2002 Fiscal Year Final Research Report Summary
Data Envelopment Approximation model in the Stochastic Frontier Analysis and Its Application to TV Advertising Planning
| Project/Area Number |
13630123
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Commerce
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| Research Institution | Osaka University |
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Principal Investigator |
TAKEDA Eiji Osaka University, Graduate School of Economics, Professor, 大学院・経済学研究科, 教授 (80106624)
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| Project Period (FY) |
2001 – 2002
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| Keywords | Advertising planning / Stochastic frontier analysis / Data envelopment analysis / TV advertising efficiency / 効率性 |
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| Research Abstract |
This report is concerned with TV advertising efficiency.
The substantial volume of the past research on advertising has focused on advertising effectiveness. On the other hand, although advertising productivity (or efficiency) has been identified as an important issue, research on advertising productivity is still limited. The efficiency is measured by the ratio of observed oulput(s) to maximum potential output(s) obtainable from the given input(s). The frontier analysis addresses advertising efficiency. There are, however, not least situations in which it is difficult to know the functional fame of the frontier, for instance, the maximum awareness value of the audiences given the number of repetitive insertions of a certain TV commercial to dayparts because of many factors in TV advertising.
In this report,
1. we proposed the data envelopment approximation (DEAP) model for an optimization problem in the stochastic frontier model with unknown functional form of the frontier based on DEA. As an application, we described the optimal allocation of spots to dayparts so as to maximize the "CM- awareness" under the constraint of advertising budget using the past TV commertials by CM-KARTE;
2. we also employed another DEA approach to the problem of repetitive insertions of a certain TV commercial to dayparts so as to attain the maximum "reach" of each target segment simultaneously. In general, there are enormous daypart combinations within an advertising budget because of a fine partition of time interval of day. Therefore, generating many individual allocating patterns and exploring efficient allocations which are progressively located by DEA, a near optimal daypart allocation under the constraint of advertising budget is examined.
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