ABSTRACT
OBJECTIVE：To provid e a more accurate calculation method for the determination of drug negotiation base price ， pharmacoeconomic calculation and budget impact analysis and calculation in the process of medical insurance access with buy-and-gift strategy. METHODS ：By the model method and literature research ，understanding the existing price conversion methods of the anti-cancer drugs that currently implement the buy-and-gift strategy ，a new method of drug price conversion was explored on the basis of the survival data of patients in different disease states ，and the core idea and calculation process of the algorithm were analyzed by an example. RESULTS ：The new algorithm was combined with the survival data of patients under different disease states. Its calculation process mainly included obtaining the actual duration of medication use per unit cycle and the theoretical amount of medication ，determining the aid model for anti-cancer drugs under buy-and-gift strategy ，converting the actual price. The simulation calculation was carried out under the one-step drug donation mode ，periodic drug donation mode and preferential installment drug donation mode. CONCLUSIONS ：The conversion method of anti-cancer drug price under buy-and-gift strategy based on survival data makes up for the shortcoming that the existing calculation methods are difficult to reflect the actual price of anti-cancer drugs ，and provides a new calculation method for calculating the actual reference price of anti-cancer drugs for medical insurance access.
ABSTRACT
This study investigates the effects of different configurations of online recommendation agents on consumers buying decisions. 104 on line consumers of clothing participated in our study (66.3% female) answering to an online questionnaire displaying different configurations of recommendation agents. Against the assumption that a large number of choices would lead to information overload and demotivate consumers (Iyengar and Lepper, 2000; Scheibehenne et al., 2008), this article shows that participants are more motivated to search for a product and more willing to buy from a website with a recommendation agent displaying a larger number of products (16), compared with a smaller number (4),and are more motivated to search for a product and more willing to buy from a website displaying 16 products at once instead of four at a time. Based on the fuzzy-trace theory (Reyna, 2008), we argue that information overload do not play a role here because people tend to reason on the basis of simplified representations (gist) rather than on the literal information available (verbatim). Also, compared to the absence of brands, the presence of brands increases the motivation to search for a product and the willingness to buy. These results can be explained by the fact that brands, like stereotypes (Janiszewski and Osselaer, 2000; Keller, 2003), help people to form the gist of the information being displayed (Brainerd and Reyna, 2005)...
Este estudo investiga os efeitos de diferentes configurações de agentes de recomendação online na tomada de decisão do consumidor. 104 consumidores online de roupas participaram desse estudo (66,3% do sexo feminino) respondendo a um questionário online que apresentava diferentes configurações de agentes de recomendação. Contrariamente à noção de que um grande número de escolhas levaria a uma sobrecarga de informações e desmotivaria os consumidores (Iyengar e Lepper, 2000; Scheibehenne et al., 2008), esse artigo mostra que participantes são mais motivados à pesquisar por produtos e mais dispostos a comprar de um web site com um agente recomendador que apresenta 16 produtos comparado com 4 produtos e são mais motivados à pesquisar por produtos e mais dispostos a comprar de um web site que apresenta 16 produtos de uma vez ao invés de quatro de cada vez. Tendo como base a teoria do traço difuso (Reyna, 2008), nós argumentamos que a sobrecarga de informações não afeta as escolhas porque as pessoas tendem a raciocinar com base em representações de essência ao invés de com base em informações literais. Ainda, a presença de marcas aumenta a motivação em pesquisar por produtos e a disposição em comprar produtos recomendados. Esses resultados podem ser explicados pelo fato de que marcas, assim como estereótipos (Janiszewski e Osselaer, 2000; Keller, 2003), ajudam as pessoas a extrair a essência da informação sendo exposta (Brainerd e Reyna, 2005)...
Este estudio investiga los efectos de diferentes configuraciones de los agentes de recomendación en línea en las decisiones de compra de los consumidores. 104 consumidores la línea de ropa participaron en nuestro estudio (66,3% mujeres) respondiendo a un cuestionario en línea mostrando diferentes configuraciones de los agentes de recomendación. En contra a la suposición que un gran número de opciones podría conducir a una sobrecarga de información y desmotivar a los consumidores (Iyengar y Lepper, 2000; Scheibehenne et al., 2008), este articulo muestra que los participantes que son más motivados a la búsqueda de un producto en un sitio web y mas dispuestos a comprar un gran número de productos (16), en comparación con un pequeño número (4), son más motivados a buscar un producto y más dispuesto a comprar en un sitio web con un agente de recomendación que presenta 16 productos a la vez en lugar de 4. Basándose en la fuzzy-trace theory (Reyna, 2008), nosotros argumentamos que la sobrecarga de información aquí no juega un papel importante porque las personas tienden a razonar sobre bases de representaciones simplificadas (esencia) en lugar de información literal disponible (literal). Además, comparando la ausencia de marcas, la presencia de marcas incrementa la motivación para buscar un producto y el deseo de compra. Estos resultados pueden ser explicados por el hecho que las marcas, como estereotipos (Janiszewski y Osselaer, 2000; Keller, 2003), ayudan a las personas a la formación de información de esencia (Brainerd y Reyna, 2005)...
Subject(s)
Humans , Male , Female , Behavior , Consumer BehaviorABSTRACT
El propósito de la investigación es determinar las relaciones existentes entre los niveles de Target Rating Point (TRP'S) entendidos como el índice acumulado de rating de Televisión mensual frente a los niveles de notoriedad (conocimiento de marca y publicitario), preferencia (favoritismo) y comportamiento (compra y próxima compra), a fin de identificar las principales tendencias derivadas de dichas asociaciones en una categoría de consumo masivo. Para esto, se tomaron los niveles de TRP'S en Televisión, como variable predictora central, así como las medidas de notoriedad de marca (top of mind, espontánea y ayudada), las medidas de notoriedad publicitaria (top of mind, espontánea y ayudada), las medidas de preferencia (marca favorita) y las variables de compra (marca comprada en el último mes y próxima marca a comprar) clasificadas en el conjunto de las variables criterio. El diseño de este estudio es de corte longitudinal de tendencia con K muestras, la muestra general del estudio comprende un conjunto de 4.104 registros agregados derivados de la replicación de 58 muestras mensuales de 500 participantes de ambos géneros con edades entre los 12 y 60 años pertenecientes a los estratos 2 al 6 dentro del período comprendido entre enero de 2004 y octubre de 2008. Los principales hallazgos resaltan el establecimiento de asociaciones estadísticamente significativas entre los niveles de TRP'S (bajo-medio y alto) y el comportamiento diferencial de cada una de las 3 marcas evaluadas dentro de la categoría en relación con sus niveles de notoriedad, preferencia y compra.
The purpose of this research is to determine the existing relation between the Target Rating Point (TRP's) levels understood as the monthly cumulative index Television rating against the levels of visibility (brand and advertising knowledge), preference (favoritism) and behavior (buy and next buy), to identify main trends derived from these associations in a mass consumption category. With this aim TRP's levels in Television were taken as a central predictor variable as well as the brand visibility measurements (top of mind, spontaneous and assisted), preference measurements (favorite brand) and the buying variables (brand bought in the last month and next brand to be bought) classified in the set of criterion variables. The design of this study is longitudinal in trend with K samples; the general sampling of the study includes a set of 4,104 added records derived from the replication of 58 monthly samples of 500 both male and female participants with ages between 12 and 60 years from strata 2 to 6 within a period between January 2004 and October 2008. Main findings enhance the establishment of associations statistically significant among the TRP's levels (low - medium and high) and the differential behavior of each of the 3 brands assessed within the category in relation with their visibility, preference and buying levels.
ABSTRACT
BACKGROUND: Cost containment through continuous quality improvement of medical service is required in an age of a keen competition of the medical market. Laboratory managers should examine the matters on make-or-buy decision periodically. On this occasion, a break-even point analysis can be useful as an analyzing tool. In this study, cost accounting and break-even point (BEP) analysis were performed in case that the immunoassay items showing a recent increase in order volume were to be in-house made. METHODS: Fixed and variable costs were calculated in case that alpha fetoprotein (AFP), carcinoembryonic antigen (CEA), prostate-specific antigen (PSA), ferritin, free thyroxine (fT4), triiodothyronine (T3), thyroid-stimulating hormone (TSH), CA 125, CA 19-9, and hepatitis B envelope antibody (HBeAb) were to be tested with Abbott AxSYM instrument. Break-even volume was calculated as fixed cost per year divided by purchasing cost per test minus variable cost per test and BEP ratio as total purchasing costs at break-even volume divided by total purchasing costs at actual annual volume. RESULTS: The average fixed cost per year of AFP, CEA, PSA, ferritin, fT4, T3, TSH, CA 125, CA 19- 9, and HBeAb was won 8,279,187 and average variable cost per test, won 3,786. Average break-even volume was 1,599 and average BEP ratio was 852%. Average BEP ratio without including quality costs such as calibration and quality control was 74%. CONCLUSIONS: Because the quality assurance of clinical tests cannot be waived, outsourcing all of 10 items was more adequate than in-house make at the present volume in financial aspect. BEP analysis was useful as a financial tool for make-or-buy decision, the common matter which laboratory managers meet with.