• Journal of Intelligence and Information Systems
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• 제17권3호
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• pp.115-130
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• 2011

Many online stores bring features that can build trust in their customers. More so, the number of products or content services on online stores has been increasing rapidly. Hence, personalization on online stores is considered to be an important technology to companies and customers. Recommender systems that provide favorable products and customer product reviews to users are the most commonly used features in this purpose. There are many studies to that investigated the relationship between social presence as an antecedent of trust and provision of recommender systems or customer product reviews. Many online stores have made efforts to increase perceived social presence of their customers through customer reviews, recommender systems, and analyzing associations among products. Primarily because social presence can increase customer trust or reuse intention for online stores. However, there were few studies that investigated the interactions between recommendation type, product type and provision of customer product reviews on social presence. Therefore, one of the purposes of this study is to identify the effects of personalized recommender systems and compare the role of customer reviews with product types. This study performed an experiment to see these interactions. Experimental web pages were developed with $2{\times}2$ factorial setting based on how to provide social presence to users with customer reviews and two product types such as hedonic and utilitarian. The hedonic type was a ringtone chosen from Nate.com while the utilitarian was a TOEIC study aid book selected from Yes24.com. To conduct the experiment, web based experiments were conducted for the participants who have been shopping on the online stores. Participants were a total of 240 and 30% of the participants had the chance of getting the presents. We found out that social presence increased for hedonic products when personalized recommendations were given compared to non.personalized recommendations. Although providing customer reviews for two product types did not significantly increase social presence, provision of customer product reviews for hedonic (ringtone) increased perceived social presence. Otherwise, provision of customer product reviews could not increase social presence when the systems recommend utilitarian products (TOEIC study.aid books). Therefore, it appears that the effects of increasing perceived social presence with customer reviews have a difference for product types. In short, the role of customer reviews could be different based on which product types were considered by customers when they are making a decision related to purchasing on the online stores. Additionally, there were no differences for increasing perceived social presence when providing customer reviews. Our participants might have focused on how recommendations had been provided and what products were recommended because our developed systems were providing recommendations after participants rating their preferences. Thus, the effects of customer reviews could appear more clearly if our participants had actual purchase opportunity for the recommendations. Personalized recommender systems can increase social presence of customers more than nonpersonalized recommender systems by using user preference. Online stores could find out how they can increase perceived social presence and satisfaction of their customers when customers want to find the proper products with recommender systems and customer reviews. In addition, the role of customer reviews of the personalized recommendations can be different based on types of the recommended products. Even if this study conducted two product types such as hedonic and utilitarian, the results revealed that customer reviews for hedonic increased social presence of customers more than customer reviews for utilitarian. Thus, online stores need to consider the role of providing customer reviews with highly personalized information based on their product types when they develop the personalized recommender systems.

• Journal of the Korea Academia-Industrial cooperation Society
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• 제10권5호
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• pp.1060-1064
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• 2009

This paper proposes a fuzzy AHP based decision-making model to select a telecommunication company and the target of the proposed model is university students in the capital area. When customers select a telecommunication company, they have difficulty in decision-making because there are many competitive and complementary factors of telecommunication companies. To select a best telecommunication company, customers need to consider a number of different quantitative and qualitative factors such as fare, various services, additional function, etc. In this study, we suggest a fuzzy AHP based decision-making model to select a telecommunication company considering various quantitative and qualitative factors. Especially, fuzzy theory is applied to deal with the unclear or ambiguous problems, and a linear normalization model is developed to convert the value of quantitative factors to fuzzy number. A empirical example which is the target of the university students in the capital area shows the feasibility of the proposed model and it can help customers to make better decision-making for their benefits.

• Journal of the Korea Safety Management & Science
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• 제14권4호
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• pp.153-168
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• 2012

It has been recognized as an important issue to design optimally a firm's logistics network for minimizing logistics cost and maximizing customer service. It is, however, not easy to get an optimal solution by analyzing trade-off of cost factors, dynamic and interdependent characteristics in the logistics network decision making. Although there has been some developments in a system which helps decision making for logistics analysis, it is true that there is no system for enterprise-wise's on-site support and methodical logistics decision. Specially, E-biz process along with information technology has been made dramatic advance in a various industries, there has been much need for practical education closely resembles on-site work. The software developed by this study materializes efficient algorithm suggested by recent studies in key topics of logistics such as location and allocation problem, traveling salesman problem, and vehicle routing problem and transportation and distribution problem. It also supports executing a variety of experimental design and analysis in a way of the most user friendly based on Java. In the near future, we expect that it can be extended to integrated supply chain solution by adding decision making in production in addition to a decision in logistics.

• Journal of Korean Institute of Industrial Engineers
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• 제21권3호
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• pp.345-356
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• 1995

The aim of this paper is to analyze the batch service queueing model M/M(a, b ; ${\mu}_k/1$) under general bulk service rule with mean service rate ${\mu}_k$ for a batch of k units, where $a{\leq}k{\leq}b$. This queueing model consists of the two-dimensional state space so that it is characterized by two-dimensional state Markov process. The steady-state solution and performane measure of this process are derived by using Matrix Geometric method. Meanwhile, a new approach is suggested to calculate the two-dimensional traffic density R which is used to obtain the steady-state solution. In addition, to determine the optimal service initiation threshold a, a decision model of this queueing system is developed evaluating cost of service per batch and cost of waiting per customer. In a job order production system, the decision-making procedure presented in this paper can be applicable to determining when production should be started.

• IE interfaces
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• 제21권4호
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• pp.444-455
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• 2008

In the present manufacturing environment, the appropriate decision making strategy has a significance and it should count on the fast-changing demand of customers. This research derives the optimal levels of the decision variables affecting the inventory related performance in multi-stage supply chain by using simulation and genetic algorithm. Simulation model helps analyze the customer service level of the supply chain computationally and the genetic algorithm searches the optimal solutions by interaction with the simulation model. Our experiments show that the integration approach of the genetic algorithm with a simulation model is effective in finding the solutions that achieve predefined target service levels.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 한국퍼지및지능시스템학회 2007년도 춘계학술대회 학술발표 논문집 제17권 제1호
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• pp.221-224
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• 2007

This report contains information about "System Selection Assistant"(SSA) - Program, which can help customers of manufacturing company to select optimal electro-mechanical system for their purposes. This Program shows main principles of programs, which can help to make decision, using knowledge of experts. Program consists of two main parts: "Expert's part" must be tuned by expert and "Customer's part" can be used to make final decision about optimal parts of system. This report describes all parts of SSA program and shows simple example of selection parts of electro-mechanical system.

• Journal of the Korean Operations Research and Management Science Society
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• 제31권3호
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• pp.81-96
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• 2006

We consider a rental company that dynamically manages Its capacity level through capacity addition and return While serving customer with its own capacity, the company expands its capacity by renting items from an outside source so that it can avoid lost opportunities of rental which occur when stock is not sufficient. If stock becomes sufficiently large enough to cope with demands, the company returns expanded capacity to the outside source. Formulating the model into a Markov decision problem, we identify an optimal capacity management Policy which states when the company should expand its capacity and when it should return expanded capacity after capacity addition. Since it is intractable to analytically find the optimal capacity management policy and the optimal size of capacity expansion, we present a numerical procedure that finds these optimal values based on the value iteration method. Numerical analysis is implemented and we observe monotonic properties of the optimal performance measures by system parameters, which are meaningful in developing effective heuristic policies.

• Journal of the Korean Operations Research and Management Science Society
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• 제29권3호
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• pp.111-127
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• 2004

We consider a supply chain model with a make-to-order production facility and a single supplier. The model we treat here is a special case of a two-echelon inventory model. Unlike classical two-echelon systems, the demand process at the supplier is affected by production process at the production facility as well as customer order arrival process. In this paper, we address that how the demand variability impacts on the optimal replenishment policy. To this end, we incorporate Erlang and phase-type demand distributions into the model. Formulating the model as a Markov decision problem, we investigate the structure of the optimal replenishment policy. We also implement a sensitivity analysis on the optimal policy and establish its monotonicity with respect to system cost parameters.

• IE interfaces
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• 제11권3호
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• pp.181-191
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• 1998

In the make-to-order (MTO) manufacturing environment, one of the important issues is setting attainable delivery dates for customer orders, which significantly affects the performance of the MTO manufacturing. Although this topic has received considerable attention in the literature, most of the efforts took a lower level approach that is concerned primarily with the effect of various delivery date assignment methods on the relative performance of some dispatching rules. This paper proposes the delivery date decision support system which takes a higher level approach of integrating the marketing and production planning functions with the consideration of the current capacity and the workload smoothing. The proposed system has been implemented in a Rotating Machinery Shop and the results of the implementation showed good performance.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 한국경영과학회/대한산업공학회 2003년도 춘계공동학술대회
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• pp.508-515
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• 2003

There are various methods to assess to company's outcome. Among them, the customers satisfaction, which is assessed by customers, is the most important. If the customers satisfaction is measured by the CSI based on the proper reliability and validity, you can apply the result for various marketing methods. Therefore, this study develops a model to assess CSI for an industry, specifically, local automotive industry based on the SEM that is already proven valid through assessing models such as ACSI, KCSI and NCSI. Moreover, this research can be utilized for marketing strategy helping customers to decide as an AHP model, one of the decision making method.