of development. Furthermore, it is found that the critical factors for successful technological learning vary along the stages of technology development. Throughout the statistical and policy analyses, this study confirms that technological learning can be understood as an intrinsic principle of the technology development process. Firms perform proactive and creative learning in the late stages, while reactive and imitative learning prevails in the early stages. In addition, this study identifies the driving forces or facilitating factors enhancing innovation performance in the post catch-up era. The results of the preliminary case studies and policy analysis show some facilitating factors such as a) the strategic intent of the CEO and corporate culture, b) leadership and change agents, c) design principles and routines, d) ecosystem and collaboration with partners, and e) intensive R&D investment.

• Culinary science and hospitality research
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• v.20 no.1
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• pp.189-204
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• 2014

This study is aimed to identify the relationship between Korean restaurant selection attributes and behavioral intention regarding foodservice consumption tendency. In order to achieve the purpose of research, frequency analysis, factor and reliability analysis, correlation analysis, cluster analysis, chi-square test, variance analysis, and multiple regression analysis were conducted using SPSS 18.0. As a result of variance analysis, accessibility did not appear to have a significant difference in all clusters, food quality appeared to have a significant result (F=5.587, $p{\leq}.001$), employees' service appeared to have a significant difference (F=5.186, p<.01), and price discounts also showed a significant difference (F=4.921, p<.01). Therefore, the first hypothesis that the foodservice consumption tendency has a difference in the Korean restaurants selection attributes was partially selected. In order to verify the hypothesis that the Korean restaurants selection attributes affect behavioral intention, the sub-factors of the Korean restaurant selection attributes (accessibility of restaurants, food quality, employees' service, price discounts) were set as independent variables, and the behavioral intention of foodservice consumers was set as a dependent variable. As a result, the accessibility of restaurants (${\beta}=.092$) and price discounts (${\beta}=.299$) have a non-significant effect on behavioral intention. However, a significant result was shown in food quality (${\beta}=.379$, p<.001) and employees' service (${\beta}=.251$, p<.001). Thus, the hypothesis that the Korean restaurant selection attributes have a positive effect on behavioral intention was partially selected. Based on the results, foodservice managers need to build up strategic management to improve food quality with better ingredients, sanitation, adequate quantity, and consistent taste of food. In addition, they should provide better service with well-trained employees.

• Journal of Global Scholars of Marketing Science
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• v.20 no.1
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• pp.59-69
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• 2010

Green or an environmental consciousness has been a major issue for businesses and government offices, as well as consumers, worldwide. In response to this movement, the Korean government announced, in the early 2000s, the era of "Green Growth" as a way to encourage green-related business activities. The Korean fashion industry, in various levels of involvement, presents diverse eco-friendly products as a part of the green movement. These apparel products include organic products and recycled clothing. For these companies to be successful, they need information about who are the consumers who consider green issues (e.g., environmental sustainability) as part of their personal values when making a decision for product purchase, use, and disposal. These consumers can be considered as eco-sumers. Previous studies have examined consumers' purchase intention for or with eco-friendly products. In addition, studies have examined influential factors used to identify the eco-sumers or green consumers. However, limited attention was paid to eco-sumers' disposal or recycling behavior of clothes in comparison with their green product purchases. Clothing disposal behaviors are ways that consumer can get rid of unused clothing and in clue temporarily lending the item or permanently eliminating the item by "handing down" (e.g., giving it to a younger sibling), donating, exchanging, selling, or simply throwing it away. Accordingly, examining purchasing behaviors of eco-friendly fashion items in conjunction with clothing disposal behaviors should improve understanding of a consumer's clothing consumption behavior from the environmental perspective. The purpose of this exploratory study is to provide descriptive information about Korean eco-sumers who have ecologically-favorable lifestyles and behaviors when buying and disposing of clothes. The objectives of this study are to (a) categorize Koreans on the basis of clothing disposal behaviors; (b) investigate the differences in demographics, lifestyles, and clothing consumption values among segments; and (c) compare the purchase intention of eco-friendly fashion items and influential factors among segments. A self-administered questionnaire was developed based on previous studies. The questionnaire included 10 items of clothing disposal behavior, 22 items of LOHAS (Lifestyles of Health and Sustainability) characteristics, and 19 items of consumption values, measured by five-point Likert-type scales. In addition, the purchase intention of two eco-friendly fashion items and 11 attributes of each item were measured by seven-point Likert type scales. Two polyester fleece pullovers, made from fabric created from recycled bottles with the PET identification code, were selected from one Korean brand and one US imported brand among outdoor sportswear brands. A brief description of each product with a color picture was provided in the survey. Demographic variables (i.e., gender, age, marital status, education level, income, occupation) were also included. The data were collected through a professional web survey agency during May 2009. A total of 600 final usable questionnaires were analyzed. The age of respondents ranged from 20 to 49 years old with a mean age of 34 years. Fifty percent of the respondents were males and about 58% were married, and 62% reported having earned university degrees. Principal components factor analysis with varimax rotation was used to identify the underlying dimensions of the clothing disposal behavior scale, and three factors were generated (i.e., reselling behavior, donating behavior, non-recycling behavior). To categorize the respondents on the basis of clothing disposal behaviors, k-mean cluster analysis was used, and three segments were obtained. These consumer segments were labeled as 'Resale Group', 'Donation Group', and 'Non-Recycling Group.' The classification results indicated approximately 98 percent of the original cases were correctly classified. With respect to demographic characteristics among the three segments, significant differences were found in gender, marital status, occupation, and age. LOHAS characteristics were reduced into the following five factors: self-satisfaction, family orientation, health concern, environmental concern, and voluntary service. Significant differences were found in the LOHAS factors among the three clusters. Resale Group and Donation Group showed a similar predisposition to LOHAS issues while the Non-Recycling Group presented the lowest mean scores on the LOHAS factors compared to the other segments. The Resale and Donation Groups described themselves as enjoying or being satisfied with their lives and spending spare-time with family. In addition, these two groups cared about health and organic foods, and tried to conserve energy and resources. Principal components factor analysis generated clothing consumption values into the following three factors: personal values, social value, and practical value. The ANOVA test with the factors showed differences primarily between the Resale Group and the other two groups. The Resale Group was more concerned about personal value and social value than the other segments. In contrast, the Non-Recycling Group presented the higher level of social value than did Donation Group. In a comparison of the intention to purchase eco-friendly products, the Resale Group showed the highest mean score on intent to purchase Product A. On the other hand, the Donation Group presented the highest intention to purchase for Product B among segments. In addition, the mean scores indicated that the Korean product (Product B) was more preferable for purchase than the U.S. product (Product A). Stepwise regression analysis was used to identify the influence of product attributes on the purchase intention of eco product. With respect to Product A, design, price and contribution to environmental preservation were significant to predict purchase intention for the Resale Group, while price and compatibility with my image factors were significant for the Donation Group. For the Non-Recycling Group, design, price compatibility with the factors of my image, participation to eco campaign, and contribution to environmental preservation were significant. Price appropriateness was significant for each of the three clusters. With respect to Product B, design, price and compatibility with my image factors were important, but different attributes were associated significantly with purchase intention for each of the three groups. The influence of LOHAS characteristics and clothing consumption values on intention to purchase Products A and B were also examined. The LOHAS factor of health concern and the personal value factor were significant in the relationships with the purchase intention; however, the explanatory powers were low in the three segments. Findings showed that each group as classified by clothing disposal behaviors showed differences in the attributes of a product, personal values, and the LOHAS characteristics that influenced their purchase intention of eco-friendly products. Findings would enable organizations to understand eco-friendly behavior and to design appropriate strategic decisions to appeal eco-sumers.