Evaluation of the Aeroplan distinction status program desirability

Aeroplan 杰出地位计划的可取性评估

• 批准号: 529296-2018
• 负责人: Saucier, Antoine
• 金额: $ 1.82万
• 依托单位: École Polytechnique de Montréal
• 依托单位国家: 加拿大
• 项目类别: Engage Grants Program
• 财政年份: 2018
• 资助国家: 加拿大
• 起止时间: 2018-01-01 至 2019-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=664339
• 关键词: Evaluation; Aeroplan; distinction; status; program

The Aeroplan Distinction Status program was launched in 2014 by our partner Aimia Canada Inc. to give**further rewards and recognition to the program's most engaged and active members. Under that program,**members qualify for one of three tiers based on eligible mileage accumulation from the previous calendar year.**Each tier offers benefits such as rewards and access to promotions. Our partner wants to determine if the status**program has an influence on members earn behaviour, and if so, for what type of members. The difficulty in**this project is to detect specific changes in a time series that has a natural variability that may include**non-stationary components, trends and seasonal components. The detection of Earning Rate (ER) local changes**that are influenced by status can be regarded as a two-step procedure. First, one must detect local variability**changes in the ER time series. Second, on must show that the times of such changes coincide (i.e. are close to)**with the critical times associated with status qualification thresholds. To establish that such coincidences are**not accidental, they should be observed repeatedly for several critical times. Obtaining statistically significant**results may require the grouping of several members having similar ER behaviours. The project has two**objectives:**1) Detect local changes in the ER local variability via local statistical indicators and correlate them with**qualification threshold times. 2) Detect local changes in the ER local variability via deviations from best linear**prediction and correlate them with qualification threshold times.**We will achieve objective 1) by searching for coincidences between local statistical measures (to be**developed) and critical times associated with status qualification thresholds. We will achieve objective 2) by**first developing a linear predictor of the ER series, and then by examining the prediction deviation (prediction**minus actual value) for each ER series. This deviation should reveal changes in the ER variability that could be**indicative of behaviour change.

Aeroplan区别状态计划于2014年由我们的合作伙伴Aimia Canada Inc.启动，以给予**进一步的奖励和认可该计划最参与和活跃的成员。在该计划下，**成员根据上一个日历年的合格里程积累有资格获得三个层之一。我们的合作伙伴想确定状态**计划是否对成员赚取行为有影响，如果是，则对哪种类型的成员产生了影响。 **这个项目的困难是检测具有自然变异性的时间序列中的特定变化，该变化可能包括**非平稳组件，趋势和季节性组件。受状态影响的收入率（ER）局部变化的检测可以被视为两步程序。首先，必须检测局部变异性** ER时间序列的变化。其次，必须表明，这种变化的时间重合（即接近）**与与状态资格阈值相关的关键时间。为了确定这种巧合不是偶然的，应该在几个关键时期反复观察它们。获得具有统计学意义的结果可能需要将几个具有相似ER行为的成员分组。该项目有两个**目标：** 1）通过局部统计指标检测ER局部变异性的局部变化，并将其与**资格阈值时间相关联。 2）通过与最佳线性预测的偏差来检测ER局部变异性的局部变化，并将其与资格阈值时间相关联。**我们将实现目标1）通过搜索局部统计措施（已开发**）与状态资格阈值相关的局部统计指标（待制）之间的巧合。我们将通过**首先开发ER系列的线性预测因子，然后检查每个ER系列的预测偏差（预测**减去实际值）来实现目标2）。这种偏差应揭示ER变异性的变化，这可能**指示行为改变。