Hemodialysis is essential treatment for the chronic renal failure patient's long-term cure and for the patient management before and after kidney transplantation. It sustains the endstage renal failure patient's life which didn't get well despite strict regimen and furthermore it becomes an essential treatment to maintain civil life. Bursing implementation in hemodialysis may affect the significant effect on patient's life. The purpose of this study was to obtain the basic data to solve the hypotension problem encountable to patient and the blood loss problem affecting hemodialysis patient'a anemic states by incomplete rinsing of blood in coil through all process of hemodialysis. The subjects for this study were 44 patients treated hemodialysis 691 times in the hemodialysis unit, The .data was collected at Gang Nam 51. Mary's Hospital from January 1, 1981 to April 30, 1981 by using the direct observation method and the clinical laboratory test for laboratory data and body weight and was analysed by the use of analysis of Chi-square, t-test and anlysis of varience. The results obtained an follows; A. On clinical laboratory data and other data by dialysis Procedure. The average initial body weight was 2.37 ± 0.97kg, and average body weight after every dialysis was 2.33 ± 0.9kg. The subject's average hemoglobin was 7.05±1.93gm/dl and average hematocrit was 20.84± 3.82%. Average initial blood pressure was 174.03±23,75mmHg and after dialysis was 158.45±25.08mmHg. The subject's average blood ion due to blood sample for laboratory data was 32.78±13.49cc/ month. The subject's average blood replacement for blood complementation was 1.31 ±0.88 pint/ month for every patient. B. On the hypotensive state and the coping approaches occurrence rate of hypotension was 28.08%. It was 194 cases among 691 times. 1. In degrees of initial blood pressure, the most 36.6% was in the group of 150-179mmHg, and in degrees of hypotension during dialysis, the most 28.9% in the group of 40-50mmHg, especially if the initial blood pressure was under 180mmHg, 59.8% clinical symptoms appeared in the group of“above 20mmHg of hypotension”. If initial blood pressure was above 180mmHg, 34.2% of clinical symptoms were appeared in the group of“above 40mmHg of hypotension”. These tendencies showed the higher initial blood pressure and the stronger degree of hypotension, these results showed statistically singificant differences. (P=0.0000) 2. Of the occuring times of hypotension,“after 3 hrs”were 29.4%, the longer the dialyzing procedure, the stronger degree of hypotension ann these showed statistically significant differences. (P=0.0142). 3. Of the dispersion of symptoms observed, sweat and flush were 43.3%, and Yawning, and dizziness 37.6%. These were the important symptoms implying hypotension during hemodialysis accordingly. Strages of procedures in coping with hypotension were as follows ; 45.9% were recovered by reducing the blood flow rate from 200cc/min to 1 00cc/min, and by reducing venous pressure to 0-30mmHg. 33.51% were recovered by controling (adjusting) blood flow rate and by infusion of 300cc of 0,9% Normal saline. 4.1% were recovered by infusion of over 300cc of 0.9% normal saline. 3.6% by substituting Nor-epinephiine, 5.7% by substituting blood transfusion, and 7,2% by substituting Albumin were recovered. And the stronger the degree of symptoms observed in hypotention, the more the treatments required for recovery and these showed statistically significant differences (P=0.0000). C. On the effects of the changes of blood pressure and osmolality by albumin and hemofiltration. 1. Changes of blood pressure in the group which didn't required treatment in hypotension and the group required treatment, were averaged 21.5mmHg and 44.82mmHg. So the difference in the latter was bigger than the former and these showed statistically significant difference (P=0.002). On the changes of osmolality, average mean were 12.65mOsm, and 17.57mOsm. So the difference was bigger in the latter than in the former but these not showed statistically significance (P=0.323). 2. Changes of blood pressure in the group infused albumin and in the group didn't required treatment in hypotension, were averaged 30mmHg and 21.5mmHg. So there was no significant differences and it showed no statistical significance (P=0.503). Changes of osmolality were averaged 5.63mOsm and 12.65mOsm. So the difference was smaller in the former but these was no stitistical significance (P=0.287). Changes of blood pressure in the group infused Albumin and in the group required treatment in hypotension were averaged 30mmHg and 44.82mmHg. So the difference was smaller in the former but there is no significant difference (P=0.061). Changes of osmolality were averaged 8.63mOsm, and 17.59mOsm. So the difference were smaller in the former but these not showed statistically significance (P=0.093). 3. Changes of blood pressure in the group iutplemented hemofiltration and in the Uoup didn't required treatment in hypotension were averaged 22mmHg and 21.5mmHg. So there was no significant differences and also these showed no statistical significance (P=0.320). Changes of osmolality were averaged 0.4mOsm and 12.65mOsm. So the difference was smaller in the former but these not showed statistical significance(P=0.199). Changes of blood pressure in the group implemented hemofiltration and in the group required treatment in hypotension were averaged 22mmHg and 44.82mmHg. So the difference was smatter in the former and these showed statistically significant differences (P=0.035). Changes of osmolality were averaged 0.4mOsm and 17.59mOsm. So the difference was smaller in the former but these not showed statistical significance (P=0.086). D. On the changes of body weight, and blood pressure, between the group of hemofiltration and hemodialysis. 1, Changes of body weight in the group implemented hemofiltration and hemodialysis were averaged 3.340 and 3.320. So there was no significant differences and these showed no statistically significant difference, (P=0.185) but standard deviation of body weight averaged in comparison with standard difference of body weight was statistically significant difference (P=0.0000). Change of blood Pressure in the group implemented hemofiltration and hemodialysis were averaged 17.81mmHg and 19.47mmHg. So there was no significant differences and these showed no statistically significant difference (P=0.119), But in comparison with standard deviation about difference of blood pressure was statistically significant difference. (P=0.0000). E. On the blood infusion method in coil after hemodialysis and residual blood losing method in coil. 1, On comparing and analysing Hct of residual blood in coil by factors influencing blood infusion method. Infusion method of saline 200cc reduced residual blood in coil after the quantitative comparison of Saline Occ, 50cc, 100cc, 200cc and the differences showed statistical significance (p < 0.001). Shaking Coil method reduced residual blood in Coil in comparison of Shaking Coil method and Non-Shaking Coil method this showed statistically significant difference (P < 0.05). Adjusting pressure in Coil at OmmHg method reduced residual blood in Coil in comparison of adjusting pressure in Coil at OmmHg and 200mmHg, and this showed statistically significant difference (P < 0.001). 2. Comparing blood infusion method divided into 10 methods in Coil with every factor respectively, there was seldom difference in group of choosing Saline 100cc infusion between Coil at OmmHg. The measured quantity of blood loss was averaged 13.49cc. Shaking Coil method in case of choosing saline 50cc infusion while adjusting pressure in coil at OmmHg was the most effective to reduce residual blood. The measured quantity of blood loss was averaged 15.18cc.
Internet commerce has been growing at a rapid pace for the last decade. Many firms try to reach wider consumer markets by adding the Internet channel to the existing traditional channels. Despite the various benefits of the Internet channel, a significant number of firms failed in managing the new type of channel. Previous studies could not cleary explain these conflicting results associated with the Internet channel. One of the major reasons is most of the previous studies conducted analyses under a specific market condition and claimed that as the impact of Internet channel introduction. Therefore, their results are strongly influenced by the specific market settings. However, firms face various market conditions in the real worlddensity and disutility of using the Internet. The purpose of this study is to investigate the impact of various market environments on a firm's optimal channel strategy by employing a flexible game theory model. We capture various market conditions with consumer density and disutility of using the Internet.
shows the channel structures analyzed in this study. Before the Internet channel is introduced, a monopoly manufacturer sells its products through an independent physical store. From this structure, the manufacturer could introduce its own Internet channel (MI). The independent physical store could also introduce its own Internet channel and coordinate it with the existing physical store (RI). An independent Internet retailer such as Amazon could enter this market (II). In this case, two types of independent retailers compete with each other. In this model, consumers are uniformly distributed on the two dimensional space. Consumer heterogeneity is captured by a consumer's geographical location (ci) and his disutility of using the Internet channel (${\delta}_{N_i}$).
shows various market conditions captured by the two consumer heterogeneities.
(a) illustrates a market with symmetric consumer distributions. The model captures explicitly the asymmetric distributions of consumer disutility in a market as well. In a market like that is represented in
(c), the average consumer disutility of using an Internet store is relatively smaller than that of using a physical store. For example, this case represents the market in which 1) the product is suitable for Internet transactions (e.g., books) or 2) the level of E-Commerce readiness is high such as in Denmark or Finland. On the other hand, the average consumer disutility when using an Internet store is relatively greater than that of using a physical store in a market like (b). Countries like Ukraine and Bulgaria, or the market for "experience goods" such as shoes, could be examples of this market condition.
summarizes the various scenarios of consumer distributions analyzed in this study. The range for disutility of using the Internet (${\delta}_{N_i}$) is held constant, while the range of consumer distribution (${\chi}_i$) varies from -25 to 25, from -50 to 50, from -100 to 100, from -150 to 150, and from -200 to 200.
summarizes the analysis results. As the average travel cost in a market decreases while the average disutility of Internet use remains the same, average retail price, total quantity sold, physical store profit, monopoly manufacturer profit, and thus, total channel profit increase. On the other hand, the quantity sold through the Internet and the profit of the Internet store decrease with a decreasing average travel cost relative to the average disutility of Internet use. We find that a channel that has an advantage over the other kind of channel serves a larger portion of the market. In a market with a high average travel cost, in which the Internet store has a relative advantage over the physical store, for example, the Internet store becomes a mass-retailer serving a larger portion of the market. This result implies that the Internet becomes a more significant distribution channel in those markets characterized by greater geographical dispersion of buyers, or as consumers become more proficient in Internet usage. The results indicate that the degree of price discrimination also varies depending on the distribution of consumer disutility in a market. The manufacturer in a market in which the average travel cost is higher than the average disutility of using the Internet has a stronger incentive for price discrimination than the manufacturer in a market where the average travel cost is relatively lower. We also find that the manufacturer has a stronger incentive to maintain a high price level when the average travel cost in a market is relatively low. Additionally, the retail competition effect due to Internet channel introduction strengthens as average travel cost in a market decreases. This result indicates that a manufacturer's channel power relative to that of the independent physical retailer becomes stronger with a decreasing average travel cost. This implication is counter-intuitive, because it is widely believed that the negative impact of Internet channel introduction on a competing physical retailer is more significant in a market like Russia, where consumers are more geographically dispersed, than in a market like Hong Kong, that has a condensed geographic distribution of consumers.