• Journal of Intelligence and Information Systems
• /
• v.20 no.1
• /
• pp.49-65
• /
• 2014

Word of Mouth (WOM) is a behavior used by consumers to transfer or communicate their product or service experience to other consumers. Due to the popularity of social media such as Facebook, Twitter, blogs, and online communities, electronic WOM (e-WOM) has become important to the success of products or services. As a result, most enterprises pay close attention to e-WOM for their products or services. This is especially important for movies, as these are experiential products. This paper aims to identify the network factors of an online movie community that impact box office revenue using social network analysis. In addition to traditional WOM factors (volume and valence of WOM), network centrality measures of the online community are included as influential factors in box office revenue. Based on previous research results, we develop five hypotheses on the relationships between potential influential factors (WOM volume, WOM valence, degree centrality, betweenness centrality, closeness centrality) and box office revenue. The first hypothesis is that the accumulated volume of WOM in online product communities is positively related to the total revenue of movies. The second hypothesis is that the accumulated valence of WOM in online product communities is positively related to the total revenue of movies. The third hypothesis is that the average of degree centralities of reviewers in online product communities is positively related to the total revenue of movies. The fourth hypothesis is that the average of betweenness centralities of reviewers in online product communities is positively related to the total revenue of movies. The fifth hypothesis is that the average of betweenness centralities of reviewers in online product communities is positively related to the total revenue of movies. To verify our research model, we collect movie review data from the Internet Movie Database (IMDb), which is a representative online movie community, and movie revenue data from the Box-Office-Mojo website. The movies in this analysis include weekly top-10 movies from September 1, 2012, to September 1, 2013, with in total. We collect movie metadata such as screening periods and user ratings; and community data in IMDb including reviewer identification, review content, review times, responder identification, reply content, reply times, and reply relationships. For the same period, the revenue data from Box-Office-Mojo is collected on a weekly basis. Movie community networks are constructed based on reply relationships between reviewers. Using a social network analysis tool, NodeXL, we calculate the averages of three centralities including degree, betweenness, and closeness centrality for each movie. Correlation analysis of focal variables and the dependent variable (final revenue) shows that three centrality measures are highly correlated, prompting us to perform multiple regressions separately with each centrality measure. Consistent with previous research results, our regression analysis results show that the volume and valence of WOM are positively related to the final box office revenue of movies. Moreover, the averages of betweenness centralities from initial community networks impact the final movie revenues. However, both of the averages of degree centralities and closeness centralities do not influence final movie performance. Based on the regression results, three hypotheses, 1, 2, and 4, are accepted, and two hypotheses, 3 and 5, are rejected. This study tries to link the network structure of e-WOM on online product communities with the product's performance. Based on the analysis of a real online movie community, the results show that online community network structures can work as a predictor of movie performance. The results show that the betweenness centralities of the reviewer community are critical for the prediction of movie performance. However, degree centralities and closeness centralities do not influence movie performance. As future research topics, similar analyses are required for other product categories such as electronic goods and online content to generalize the study results.

• Journal of forensic and investigative science
• /
• v.2 no.2
• /
• pp.5-20
• /
• 2007

During the period from 2001 to 2005, 29,892 burglaries took place in Korea with the approximate average annual number - 5,978 cases. This study was conducted to analyze the reported burglaries and the result was summarized as follows. There were 8,605 residential invasion burglaries (28.8%) as the most frequent characteristic pattern. The exit was used as the most frequent invasion route for 4,031 invasion burglaries (64.3%), and an unlocked exit door or window was used as the most frequent invasion method for 2,462 invasion burglaries (28.6%). The hours just after midnight (between 00:00 and 04:00) were the most frequent time for invasion burglary to occur. Also, 5,652 burglaries occurred on Wednesday which was twice higher than on Sunday (2,988 burglaries). It was shown that the number of persons injured during burglaries were 260 deaths and 10,610 injuries. The places of the highest occurrence were the street with 10,183 burglaries (34%) and then residential place with 7,527 burglaries (approximately 25%). One-man burglary was the highest complicity: 15,012 offenders (56.1%). The knife was used as the most frequent instrument for 6,498 burglaries (24,3%) what is rare, while no criminal tool or instrument was used for 15,631 burglaries (58.4). During the period from 2001 to 2006, 1,506 burglaries occurred in Daegu and the average annual number was 251 burglaries. Among those,515 residential invasion burglaries (34.2%) took place and the average annual number was approximately 86 cases. The hours just after midnight (between 00:00 and 04:00) were the most frequent time for invasion burglary to occur (194 cases, 37.7%), the place of the highest invasion occurrence was the residential place (259 cases, 50.3%), and the exit was used as the most frequent invasion route (87 cases, 37.7%). An unlocked exit door or window was the most frequent invasion method (65 cases, 25.1%). In addition, pretending to be a delivery man, visitor or following the victim methods were used for 26 burglaries (10%). It is apparent that personal preventive measures against crimes, as well as governmental and social measures, play an important role in preventing burglaries. In particular, based on the analyzed result that an unlocked window or exit door was most frequently used for reported burglaries, it seems that there is a lack of understanding of crime prevention while little effort has been made to prevent crimes. Although everyone knows that locking a door is one of the basic measures to prevent crimes, many people tend to pay little attention to lock a door properly so burglary takes place. This study, therefore, is intended to encourage people to pay more careful attention to crime prevention, in order to help reduce the probability of burglary. With the recent improvement in social understanding of scientific crime investigation, a wide variety of police professions, including crime analysts, crime victim police counselors and coroners, have been prepared to develop the scientific crime investigation and crime analysis. In addition, it is hoped that further this study will contribute to encourage studies on crime prevention to be carried out in the future.

• Journal of Intelligence and Information Systems
• /
• v.20 no.1
• /
• pp.149-161
• /
• 2014

The export of domestic public services to overseas markets contains many potential obstacles, stemming from different export procedures, the target services, and socio-economic environments. In order to alleviate these problems, the business incubation platform as an open business ecosystem can be a powerful instrument to support the decisions taken by participants and stakeholders. In this paper, we propose an ontology model and its implementation processes for the business incubation platform with an open and pervasive architecture to support public service exports. For the conceptual model of platform ontology, export case studies are used for requirements analysis. The conceptual model shows the basic structure, with vocabulary and its meaning, the relationship between ontologies, and key attributes. For the implementation and test of the ontology model, the logical structure is edited using Prot$\acute{e}$g$\acute{e}$ editor. The core engine of the business incubation platform is the simulator module, where the various contexts of export businesses should be captured, defined, and shared with other modules through ontologies. It is well-known that an ontology, with which concepts and their relationships are represented using a shared vocabulary, is an efficient and effective tool for organizing meta-information to develop structural frameworks in a particular domain. The proposed model consists of five ontologies derived from a requirements survey of major stakeholders and their operational scenarios: service, requirements, environment, enterprise, and county. The service ontology contains several components that can find and categorize public services through a case analysis of the public service export. Key attributes of the service ontology are composed of categories including objective, requirements, activity, and service. The objective category, which has sub-attributes including operational body (organization) and user, acts as a reference to search and classify public services. The requirements category relates to the functional needs at a particular phase of system (service) design or operation. Sub-attributes of requirements are user, application, platform, architecture, and social overhead. The activity category represents business processes during the operation and maintenance phase. The activity category also has sub-attributes including facility, software, and project unit. The service category, with sub-attributes such as target, time, and place, acts as a reference to sort and classify the public services. The requirements ontology is derived from the basic and common components of public services and target countries. The key attributes of the requirements ontology are business, technology, and constraints. Business requirements represent the needs of processes and activities for public service export; technology represents the technological requirements for the operation of public services; and constraints represent the business law, regulations, or cultural characteristics of the target country. The environment ontology is derived from case studies of target countries for public service operation. Key attributes of the environment ontology are user, requirements, and activity. A user includes stakeholders in public services, from citizens to operators and managers; the requirements attribute represents the managerial and physical needs during operation; the activity attribute represents business processes in detail. The enterprise ontology is introduced from a previous study, and its attributes are activity, organization, strategy, marketing, and time. The country ontology is derived from the demographic and geopolitical analysis of the target country, and its key attributes are economy, social infrastructure, law, regulation, customs, population, location, and development strategies. The priority list for target services for a certain country and/or the priority list for target countries for a certain public services are generated by a matching algorithm. These lists are used as input seeds to simulate the consortium partners, and government's policies and programs. In the simulation, the environmental differences between Korea and the target country can be customized through a gap analysis and work-flow optimization process. When the process gap between Korea and the target country is too large for a single corporation to cover, a consortium is considered an alternative choice, and various alternatives are derived from the capability index of enterprises. For financial packages, a mix of various foreign aid funds can be simulated during this stage. It is expected that the proposed ontology model and the business incubation platform can be used by various participants in the public service export market. It could be especially beneficial to small and medium businesses that have relatively fewer resources and experience with public service export. We also expect that the open and pervasive service architecture in a digital business ecosystem will help stakeholders find new opportunities through information sharing and collaboration on business processes.

• Journal of Intelligence and Information Systems
• /
• v.18 no.4
• /
• pp.19-42
• /
• 2012

Consumer consumption patterns are shifting rapidly as buyers migrate from offline markets to e-commerce routes, such as shopping channels on TV and internet shopping malls. In the offline markets consumers go shopping, see the shopping items, and choose from them. Recently consumers tend towards buying at shopping sites free from time and place. However, as e-commerce markets continue to expand, customers are complaining that it is becoming a bigger hassle to shop online. In the online shopping, shoppers have very limited information on the products. The delivered products can be different from what they have wanted. This case results to purchase cancellation. Because these things happen frequently, they are likely to refer to the consumer reviews and companies should be concerned about consumer's voice. E-commerce is a very important marketing tool for suppliers. It can recommend products to customers and connect them directly with suppliers with just a click of a button. The recommender system is being studied in various ways. Some of the more prominent ones include recommendation based on best-seller and demographics, contents filtering, and collaborative filtering. However, these systems all share two weaknesses : they cannot recommend products to consumers on a personal level, and they cannot recommend products to new consumers with no buying history. To fix these problems, we can use the information which has been collected from the questionnaires about their demographics and preference ratings. But, consumers feel these questionnaires are a burden and are unlikely to provide correct information. This study investigates combining collaborative filtering with the centrality of social network analysis. This centrality measure provides the information to infer the preference of new consumers from the shopping history of existing and previous ones. While the past researches had focused on the existing consumers with similar shopping patterns, this study tried to improve the accuracy of recommendation with all shopping information, which included not only similar shopping patterns but also dissimilar ones. Data used in this study, Movie Lens' data, was made by Group Lens research Project Team at University of Minnesota to recommend movies with a collaborative filtering technique. This data was built from the questionnaires of 943 respondents which gave the information on the preference ratings on 1,684 movies. Total data of 100,000 was organized by time, with initial data of 50,000 being existing customers and the latter 50,000 being new customers. The proposed recommender system consists of three systems : [+] group recommender system, [-] group recommender system, and integrated recommender system. [+] group recommender system looks at customers with similar buying patterns as 'neighbors', whereas [-] group recommender system looks at customers with opposite buying patterns as 'contraries'. Integrated recommender system uses both of the aforementioned recommender systems to recommend movies that both recommender systems pick. The study of three systems allows us to find the most suitable recommender system that will optimize accuracy and customer satisfaction. Our analysis showed that integrated recommender system is the best solution among the three systems studied, followed by [-] group recommended system and [+] group recommender system. This result conforms to the intuition that the accuracy of recommendation can be improved using all the relevant information. We provided contour maps and graphs to easily compare the accuracy of each recommender system. Although we saw improvement on accuracy with the integrated recommender system, we must remember that this research is based on static data with no live customers. In other words, consumers did not see the movies actually recommended from the system. Also, this recommendation system may not work well with products other than movies. Thus, it is important to note that recommendation systems need particular calibration for specific product/customer types.

• Journal of Hospice and Palliative Care
• /
• v.3 no.2
• /
• pp.126-135
• /
• 2000

Purpose : To evaluate the present status of bereavement care in Korean hospice service as a basic database for the effective bereavement care. Method : The data were collected two sets from September to October, 1999 and from November to December, 2000, 55 hospice institutions identified by the Hospice Education Institution, College of Nursing, Catholic University were contacted for a telephone survey. The researchers conducted telephone interviews with hospice administrators for 10 to 30 minutes. Result : 1) Among the 55 Korean Hospice institutions, 38 institutions(69.1%) provided bereavement services. 2) The contents of bereavement services consisted of telephone call 28 institutions(74.5%), bereaved family meeting 26 institutions(69.4%), home visiting 22 institutions(57.9%), mail 16 institutions(42.1%), personal counselling 7 institutions(18.4%). 3) The 26 hospice institutions(68.4%) which provided meetings for bereaved families met with the following frequency : Annually is 11 institutions(42.3%), biannually 6 institutions(23.1%), monthly 6 institutions(23.1%) and bimonthly 3 institutions(11.5%). 4) Only 4 hospice institutions(10.5%) used the assessment tool to screen for high risk of bereaved. 5) The major difficulties of current bereavement services were low attendance for the bereaved family meeting, shortage of professional managers and volunteers, limited accessibility to hospice institutions, little social awareness for the bereaved, and financial difficulties. 6) The hospice administrators expressed the need for the development of bereavement program, the education program for the bereavement services, trained professionals, the sufficient provision of human resource and financial support for more effective bereavement services. Conclusion : Although many hospice institutions(69.1%) provided bereavement services, they generally lacked capable bereavement professionals and various individualized bereavement services. In conclusion, it is required to develop the specified bereavement program and the training program for the staff and volunteers, so as to provide customized bereavement services based on individual needs. Further research will be necessary to evaluate the effects of customized bereavement services in Korea before applying to practice.

• Journal of Intelligence and Information Systems
• /
• v.22 no.1
• /
• pp.159-185
• /
• 2016

Planning a multi-day trip is a complex, yet time-consuming task. It usually starts with selecting a list of points of interest (POIs) worth visiting and then arranging them into an itinerary, taking into consideration various constraints and preferences. When choosing POIs to visit, one might ask friends to suggest them, search for information on the Web, or seek advice from travel agents; however, those options have their limitations. First, the knowledge of friends is limited to the places they have visited. Second, the tourism information on the internet may be vast, but at the same time, might cause one to invest a lot of time reading and filtering the information. Lastly, travel agents might be biased towards providers of certain travel products when suggesting itineraries. In recent years, many researchers have tried to deal with the huge amount of tourism information available on the internet. They explored the wisdom of the crowd through overwhelming images shared by people on social media sites. Furthermore, trip planning problems are usually formulated as 'Tourist Trip Design Problems', and are solved using various search algorithms with heuristics. Various recommendation systems with various techniques have been set up to cope with the overwhelming tourism information available on the internet. Prediction models of recommendation systems are typically built using a large dataset. However, sometimes such a dataset is not always available. For other models, especially those that require input from people, human computation has emerged as a powerful and inexpensive approach. This study proposes CYTRIP (Crowdsource Your TRIP), a multi-day trip itinerary planning system that draws on the collective intelligence of contributors in recommending POIs. In order to enable the crowd to collaboratively recommend POIs to users, CYTRIP provides a shared workspace. In the shared workspace, the crowd can recommend as many POIs to as many requesters as they can, and they can also vote on the POIs recommended by other people when they find them interesting. In CYTRIP, anyone can make a contribution by recommending POIs to requesters based on requesters' specified preferences. CYTRIP takes input on the recommended POIs to build a multi-day trip itinerary taking into account the user's preferences, the various time constraints, and the locations. The input then becomes a multi-day trip planning problem that is formulated in Planning Domain Definition Language 3 (PDDL3). A sequence of actions formulated in a domain file is used to achieve the goals in the planning problem, which are the recommended POIs to be visited. The multi-day trip planning problem is a highly constrained problem. Sometimes, it is not feasible to visit all the recommended POIs with the limited resources available, such as the time the user can spend. In order to cope with an unachievable goal that can result in no solution for the other goals, CYTRIP selects a set of feasible POIs prior to the planning process. The planning problem is created for the selected POIs and fed into the planner. The solution returned by the planner is then parsed into a multi-day trip itinerary and displayed to the user on a map. The proposed system is implemented as a web-based application built using PHP on a CodeIgniter Web Framework. In order to evaluate the proposed system, an online experiment was conducted. From the online experiment, results show that with the help of the contributors, CYTRIP can plan and generate a multi-day trip itinerary that is tailored to the users' preferences and bound by their constraints, such as location or time constraints. The contributors also find that CYTRIP is a useful tool for collecting POIs from the crowd and planning a multi-day trip.

• Progress in Medical Physics
• /
• v.25 no.3
• /
• pp.151-156
• /
• 2014

The purpose of this study was to confirm the feasibility of imaging of therapy region from the boron neutron capture therapy (BNCT) using the measurement of the prompt gamma ray depending on the neutron flux. Through the Monte Carlo simulation, we performed the verification of physical phenomena from the BNCT; (1) the effects of neutron according to the existence of boron uptake region (BUR), (2) the internal and external measurement of prompt gamma ray dose, (3) the energy spectrum by the prompt gamma ray. All simulation results were deducted using the Monte Carlo n-particle extended (MCNPX, Ver.2.6.0, Los Alamos National Laboratory, Los Alamos, NM, USA) simulation tool. The virtual water phantom, thermal neutron source, and BURs were simulated using the MCNPX. The energy of the thermal neutron source was defined as below 1 eV with 2,000,000 n/sec flux. The prompt gamma ray was measured with the direction of beam path in the water phantom. The detector material was defined as the lutetium-yttrium oxyorthosilicate (Lu0,6Y1,4Si0,5:Ce; LYSO) scintillator with lead shielding for the collimation. The BUR's height was 5 cm with the 28 frames (bin: 0.18 cm) for the dose calculation. The neutron flux was decreased dramatically at the shallow region of BUR. In addition, the dose of prompt gamma ray was confirmed at the 9 cm depth from water surface, which is the start point of the BUR. In the energy spectrum, the prompt gamma ray peak of the 478 keV was appeared clearly with full width at half maximum (FWHM) of the 41 keV (energy resolution: 8.5%). In conclusion, the therapy region can be monitored by the gamma camera and single photon emission computed tomography (SPECT) using the measurement of the prompt gamma ray during the BNCT.

• Journal of Korean Academy of Nursing Administration
• /
• v.8 no.1
• /
• pp.169-191
• /
• 2002

As the tendency of the society is centralized into consumers and services, patients are getting to ask better medical services. The consumers influenced from various social surroundings became to have some expectation of nursing service. Compared with their expectation, the quality of the services which they virtually get may be recognized and evaluated. So it is necessary to know exactly what the consumers want in nursing services. The purpose of this study is to examine the determinants which can evaluate the quality of nursing services by researching into consumers' expectation and perception of the nursing services depending on the consumer-oriented attributions on the basis of the model of SERVQUAL. 1,144 of outpatients were selected as the subjects for this research. They used to continuously visit the same hospital after being hospitalized and nursed in 9 hospitals randomly selected among the second-level medical organizations in Seoul from January to February, 2001. The collected data are analyzed into the Descriptive Statistics, t-test, GLM and Multiple Regression through the SAS program. Delphi was used for the research tool and the results of the research are as follows; the determinants in evaluating the quality of nursing services consist of 5 categories such as Tangibility, Reliability, Responsiveness, Assurance, Empathy. The values of Cronbach' $\alpha$ appeared to be 0.96 in the expectation of nursing services, 0.94 in the perception of nursing services and 0.96 in the importance of nursing services. The determinants in the expectation of nursing services were ranged in the order of Assurance, Empathy, Reliability, Responsiveness and Tangibility. And those in the perception of nursing services were in the order of Assurance, Empathy, Reliability, Tangibility and Responsiveness. Those in the importance of nursing service were in the order of Empathy, Assurance, Reliability, Tangibility and Responsiveness. Finally, those in the quality of nursing service were in the order of Tangibility, Responsiveness, Empathy, Reliability and Assurance. Each expectation of nursing services appeared different depending on the subjects' age, gender, clinical department and reason for hospitalization. The hypothesis examined in this research shows that the group having higher personal needs shows meaningful differences in the expectation of nursing services, and the subjects who have had external communication show higher perception of nursing service than uncommunicative ones. After all, we can see that the statistical differences in the perception of nursing services depend on whether the subjects have external communications or not. The determinants in the expectation of nursing services can explain the quality of nursing service up to 14.96%. The statistically meaningful determinants in the expectation could be arranged in the order of Reliability, Assurance and Tangibility. And the more expectation brings about the lower evaluation of the quality of nursing services. The determinants in the perception of nursing service can explain the quality of nursing services up to 29.85%. The statistically meaningful determinants in the perception could be arranged in the order of Responsiveness, Reliability, Tangibility, Empathy, and Assurance. And the more perception brings about the higher evaluation of the quality of nursing services. According to the result of the above research, I would like to propose as follows. As long as this research is oriented to get knowledge of the consumer-oriented nursing services, it should be continued to draw the other elements determining the quality of the nursing services. Furthermore, this research is based upon the Parasuraman, A., et al.'s SERVQUAL Model(1991), which deals only expectation, perception and quality of consumer-oriented nursing services, so it will be necessary to inspect and verify it through the other models containing the offerers of nursing services in the future. On the other hand, as this research evaluates the actual quality of nursing services based on the expectation and perception of nursing services, it can be utilized as fundamental data to develop the marketing strategies and to estimate the qualities as well. I hope this research will be periodically estimated to be the useful data to develop the marketing strategies in the nursing service area.

• Analytical Science and Technology
• /
• v.33 no.3
• /
• pp.151-158
• /
• 2020

Alcohol, which can easily be obtained in the same way as ordinary beverages, is harmful enough to cause death due to excessive drinking and chronic alcohol intake, so it is important to maintain a proper amount of drinking and healthy drinking habits. In addition, the incidence of behavioral disturbances and impaired judgments that can be caused by chronic alcohol drinking of more than adequate amounts of alcohol is also significant. Accordingly it is very useful for forensic science to check whether the person involved is drunken or is alcoholism state in various accidents. Currently, in Korea, alcohol consumption is determined by detecting the level of alcohol or alcohol metabolism 'ethyl glucuronide (EtG)' in blood or urine samples. However, analysis of alcohol or EtG in blood or urine can only provide information about the current state of alcohol consumption because of a narrow window of detection time. Therefore, it is important to analyze the EtG as a long-term direct alcohol metabolite bio-marker in human hair and to investigate relationship between alcohol consumption and EtG concentration for the evaluation of chronic ethanol consumption. In this study, we established an analytical method for the detection of EtG in Korean hair efficiently and validated selectivity, linearity, limits of detection (LOD), limits of quantification (LOQ), matrix effect, recovery, process efficiency, accuracy and precision using liquid chromatography tandem mass spectrometry (LC-MS/MS). In addition, the assay performance was evaluated in Korean social drinker's hair and the postmortem hair of a chronic alcoholism. The results of this study can be useful in monitoring the alcohol abuse of Korean in clinical cases and legal procedures related to custody and provide a useful tool to evaluate postmortem diagnosis of alcoholic ketoacidosis in forensics.

• Journal of Preventive Medicine and Public Health
• /
• v.11 no.1
• /
• pp.123-127
• /
• 1978

The major objective of this research is to identify those hospital characteristics that best explain cost variation among hospitals and to formulate linear models that can predict hospital costs. Specific emphasis is placed on hospital output, that is, the identification of diagnosis related patient groups (DRGs) which are medically meaningful and demonstrate similar patterns of hospital resource consumption. A casemix index is developed based on the DRGs identified. Considering the common problems encountered in previous hospital cost research, the following study requirements are estab-lished for fulfilling the objectives of this research: 1. Selection of hospitals that exercise similar medical and fiscal practices. 2. Identification of an appropriate data collection mechanism in which demographic and medical characteristics of individual patients as well as accurate and comparable cost information can be derived. 3. Development of a patient classification system in which all the patients treated in hospitals are able to be split into mutually exclusive categories with consistent and stable patterns of resource consumption. 4. Development of a cost finding mechanism through which patient groups' costs can be made comparable across hospitals. A data set of Medicare patients prepared by the Social Security Administration was selected for the study analysis. The data set contained 27,229 record abstracts of Medicare patients discharged from all but one short-term general hospital in Connecticut during the period from January 1, 1971, to December 31, 1972. Each record abstract contained demographic and diagnostic information, as well as charges for specific medical services received. The 'AUT-OGRP System' was used to generate 198 DRGs in which the entire range of Medicare patients were split into mutually exclusive categories, each of which shows a consistent and stable pattern of resource consumption. The 'Departmental Method' was used to generate cost information for the groups of Medicare patients that would be comparable across hospitals. To fulfill the study objectives, an extensive analysis was conducted in the following areas: 1. Analysis of DRGs: in which the level of resource use of each DRG was determined, the length of stay or death rate of each DRG in relation to resource use was characterized, and underlying patterns of the relationships among DRG costs were explained. 2. Exploration of resource use profiles of hospitals; in which the magnitude of differences in the resource uses or death rates incurred in the treatment of Medicare patients among the study hospitals was explored. 3. Casemix analysis; in which four types of casemix-related indices were generated, and the significance of these indices in the explanation of hospital costs was examined. 4. Formulation of linear models to predict hospital costs of Medicare patients; in which nine independent variables (i. e., casemix index, hospital size, complexity of service, teaching activity, location, casemix-adjusted death. rate index, occupancy rate, and casemix-adjusted length of stay index) were used for determining factors in hospital costs. Results from the study analysis indicated that: 1. The system of 198 DRGs for Medicare patient classification was demonstrated not only as a strong tool for determining the pattern of hospital resource utilization of Medicare patients, but also for categorizing patients by their severity of illness. 2. The wei틴fed mean total case cost (TOTC) of the study hospitals for Medicare patients during the study years was $11,27.02 with a standard deviation of $117.20. The hospital with the highest average TOTC ($1538.15) was 2.08 times more expensive than the hospital with the lowest average TOTC ($743.45). The weighted mean per diem total cost (DTOC) of the study hospitals for Medicare patients during the sutdy years was $107.98 with a standard deviation of $15.18. The hospital with the highest average DTOC ($147.23) was 1.87 times more expensive than the hospital with the lowest average DTOC ($78.49). 3. The linear models for each of the six types of hospital costs were formulated using the casemix index and the eight other hospital variables as the determinants. These models explained variance to the extent of 68.7 percent of total case cost (TOTC), 63.5 percent of room and board cost (RMC), 66.2 percent of total ancillary service cost (TANC), 66.3 percent of per diem total cost (DTOC), 56.9 percent of per diem room and board cost (DRMC), and 65.5 percent of per diem ancillary service cost (DTANC). The casemix index alone explained approximately one half of interhospital cost variation: 59.1 percent for TOTC and 44.3 percent for DTOC. Thsee results demonstrate that the casemix index is the most importand determinant of interhospital cost variation Future research and policy implications in regard to the results of this study is envisioned in the following three areas: 1. Utilization of casemix related indices in the Medicare data systems. 2. Refinement of data for hospital cost evaluation. 3. Development of a system for reimbursement and cost control in hospitals.