Rosko M D, McKenna W
Soc Sci Med. 1983;17(7):421-9. doi: 10.1016/0277-9536(83)90347-7.
This paper has two objectives. First, we will describe how conjoint measurement, a multivariate marketing research technique, can be applied in health care marketing. Second, we will compare the validity of results from two conjoint measurement techniques--the full profile approach and the tradeoff approach. A convenience sample of 97 university students was used in the study. Fifty-two students supplied data by using the full profile approach. Each respondent provided a complete rank order of 26 profile cards which included the following ambulatory health service attributes: charge for routine visit, travel time, office hours, length of time needed to make an appointment, waiting time in physician's office, practice arrangement/freedom of physician choice, parking arrangements and type of hospital. A fractional factorial design was used to determine different attribute levels (e.g. charge for routine office visit could be set at $10, $20 or $30) for each card. Forty-five students performed ranking tasks for the trade-off approach to conjoint measurement. These respondents ranked 28 grids which represent all combinations of factors taken two at a time. From the data collected in the ranking tasks, utilities or part-worth values for each level of each attribute were estimated by using dummy variable regression. Relative importance of ambulatory service attributes was inferred from the range of utility values of the attributes. Three measures of validity were assessed--adherence of estimated utility scores to monotonic assumptions, plausability of importance rankings and comparative validity. The results from the full-profile approach satisfied all three criteria. In contrast, the tradeoff approach results satisfied the first two criteria, but its comparative validity was only marginal. Valid conjoint data can be used for: simulations of market responses to different health services configurations; market segmentation studies; and development of promotional efforts.
本文有两个目标。第一，我们将描述联合测量这一多元营销研究技术如何应用于医疗保健营销。第二，我们将比较两种联合测量技术——全轮廓法和权衡法——结果的有效性。本研究使用了一个由97名大学生组成的便利样本。52名学生通过全轮廓法提供数据。每位受访者对26张轮廓卡片进行了完整的排序，这些卡片包含以下门诊医疗服务属性：常规就诊费用、出行时间、办公时间、预约所需时间、在医生办公室的等待时间、执业安排/医生选择自由度、停车安排以及医院类型。采用分数因子设计来确定每张卡片的不同属性水平（例如，常规门诊就诊费用可以设定为10美元、20美元或30美元）。45名学生对联合测量的权衡法进行了排序任务。这些受访者对28个网格进行了排序，这些网格代表了一次取两个因素的所有组合。根据排序任务中收集的数据，通过使用虚拟变量回归估计每个属性每个水平的效用或部分价值。从属性效用值的范围推断门诊服务属性的相对重要性。评估了三种有效性度量——估计效用分数对单调假设的遵循情况、重要性排名的合理性以及比较有效性。全轮廓法的结果满足所有三个标准。相比之下，权衡法的结果满足前两个标准，但其比较有效性仅处于边缘水平。有效的联合数据可用于：模拟市场对不同医疗服务配置的反应；市场细分研究；以及促销活动的开展。
