With the enormous growth and various applications of private brands, national brand manufacturers are confronted with a dilemmatic situation. That is, paradoxically, some manufacturers have come to produce private brands of retailers which are potential competitors to their own brands. This study reveals why manufacturers with their own brands let themselves do the consignment production of retailers' private brands although those private brands may become strong competitors of their own brands and then investigates the condition in which manufacturers may benefit from such consignment production. Through an analysis of a game theoretical model assuming a monopoly market, the present study presents the theoretical backgrounds and provides new insights about consignment production of manufacturer with its own brand for retailer's private brand. First, such consignment production can play a role in mitigating the loss in the consignee manufacturer's own brand sales caused by the private brand in the competitive environment. Second, the effectiveness of such role is affected by the quality of the private brand produced under consignment. In other word, only if the consignee manufacturer keeps the quality of the private brand low, the manufacturer can maintain the benefit from its own brand. In addition, a consigner retailer needs to consider the final objective of launching its private brand, when it chooses its consignee manufacturer of the brand. Finally, a manufacturer with its own brand may consider consignment production as not merely an unavoidable option compelled by a retailer's power but a reasonable strategic choice to reduce the risk from competition.

The Semantic Web technology, purporting to share, to reuse and to process by machines data stored in the Web environment, incessantly evolves to help human decision making; in particular, decision making based on data, or quantitative decision making. This trend drives researchers to fill the gap with strenuous efforts between the current state of the technology and the terminus of this evolution. The Semantic Web Constraint Language (SWCL) together with SWRL is one of these endeavors to achieve the goal. This paper focuses particularly on how to express the piecewise linear form in the context of SWCL. The importance of this ingredient can be fortified by the fact that any nonlinear expression can be approximated in the piecewise linear form. This paper will also provide the information of how it will work in the decision making process through an example of the Internet shopping mall problem.

The existing DEA models have been devoted to evaluate relative efficiency of DMUs based on multiple input and output factors of a same period. However, a certain kind of lead time can be required to produce outputs using inputs in an organization. R&D evaluation is a typical area with this kinds of time lag. Thus, the purpose of this paper is to develop a new DEA model to deal with time lag effect in performance evaluation. The proposed model is to find relative efficiency of each DMU for each period considering the time lag effect. A case example using a real data set is also given to show the usage or implication of the suggested model. The results are compared with the ones of the CCR model and the multi-periods input model.

Battery switching EVs are considered to be a promising alternative to overcome long charging time problems in the EV adoption. The purpose of this research is to develop integrated model for battery inventory and battery switching waiting times. Due to complexity of exact analysis, a practical approximation method is developed, which provides close results to exact values. Numerical experiments show that there exist trade-offs between the battery inventory level and the number of switching stations. The proposed model can be applied to evaluate and select the minimum cost alternative in implementing the battery switching stations.

In this paper a new method of handling linear constraints for the genetic algorithm is suggested. The method is designed to maintain the feasibility of offsprings during the evolution process of the genetic algorithm. In the genetic algorithm, the chromosomes are coded as the vectors in the real vector space constrained by the linear constraints. A method of handling the linear constraints already exists in which all the constraints of equalities are eliminated so that only the constraints of inequalities are considered in the process of the genetic algorithm. In this paper a new method is presented in which all the constraints of inequalities are eliminated so that only the constraints of equalities are considered. Several genetic operators such as arithmetic crossover, simplex crossover, simple crossover and random vector mutation are designed so that the resulting offspring vectors maintain the feasibility subject to the linear constraints in the framework of the new handling method.

In recent years, service delivery systems employing a self-service approach have been rapidly spreading. Since a self-service system provides a lower product price, it attracts more customers. However, some system managers are still hesitant to accept a self-service system, because there is no systematic model to predict its performance. Therefore, this research attempts to provide a systematic and quantitative model to predict the performance of a self-service system, focused specifically on a self-service gas station. Under this model, the traditional queuing theory was adopted to describe the general self-service process, but it is also assumed that some changes occur in both the customer arrival rate and the service performance rate. In particular, the price elasticity was introduced to capture the change in the customer arrival rate, and the existence of learning effect and helpers were assumed to design the changed service performance rate. Under these assumptions, a simulation model for a self-service gas station is established, and three performance measurements, such as average number of customers, average waiting time, and Utilization are observed, depending on the changes in price difference and helper-operating time. In this research, the optimal operation strategy for price differentiation and helper-operating time is proposed in accordance with the level of the customer learning rate. Although this research confines the scope of the study to the self-service gas station model, the results of this research can be applied to any type of self-service system.

Being able to quickly locate valuable medical equipment is critical inside hospitals. In order to utilize limited budget and resources efficiently, accurate locating or tracking is required in many fields. In this research, we focus on how to find the location of missing assets by using RFID in real time indoors to track equipment. When equipment needs to be searched, the purpose of a RFID device is to minimize the time, investment cost and effort spent searching for the equipment. Thus, this research presents a mathematical model of using RFID (both handheld reader and stationary reader) for efficient asset location. We derive the expected time of locating RFID-tagged objects in a multi-area environment where hand-held RF readers are used. We then discuss where to deploy stationary RF readers in order to maximize the efficiency of the search process.

Emergency room process is very important in the whole hospital processes because it is first diagnosis for patient. Above all, triage is important activity which quickly diagnose the status of emergency patient and sets the priority for treatment. This paper analyzes the treatment process pattern by triage type. The results show that the treatment process after triage such as residence time, diagnosis and checkup type, and joint treatment are dependent on triage types. We can use these analysis results for improving the current triage system and developing the new triage system considering a domestic emergency medical service environment.

Health care that is considered to be one of the major factors for the quality of life is nowadays receiving a great deal of attention, and thus there is a growing need in Korea to identify the efficiency of national medical service and enhance the competitiveness. Although there exist studies on the medical service efficiency about general hospitals and local hospitals, they mostly deal with the efficiency problems from a domestic and regional perspective. In response, this paper analyzes the competitive efficiency of national medical service with respect to 16 OECD countries, by exploiting Data Envelopment Analysis (DEA) and Malmquist Productivity Index (MPI). Building on the DEA and MPI analysis results, this paper identifies the competitive position of Korean national medical service and suggests implications for the medical service improvement.

This paper introduces an Internet-based generic simulator for outpatient clinics, named PIOS (Postech Internet-based Outpatient Simulator). Unlike other simulation tools, PIOS is operated on the Internet, is straightforward to use for outpatient process analysis, and is open to public via http://logistics.postech.ac.kr/pios with free of charge. Therefore, non-simulation expert users such as hospital administrators and managers can easily access to PIOS and conduct simulation study by themselves. In this paper, we describe the main components and programming logic of PIOS, and demonstrate its validity by comparing the output results of PIOS and a commercial software package.

This study investigates how discrete choice analysis can be applied to health care operations. Discrete choice analysis helps to understand the complex decision-making process of purchasing expensive medical equipments by identifying relative weights that decision makers impose on each attribute through simple virtual choice experiments. We also verified the usefulness of applying discrete choice analysis to the purchase of medical equipments with empirical evidence.

We develop some evaluation tool and indicators for the scores for medical equipment replacement in hospital. There has been no research for Korean hospitals although there are many for foreign medical institutions. In this paper, among many variables that were obtained from the previous studies, eleven variables are selected as indicators and tied as three groups. And then we obtain scores of medical equipments based on the weighted values of those indicators. We can make decisions whether we replace medical equipments or not by ranking the medical equipments based on the scores. This paper shows that we can make decisions to replace medical equipments very objectively and effectively using the evaluation tool and indicators we develop.

The purpose of this study is to evaluate of the perception, elements and quality level of business strategy in domestic hospitals. We analyze survey data about strategy. Significantly, we find that domestic hospitals were greatly feeling about the necessity and importance of strategy, but elements and quality level of actual execution strategy is much lower. When evaluating level on the perception, elements and quality of strategy within each of Miles and Snow's strategy type, PA(prospector+analyzer) was higher than DR(defender+reactor). And result of structural equation modeling(SEM), elements had a significant influence on the quality of the strategy, a positive relationship between the components and the PA have been identified. Therefore, we propose that to increase the elements level in order to improve the quality level of strategy, and hospital administrators are need to be PA rather than DR.

This paper studies an emergency service vehicle location problem, where minimum reliability level pre-specified at each demand point is assured. Several models are suggested depending on the busy fraction, which is the time proportion of unavailability for the ambulances. In this paper a new model on computing the busy fraction is suggested, where it varies depending on the distance between the demand point and ambulances, hence it may respond the more realistic situation. The busy fraction for the ambulance location determined by the optimization model is computed by the simulation, and updated through the iterative procedure. It has been shown that the performances of the solutions obtained by the algorithm suggested for the instances appeared in the literature.

This study purposed to evaluate the influences of rival hospitals on the number of patients who visited the a study territory hospital. Spatial analysis technique was used to measure the impact of rival hospitals in study region. Selected hospitals were all medical school affiliated hospitals which were located in Daejeon metropolitan city and Chungchungnamdo. Patient data was collected from the claims data of the study hospital, and the number of inpatient and outpatients who visited the study hospital between January and June in 2008 were calculated on the smallest administrative district, Eup, Myeon, and Dong, in study region. To control the differences of regional characteristics among Eup, Myeon, Dong, socio-economic variables (total population, number of people aged over 65, number of basic livelihood security recipients, distance from the study hospital to the centroid point of each Eup, Myeon, Dong, number of business, and number of employees) were included in analysis model. These variables were collected from the annual year book of city as well as county located in study region. Cluster analysis classified the study region into three groups by using the difference of between th actual number of inpatient/outpatient and the predicted number of inpatient/outpatient in Eup, Myeon, and Dong. Most areas around the rivalry hospitals were categorized into same group. Multiple regression analysis indicated that areas around rivalry hospitals had statistically significantly negative relationship with the number of inpatients and outpatients who visited the study hospital. As the buffer size was increased from 5Km to 10Km, the standardized regression coefficients were decreased. These study results confirmed that rivalry hospitals in region had negative impacts on the performance of hospitals. It suggests that hospitals will require not only to select their location to minimize the effects of rivalry hospitals, but also to establish their strategy to cope with the rivalry's threats in their region.

The purpose of this study is to examine the factors influencing usage intention of u-Healthcare with voluntariness in long-term care hospitals. This model tests various theoretical research hypotheses relating to u-Healthcare, UTAUT theory and voluntariness. The proposed model is analyzed to target long-term care hospitals. Questionnaires have been collected during two months of 2010 and total 142 has been considered to be valid. Smart PLS (partial least square) 2.0 and SPSS 15.0 have been utilized for deriving the study results. The results of hypothesis testing are as follows. First, performance expectance, effort expectancy and social influence positively influence usage intention. Second, facilitation not influence usage intention. Still due to lack of technical infrastructure to promote conditions of use u-Healthcare in long-care hospitals for u-Healthcare system also considered to be not significantly affected. Finally, performance expectance to usage intention for low voluntariness group is significantly larger than those for high voluntariness group. In addition, social influence to usage intention for high voluntarines group is significantly larger than those for low voluntariness group.