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Understanding the attendance at cultural venues and events with stochastic preference models

机译：通过随机偏好模型了解文化场所和活动的出席情况

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This study proposes an alternative approach to the usual cognitive investigation of cultural venue and event attendance. This approach is based on stochastic preference theory. Specifically, the study utilises two well-known stochastic models of consumer behaviour: the NBD model and NBD-Dirichlet model to predict attendance behaviour at cultural venues and events. Using data from a large national survey across a range of cultural venues and events in Australia, including art:galleries, museums, zoological parks and aquariums, botanic gardens, archives, music concerts, theatre performances, dance performances, musicals and operas, and cinemas, the study shows that stochastic preference theory is able to predict the attendance at cultural venues and events. This theory has important implications for marketers of cultural venues and events, such as which segments of attendees should be targeted, predicting future attendance behaviour, as well as evaluating the effectiveness of marketing activities such as price promotion and advertising. (C) 2016 Elsevier Inc. All rights reserved.
机译：这项研究为文化场所和活动出席率的常规认知调查提出了另一种方法。该方法基于随机偏好理论。具体而言，该研究利用两种著名的消费者行为随机模型：NBD模型和NBD-Dirichlet模型来预测文化场所和活动中的出勤行为。使用来自澳大利亚的广泛全国性调查数据，涵盖澳大利亚各种文化场所和事件，包括艺术：画廊，博物馆，动物园和水族馆，植物园，档案馆，音乐演唱会，戏剧表演，舞蹈表演，音乐和歌剧以及电影院研究表明，随机偏好理论能够预测文化场所和事件的出席率。该理论对文化场所和活动的营销人员具有重要意义，例如应针对哪些参与者群体，预测未来的出勤行为以及评估营销活动（例如价格促销和广告）的有效性。 （C）2016 Elsevier Inc.保留所有权利。

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