• Title/Summary/Keyword: Sensitive Customer

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A Study on the Critical Factors of Logistics Service Contracts (물류서비스 계약의 결정요인에 관한 연구)

  • Jung, Kyung-Seon;Kim, Tae-Bok
    • Journal of Korea Port Economic Association
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    • v.25 no.3
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    • pp.93-116
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    • 2009
  • As the popularity of logistics service outsourcing has been continuously growing, one of the most frequently addressed issues is how to estimate the effect of cost reduction for users and profit gains from outsourcing contract for providers. Many manufacturing companies agree that logistics outsourcing helps to reduce their operating costs, but some other companies still do not achieve the cost saving or do not trust logistics service providers, so they keep up in-house logistics operations. On the other hand, logistics service providers have low profitability from domestic business activities since they should meet the requirements for highly customized and diverse services from customers and unstable market situation. This study provided the status report dealing with logistics service contracts in Korea. From the focused group interview with logistics professionals, we found out that service scope, scale and cost structure are the most influential factors affecting logistics service contracts. Also, logistics service providers are more sensitive than users regarding value-added logistics service, contract duration and process. Moreover, this study also proposed the standard clauses for logistics service contract and types of logistics contract applied in current logistics fields. As a result, it is expected that these achievements from this study can be utilized to improve the satisfaction of logistics outsourcing in upgrading service quality and customer service level.

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A Study on Sustainable Service Improvement - Case of Seoul National University Hospital, Korea - (지속적인 서비스 개선을 위한 연구 - 서울대학교병원 사례를 중심으로 -)

  • Sung, Hyun Jin;Kim, Young Se
    • Korea Science and Art Forum
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    • v.19
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    • pp.417-424
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    • 2015
  • The healthcare service industry has become one of the business industries in South Korea where service design is most actively being researched on and applied. In accordance with the recent upsurge of the interest in health, healthcare service is expanding its area including disease prevention, patient management, and rehabilitation treatment as well as cure and nursing care. The health manpower is the supplier, and their professional knowledge and ability and the patients' trust in medical technology are the most important factors for their customers. In addition, service design has come into the spotlight given that the medical institute system, health manpower attitude, and information delivery system and touch point are considered important factors contributing to customer satisfaction. It is very hard to satisfy customers only through professionalism, the environment, and product improvement because healthcare service deals with much more sensitive and emotional customers compared to other service industries. This means that a change in the service mind-set and the attitude of the health manpower as emotional labourers have practical effects. Therefore, the fundamental solution is to establish a system that provides related education with manpower and that settles various problems by itself. This paper introduces several solutions, such as education for health manpower and a service design system applied to a national-university-affiliated hospital in South Korea, and takes a close look at its effects.

Response Modeling for the Marketing Promotion with Weighted Case Based Reasoning Under Imbalanced Data Distribution (불균형 데이터 환경에서 변수가중치를 적용한 사례기반추론 기반의 고객반응 예측)

  • Kim, Eunmi;Hong, Taeho
    • Journal of Intelligence and Information Systems
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    • v.21 no.1
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    • pp.29-45
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    • 2015
  • Response modeling is a well-known research issue for those who have tried to get more superior performance in the capability of predicting the customers' response for the marketing promotion. The response model for customers would reduce the marketing cost by identifying prospective customers from very large customer database and predicting the purchasing intention of the selected customers while the promotion which is derived from an undifferentiated marketing strategy results in unnecessary cost. In addition, the big data environment has accelerated developing the response model with data mining techniques such as CBR, neural networks and support vector machines. And CBR is one of the most major tools in business because it is known as simple and robust to apply to the response model. However, CBR is an attractive data mining technique for data mining applications in business even though it hasn't shown high performance compared to other machine learning techniques. Thus many studies have tried to improve CBR and utilized in business data mining with the enhanced algorithms or the support of other techniques such as genetic algorithm, decision tree and AHP (Analytic Process Hierarchy). Ahn and Kim(2008) utilized logit, neural networks, CBR to predict that which customers would purchase the items promoted by marketing department and tried to optimized the number of k for k-nearest neighbor with genetic algorithm for the purpose of improving the performance of the integrated model. Hong and Park(2009) noted that the integrated approach with CBR for logit, neural networks, and Support Vector Machine (SVM) showed more improved prediction ability for response of customers to marketing promotion than each data mining models such as logit, neural networks, and SVM. This paper presented an approach to predict customers' response of marketing promotion with Case Based Reasoning. The proposed model was developed by applying different weights to each feature. We deployed logit model with a database including the promotion and the purchasing data of bath soap. After that, the coefficients were used to give different weights of CBR. We analyzed the performance of proposed weighted CBR based model compared to neural networks and pure CBR based model empirically and found that the proposed weighted CBR based model showed more superior performance than pure CBR model. Imbalanced data is a common problem to build data mining model to classify a class with real data such as bankruptcy prediction, intrusion detection, fraud detection, churn management, and response modeling. Imbalanced data means that the number of instance in one class is remarkably small or large compared to the number of instance in other classes. The classification model such as response modeling has a lot of trouble to recognize the pattern from data through learning because the model tends to ignore a small number of classes while classifying a large number of classes correctly. To resolve the problem caused from imbalanced data distribution, sampling method is one of the most representative approach. The sampling method could be categorized to under sampling and over sampling. However, CBR is not sensitive to data distribution because it doesn't learn from data unlike machine learning algorithm. In this study, we investigated the robustness of our proposed model while changing the ratio of response customers and nonresponse customers to the promotion program because the response customers for the suggested promotion is always a small part of nonresponse customers in the real world. We simulated the proposed model 100 times to validate the robustness with different ratio of response customers to response customers under the imbalanced data distribution. Finally, we found that our proposed CBR based model showed superior performance than compared models under the imbalanced data sets. Our study is expected to improve the performance of response model for the promotion program with CBR under imbalanced data distribution in the real world.

Determination of the Levels of Bisphenol A Diglycidyl Ether (BADGE), Bisphenol F Diglycidyl Ether (BFDGE) and Their Reaction Products in Canned Foods Circulated at Korean Markets (캔 제품의 bisphenol A diglycidyl ether (BADGE), bisphenol F diglycidyl ether (BFDGE) 유도체 및 분해산물 분석법)

  • Kim, Hee-Yun;Lee, Jin-Sook;Cho, Min-Ja;Yang, Ji-Yeon;Baek, Ji-Yun;Cheong, So-Young;Choi, Sun-Hee;Kim, Young-Seon;Choi, Jae-Chun
    • Korean Journal of Food Science and Technology
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    • v.42 no.1
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    • pp.8-13
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    • 2010
  • Bisphenol A diglycidyl ether (BADGE) and bisphenol F diglycidyl ether (BFDGE) were obtained by a polymerization reaction of epichlorohydrin (ECH) with bisphenol A (BPA) or bisphenol F (BPF). These compounds are commonly used as monomers or additives such as a polymerization stabilizer and a hydrochloric acid scavenger of epoxy resin, polyvinyl chloride (PVC)-containing organosols and polyester lacquers, that are applied to the internal surface of most canned foods to impart chemical resistance. The unreacted BADGE, BFDGE and their reaction products migrating from epoxy resin, PVC-containing organosol and/or polyester lacquer-based food packaging materials into the foods have recently become an issue of great concern because of increased customer demand for safety. This study was conducted to develop a rapid and sensitive simultaneous analysis method based on HPLC/FLD and HPLC/APCI-mass and to evaluate the concentration of BADGE, BFDGE and their metabolites, BADGE $H_2O$, BADGE $2H_2O$, BADGE HCl, BADGE 2HCl, BADGE HCl $H_2O$, BFDGE $H_2O$, BFDGE $2H_2O$, BFDGE HCl, BFDGE 2HCl and BFDGE HCl $H_2O$ for 133 canned food samples. The method provided a linearity of 0.9997-0.9999, a limit of detection of $0.01-0.13\;{\mu}g/mL$, a limit of quantitation of $0.03-0.44\;{\mu}g/mL$ and a recovery (%) of 85.64-118.18. The number of samples containing BADGE, BFDGE or their metabolites were: 28/133 (21.1%), with levels of 0.400-0.888 mg/kg being observed for aqueous foods (19/133) and 0.093-0.506 mg/kg being observed for oily foods (9/133).

A Study for strategic cooperaton of enterprise security and business (기업보안과 비즈니스의 전략적 협력에 관한 연구)

  • Ryu, Hyung-Chang
    • Korean Security Journal
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    • no.28
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    • pp.103-130
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    • 2011
  • This study is the research of enterprise security for raising the profitability and stability of Korean companies in global business environment and strategic cooperation of business. As the scientific technology gets complicated as day goes by and new competitors appear regardless the border in the modern business environment, the situation happens frequently which the huge company hands over their market to the new one armed with the innovative thinking overnight. To survive such new environment, the answer is the change of paradigm regarding business management method at the new point of view. With the low level of security risk management of Korean companies which stick to old habit, the security management which helps the companies secure profits is not affordable. The global village where the population of 7 billions live in 21st century is facing up to the rapid ecological adaptation. The rapid change of climatic environment creates the hundreds of thousands of sufferers in a moment, and we have been watching the millions of livestock are buried alive due to new contagious disease everyday. Such change encourages the humans in global village to change the basic way of living. The business ecosystem which is the basic root for economic life cannot be an exception. To survive the business environment of 21st century, the security risk management at management level is required and the reporting line of companies should be established newly for raising business competing power through security risk management. The companies should bear in mind that they can be disappeared into our old memories overnight if they are not sensitive to the changing environment. Out of new risks for the modern companies, the field especially Korean companies are dealing easily is the security risk. Not like past, the security risk which's size is much more massive and its propagation velocity is very fast is the one of important business risks which the management should take care. Out of security risks which influence on the modern companies significantly, the brand of companies, protection of their reputation, continuity of production and operation and keeping customer's trust are prior to the others. This study offered the suggestion regarding enterprise security and the strategic cooperation of business to deal with such security risk effectively.

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Extension Method of Association Rules Using Social Network Analysis (사회연결망 분석을 활용한 연관규칙 확장기법)

  • Lee, Dongwon
    • Journal of Intelligence and Information Systems
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    • v.23 no.4
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    • pp.111-126
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    • 2017
  • Recommender systems based on association rule mining significantly contribute to seller's sales by reducing consumers' time to search for products that they want. Recommendations based on the frequency of transactions such as orders can effectively screen out the products that are statistically marketable among multiple products. A product with a high possibility of sales, however, can be omitted from the recommendation if it records insufficient number of transactions at the beginning of the sale. Products missing from the associated recommendations may lose the chance of exposure to consumers, which leads to a decline in the number of transactions. In turn, diminished transactions may create a vicious circle of lost opportunity to be recommended. Thus, initial sales are likely to remain stagnant for a certain period of time. Products that are susceptible to fashion or seasonality, such as clothing, may be greatly affected. This study was aimed at expanding association rules to include into the list of recommendations those products whose initial trading frequency of transactions is low despite the possibility of high sales. The particular purpose is to predict the strength of the direct connection of two unconnected items through the properties of the paths located between them. An association between two items revealed in transactions can be interpreted as the interaction between them, which can be expressed as a link in a social network whose nodes are items. The first step calculates the centralities of the nodes in the middle of the paths that indirectly connect the two nodes without direct connection. The next step identifies the number of the paths and the shortest among them. These extracts are used as independent variables in the regression analysis to predict future connection strength between the nodes. The strength of the connection between the two nodes of the model, which is defined by the number of nodes between the two nodes, is measured after a certain period of time. The regression analysis results confirm that the number of paths between the two products, the distance of the shortest path, and the number of neighboring items connected to the products are significantly related to their potential strength. This study used actual order transaction data collected for three months from February to April in 2016 from an online commerce company. To reduce the complexity of analytics as the scale of the network grows, the analysis was performed only on miscellaneous goods. Two consecutively purchased items were chosen from each customer's transactions to obtain a pair of antecedent and consequent, which secures a link needed for constituting a social network. The direction of the link was determined in the order in which the goods were purchased. Except for the last ten days of the data collection period, the social network of associated items was built for the extraction of independent variables. The model predicts the number of links to be connected in the next ten days from the explanatory variables. Of the 5,711 previously unconnected links, 611 were newly connected for the last ten days. Through experiments, the proposed model demonstrated excellent predictions. Of the 571 links that the proposed model predicts, 269 were confirmed to have been connected. This is 4.4 times more than the average of 61, which can be found without any prediction model. This study is expected to be useful regarding industries whose new products launch quickly with short life cycles, since their exposure time is critical. Also, it can be used to detect diseases that are rarely found in the early stages of medical treatment because of the low incidence of outbreaks. Since the complexity of the social networking analysis is sensitive to the number of nodes and links that make up the network, this study was conducted in a particular category of miscellaneous goods. Future research should consider that this condition may limit the opportunity to detect unexpected associations between products belonging to different categories of classification.

The Effect of Price Discount Rate According to Brand Loyalty on Consumer's Acquisition Value and Transaction Value (브랜드애호도에 따른 가격할인율의 차이가 소비자의 획득가치와 거래가치에 미치는 영향)

  • Kim, Young-Ei;Kim, Jae-Yeong;Shin, Chang-Nag
    • Journal of Global Scholars of Marketing Science
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    • v.17 no.4
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    • pp.247-269
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    • 2007
  • In recent years, one of the major reasons for the fierce competition amongst firms is that they strive to increase their own market shares and customer acquisition rate in the same market with similar and apparently undifferentiated products in terms of quality and perceived benefit. Because of this change in recent marketing environment, the differentiated after-sales service and diversified promotion strategies have become more important to gain competitive advantage. Price promotion is the favorite strategy that most retailers use to achieve short-term sales increase, induce consumer's brand switch, in troduce new product into market, and so forth. However, if marketers apply or copy an identical price promotion strategy without considering the characteristic differences in product and consumer preference, it will cause serious problems because discounted price itself could make people skeptical about product quality, and the changes of perceived value might appear differently depending on other factors such as consumer involvement or brand attitude. Previous studies showed that price promotion would certainly increase sales, and the discounted price compared to regular price would enhance the consumer's perceived values. On the other hand, discounted price itself could make people depreciate or skeptical about product quality, and reduce the consumers' positivity bias because consumers might be unsure whether the current price promotion is the retailer's best price offer. Moreover, we cannot say that discounted price absolutely enhances the consumer's perceived values regardless of product category and purchase situations. That is, the factors that affect consumers' value perceptions and buying behavior are so diverse in reality that the results of studies on the same dependent variable come out differently depending on what variable was used or how experiment conditions were designed. Majority of previous researches on the effect of price-comparison advertising have used consumers' buying behavior as dependent variable. In order to figure out consumers' buying behavior theoretically, analysis of value perceptions which influence buying intentions is needed. In addition, they did not combined the independent variables such as brand loyalty and price discount rate together. For this reason, this paper tried to examine the moderating effect of brand loyalty on relationship between the different levels of discounting rate and buyers' value perception. And we provided with theoretical and managerial implications that marketers need to consider such variables as product attributes, brand loyalty, and consumer involvement at the same time, and then establish a differentiated pricing strategy case by case in order to enhance consumer's perceived values properl. Three research concepts were used in our study and each concept based on past researches was defined. The perceived acquisition value in this study was defined as the perceived net gains associated with the products or services acquired. That is, the perceived acquisition value of the product will be positively influenced by the benefits buyers believe they are getting by acquiring and using the product, and negatively influenced by the money given up to acquire the product. And the perceived transaction value was defined as the perception of psychological satisfaction or pleasure obtained from taking advantage of the financial terms of the price deal. Lastly, the brand loyalty was defined as favorable attitude towards a purchased product. Thus, a consumer loyal to a brand has an emotional attachment to the brand or firm. Repeat purchasers continue to buy the same brand even though they do not have an emotional attachment to it. We assumed that if the degree of brand loyalty is high, the perceived acquisition value and the perceived transaction value will increase when higher discount rate is provided. But we found that there are no significant differences in values between two different discount rates as a result of empirical analysis. It means that price reduction did not affect consumer's brand choice significantly because the perceived sacrifice decreased only a little, and customers are satisfied with product's benefits when brand loyalty is high. From the result, we confirmed that consumers with high degree of brand loyalty to a specific product are less sensitive to price change. Thus, using price promotion strategy to merely expect sale increase is not recommendable. Instead of discounting price, marketers need to strengthen consumers' brand loyalty and maintain the skimming strategy. On the contrary, when the degree of brand loyalty is low, the perceived acquisition value and the perceived transaction value decreased significantly when higher discount rate is provided. Generally brands that are considered inferior might be able to draw attention away from the quality of the product by making consumers focus more on the sacrifice component of price. But considering the fact that consumers with low degree of brand loyalty are known to be unsatisfied with product's benefits and have relatively negative brand attitude, bigger price reduction offered in experiment condition of this paper made consumers depreciate product's quality and benefit more and more, and consumer's psychological perceived sacrifice increased while perceived values decreased accordingly. We infer that, in the case of inferior brand, a drastic price-cut or frequent price promotion may increase consumers' uncertainty about overall components of product. Therefore, it appears that reinforcing the augmented product such as after-sale service, delivery and giving credit which is one of the levels consisting of product would be more effective in reality. This will be better rather than competing with product that holds high brand loyalty by reducing sale price. Although this study tried to examine the moderating effect of brand loyalty on relationship between the different levels of discounting rate and buyers' value perception, there are several limitations. This study was conducted in controlled conditions where the high involvement product and two different levels of discount rate were applied. Given the presence of low involvement product, when both pieces of information are available, it is likely that the results we have reported here may have been different. Thus, this research results explain only the specific situation. Second, the sample selected in this study was university students in their twenties, so we cannot say that the results are firmly effective to all generations. Future research that manipulates the level of discount along with the consumer involvement might lead to a more robust understanding of the effects various discount rate. And, we used a cellular phone as a product stimulus, so it would be very interesting to analyze the result when the product stimulus is an intangible product such as service. It could be also valuable to analyze whether the change of perceived value affects consumers' final buying behavior positively or negatively.

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