行動計量学
Online ISSN : 1880-4705
Print ISSN : 0385-5481
ISSN-L : 0385-5481
43 巻 , 1 号
選択された号の論文の9件中1~9を表示しています
特集 確率論とリスク論の悩ましき関係
原著
資料
  • 上田 雅夫
    原稿種別: 資料
    2016 年 43 巻 1 号 p. 69-83
    発行日: 2016年
    公開日: 2016/09/09
    ジャーナル フリー

    The purpose of this research is to offer the point which utilizes the brand association network for brand management. For this purpose, the consumer survey was performed four times from the same respondents in order to collect brand association networks.

    The following three points became clear from result of this survey

    ● The brand association network change with time

    ● The change is not only an addition and disappearance of the association in a network, but also combination of a link, and cutting.

    ● The relations among associations are not stable, and changes with time. This means that a certain association meaning has also changes with time.

  • 河原 達也
    原稿種別: 資料
    2016 年 43 巻 1 号 p. 85-105
    発行日: 2016年
    公開日: 2016/09/09
    ジャーナル フリー

    Advertising investment risk has become high due to the explosive information increase and the commoditization evolution. In order to reduce such risk, it is important to understand the relation between advertising elements and consumer responses, and apply the knowledge to decision making process of advertising production. There have been lots of efforts to develop a set of scales to measure the advertising perceptions and relate it to the consumer responses. However, that is not adequate when we assume to support the actual practices of the advertising production. Although the advertising perceptions are helpful to understand the reasons of the consumer responses, they don't directly lead the way to the advertising production.

    In this study, we analyze the effects of 28 elements of TV advertisements on the advertising perceptions and the consumer responses. The elements adopted in this study are controllable by advertisers so that they can apply the research findings to the advertising production. Empirical analyses using a dataset of the advertising perceptions and the consumer responses to more than 800 TV advertisements clarified not only the important advertising elements which had high impacts on the consumer responses but also how and why they affect consumer responses. Simultaneously, simulation of the consumer responses using random forests was found to be helpful to explore the effective combination of the advertising elements.

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