• Journal of Preventive Medicine and Public Health
• /
• v.24 no.4 s.36
• /
• pp.485-495
• /
• 1991

This study examined the effects of referral requirements for insurance patients which have been enforced since July 1, 1989 when medical insurance coverage was extended to the whole population except beneficiaries of medical assistance program. The requirements are mainly aimed at discouraging the use of tertiary care hospitals by imposing restrictions on the patient's choice of a medical service facility. The expectation is that such change in the pattern of medical care utilization would produce several desirable effects including increased efficiency in patient care and balanced development of various types of medical service facilities. In this study, these effects were assessed by the change in the number of out-patient visits and bed-days per illness episode and the share of each type of facility in the volume of services and the amount of expenditures after the implementation of the new referral system. The data for analysis were obtained from the claims to the insurance for government and school employees. The sample was drawn from the claims for the patients treated during the first six months of 1989, prior to the enforcement of referral requirements, and those of the patients treated during the first six months of 1990, after the enforcement. The 1989 sample included 299,824 claims (3.6% of total) and the 1990 sample included 332,131 (3.7% of total). The data were processed to make the unit of analysis an illness episode instead of an insurance claim. The facilities and types of care utilized for a given illness episode are defined to make up the pathway of medical care utilization. This pathway was conceived of as a Markov Chain process for further analysis. The conclusion emerged from the analysis is that the enforcement of referral requirements resulted in less use of tertiary care hospitals, and thereby decreased the volume of services and the amount of insurance expenses per illness episode. However, there are a few points that have to be taken into account in relation to the conclusion. The new referral system is likely to increase the use of medical services not covered by insurance, so that its impact on national health expenditures would be different from that on insurance expenditures. The extension of insurance coverage must have inereased patient load for all types of medical service organizations, and this increase may be partly responsible for producing the effects attributed to the new referral system. For example, excessive patient load for tertiary care hospitals may lead to the transfer of their patients to other types of facilities. Another point is that the data for this study correspond to very early phase of the new system. But both patients and medical care providers would adapt themselves to the new system to avoid or overcome its disadvantages for them, so as that its effects could change over time. Therefore, it is still necessary to closely monitor the impact of the referral requirements.

• Journal of the Korean Geographical Society
• /
• v.47 no.1
• /
• pp.98-120
• /
• 2012

The main objective of this study is to conduct subnational population projections of Korea based on a multiregional cohort-component method. This objective is accomplished by: (i) establishing a viable framework to implement the multiregional cohort-component method with reference to the Markov chain model and Rogers' multiregional population projection model; (ii) applying the established framework to subnational population projections of Korea, 2005~2030. The main results are twofold. First, the proposed method turns out to be highly valid in a methodological sense, which is seen from a high level of coincidence between the estimated and the observed. Second, the projection results turn out to be highly useful in the sense that interregional migration flow matrices are resulted for projection periods. The projected migration flows are expected to provide invaluable information for an understanding of future population change and for a formulation of policy alternatives. This study is strongly inspired by the multiregional perspective emphasizing the evolution of multiple regional populations interconnected by interregional migration flows rather than the overall national change.

• Asia Marketing Journal
• /
• v.11 no.1
• /
• pp.73-92
• /
• 2009

Consumers influence other consumers' brand choice behavior by delivering a variety of objective or subjective information on a particular product, which is called WOM (Word-Of-Mouth) activities. For WOM activities, WOM senders should choose messages to deliver to other consumers. We classify the contents of the messages a consumer chooses for WOM delivery into two categories: Subjective (positive or negative) evaluation and objective information on products. In our study, we regard WOM senders' activities as a choice behavior and introduce a choice model to study the relationship between the choice of different WOM information (WOM with positive or negative subjective evaluation and WOM with objective information) and its influencing factors (information sources and consumer characteristics) by developing two bivariate Probit models. In order to consider the mediating effects of WOM senders' product involvement, product attitude, and their characteristics (gender and age), we develop three second-level models for the propagation of positive evaluations, of negative evaluations, and of objective information on products in an hierarchical Bayesian modeling framework. Our empirical results show that WOM senders' information choice behavior differs according to the types of information sources. The effects of information sources on WOM activities differ according to the types of WOM messages (subjective evaluation (positive or negative) and objective information). Therefore, our study concludes that WOM activities can be partially managed with effective communication plans influencing on consumers' WOM message choice behavior. The empirical results provide some guidelines for consumers' propagation of information on products companies want.

• Journal of Intelligence and Information Systems
• /
• v.25 no.2
• /
• pp.167-194
• /
• 2019

This research starts from the four basic concepts of incentive incompatibility, limited information, myopia and decision variable which are confronted when making decisions in keyword bidding. In order to make these concept concrete, four framework approaches are designed as follows; Strategic approach for the incentive incompatibility, Statistical approach for the limited information, Alternative optimization for myopia, and New model approach for decision variable. The purpose of this research is to propose the statistical optimization model in constructing the portfolio of Sponsored Search Advertising (SSA) in the Sponsor's perspective through empirical tests which can be used in portfolio decision making. Previous research up to date formulates the CTR estimation model using CPC, Rank, Impression, CVR, etc., individually or collectively as the independent variables. However, many of the variables are not controllable in keyword bidding. Only CPC and Rank can be used as decision variables in the bidding system. Classical SSA model is designed on the basic assumption that the CPC is the decision variable and CTR is the response variable. However, this classical model has so many huddles in the estimation of CTR. The main problem is the uncertainty between CPC and Rank. In keyword bid, CPC is continuously fluctuating even at the same Rank. This uncertainty usually raises questions about the credibility of CTR, along with the practical management problems. Sponsors make decisions in keyword bids under the limited information, and the strategic portfolio approach based on statistical models is necessary. In order to solve the problem in Classical SSA model, the New SSA model frame is designed on the basic assumption that Rank is the decision variable. Rank is proposed as the best decision variable in predicting the CTR in many papers. Further, most of the search engine platforms provide the options and algorithms to make it possible to bid with Rank. Sponsors can participate in the keyword bidding with Rank. Therefore, this paper tries to test the validity of this new SSA model and the applicability to construct the optimal portfolio in keyword bidding. Research process is as follows; In order to perform the optimization analysis in constructing the keyword portfolio under the New SSA model, this study proposes the criteria for categorizing the keywords, selects the representing keywords for each category, shows the non-linearity relationship, screens the scenarios for CTR and CPC estimation, selects the best fit model through Goodness-of-Fit (GOF) test, formulates the optimization models, confirms the Spillover effects, and suggests the modified optimization model reflecting Spillover and some strategic recommendations. Tests of Optimization models using these CTR/CPC estimation models are empirically performed with the objective functions of (1) maximizing CTR (CTR optimization model) and of (2) maximizing expected profit reflecting CVR (namely, CVR optimization model). Both of the CTR and CVR optimization test result show that the suggested SSA model confirms the significant improvements and this model is valid in constructing the keyword portfolio using the CTR/CPC estimation models suggested in this study. However, one critical problem is found in the CVR optimization model. Important keywords are excluded from the keyword portfolio due to the myopia of the immediate low profit at present. In order to solve this problem, Markov Chain analysis is carried out and the concept of Core Transit Keyword (CTK) and Expected Opportunity Profit (EOP) are introduced. The Revised CVR Optimization model is proposed and is tested and shows validity in constructing the portfolio. Strategic guidelines and insights are as follows; Brand keywords are usually dominant in almost every aspects of CTR, CVR, the expected profit, etc. Now, it is found that the Generic keywords are the CTK and have the spillover potentials which might increase consumers awareness and lead them to Brand keyword. That's why the Generic keyword should be focused in the keyword bidding. The contribution of the thesis is to propose the novel SSA model based on Rank as decision variable, to propose to manage the keyword portfolio by categories according to the characteristics of keywords, to propose the statistical modelling and managing based on the Rank in constructing the keyword portfolio, and to perform empirical tests and propose a new strategic guidelines to focus on the CTK and to propose the modified CVR optimization objective function reflecting the spillover effect in stead of the previous expected profit models.