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1 TVCM Understanding Effects of TV Advertising Elements on Consumer Responses Tatsuya Kawahara 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. Key words: advertising elements, TV advertisement, consumer response, random forests TVCM 1. ST P, 2007 Rossiter and Percy (1997) (1) (2) Video Research Ltd tatsuya.kawahara@videor.co.jp (3) 3 Aaker and Stayman (1990) TVCM amusing/clever, informative/effective, irritating/silly, dull, warm, lively, familiar, believable, confusing 9
2 Hovland (1951) Hovland (1951) Hovland (1951) Erdogan (1999) (Pieters and Wedel, 2004; Pieters, Wedel, and Zhang, 2007; Zhang, Wedel, and Pieters, 2009; Pieters, Wedel, and Batra, 2010) TVCM TVCM Stewart and Furse (1986) Stewart and Koslow (1989) Stewart and Koslow (1989) 160 Research Systems Corporation TVCM Stewart and Koslow (1989) 5% 1 1 Stewart and Koslow (1989)
3 TVCM [Stewart and Koslow (1989)] TVCM (1993) (1993) 2.2. Wells, Leavitt, and McConville (1971) Aaker and Stayman (1990) Smith, MacKenzie, Yang, Buchholz, and Darley (2007) (1996) (1996) TV-CM Karte
4 CM 9 CM 3 & CM 3 & (1996) (2006) (2009) TVCM TVCM Stewart and Furse (1986) Stewart and Koslow (1989) TVCM Stewart and Furse (1986) Stewart and Koslow (1989) CM CM TVCM TVCM TVCM & Stewart and Koslow (1989) 2 Stewart and Furse (1986) Stewart and Koslow (1989) TVCM 16: CM CM CM 7 TVCM CM CM
5 TVCM TV-CM Karte 1) CM CM 823 CM CM ) 1) 30 km ) Vakratsas and Ambler (1999) CM 3. CM 2 CM CM 3) CM CM 823 CM 4 4 CM A B 3) Singh and Rothschild, 1983; Singh, Rothschild, and Churchill, Jr., 1988
6 ) A 4) CM
7 TVCM 91 GRP GRP TVCM 3.3. Breiman (2001) 32 CART Breiman, Friedman, Olshen, and Stone, 1984 CART p j j GI = J J p j (1 p j)=1 j=1 entropy = j=1 J p j log p j j=1 S I(S) S S L, S R P (S L) I (S L)+P (S R) I (S R) P ( ) n L i( S L )=1 (y i ȳ L) 2 + n R i( S R )=1 (y i ȳ R) 2 n L n R ȳ L ȳ R Hastie, Tibshirani, and Friedman, K B 1,B 2,...,B k,...,b K 2. B k T k T k p 2 j
8 p m 2-2. m x } K Ĉ(x) =majority vote{ĉi(x) 1 ˆf(x) = 1 K K ˆT k (x) k= m K K m m Breiman, ) m Breiman (2002) p/2, p, 2 p m Hastie et al. (2009) p/3 p Out of Bag = OOB k MSE OOBMSE k = 1 n OOBk n OOBk i( OOB k )=1 (y i ŷ i,k ) 2 n OOBk k OOB ŷ i,k i k 2 x j k MSE OOBMSE k (x j permuted) = 1 n OOBk n OOBk i( OOB k )=1 (y i ŷ i,k (x j permuted)) 2 5) x σ 2 (x) K 1 K σ2 (x) ρ(x) K ρ(x)σ 2 (x) + 1 ρ(x) K σ2 (x) (Hastie et al., 2009) K 2 x ρ(x)σ 2 (x) ρ(x)
9 TVCM 93 3 OOBMSE k importance j = 1 K (OOBMSE k (x j permuted) OOBMSE k ) K k= Out of Bag = OOB 6) MSE MSE = 1 n (y i n ŷ i,oob ) 2 i=1 ŷ i,oob i OOB R 2 R 2 ( ) pseudo R 2 MSE =1 σ 2 y σ 2 y y 2. MSE Step1 K = 1000 =5 m Step2 MSE K Step3 MSE 6) OOB Breiman, 1996; Hastie et al., m MSE 2 MSE CM m =7 m =9 p/ MSE MSE 10 MSE m CM 7 9 K = 1000 = 5
10 MSE 6. MSE 3. MSE CM 206 CM 617 CM 206 CM 7) CM 2 CM 31 GRP F ) MSE 6 MSE CM 7 CM GRP CM CM CM CM
11 TVCM CM
12 A B
13 TVCM 97 4 CM 15 CM A B CM CM 1 6 CM CM CM 0 CM & GRP 800 GRP CM GRP CM 800 GRP 1800 GRP 1GRP 800 GRP CM CM CM GRP CM GRP 1 5 GRP 2000 GRP CM 6 CM
14 CM GRP CM Krugman (1972) Three Hit Theory 8) Anderson-Rubin CM GRP ) CM GRP 564 GRP 0 CM GRP 8) Campbell and Keller (2003) 9) CM =2 =2 K CM
15 TVCM CM CM 10) 12 10) =6 =8 =9 =11 =8 K
16 CM 4 CM CM CM CM CM 4 6 CM CM
17 TVCM
18 CM 10 CM CM CM 4 CM CM & CM 5. TVCM TVCM TVCM TVCM TVCM CM 2 GRP CM
19 TVCM 103 GRP CM GRP CM 3 (1996) CM & CM Stewart and Koslow (1989) CM 2 CM CM GRP CM CM CM & GRP 800 GRP CM 1GRP 800 GRP (Erdogan, 1999) Ohanian (1990) 3 15 CM CM (Bruner, 1990) Maclnnis and Jaworski (1989) Petty, Cacioppo, and Schumann (1983) 3
20 Maclnnis and Jaworski (1989) Petty et al. (1983) CM CM Schweidel, Bradlow, and Williams (2006) Strobl, Boulesteix, Zeileis, and Hothorn (2007) conditional inference tree Aaker, D. A. & Stayman, D. M. (1990). Measuring audience perceptions of commercials and relating them to ad impact. Journal of Advertising Research, 30(4), (2006).., 226, 2 9. (2009). CM., 36(1), Breiman, L., Friedman, J. H., Olshen, R. A. & Stone, C. J. (1984). Classification and regression trees. Wadsworth. Breiman, L. (1996). Out-of-bag estimation. breiman/ OOBestimation.pdf. Breiman, L. (2001). Random forests. Machine Learning, 45(1), Breiman, L. (2002). Manual on setting up, using, and understanding random forests V breiman/ Using random forests v4.0.pdf. Bruner II, G. C. (1990). Music, mood, and marketing. Journal of Marketing, 54(4), Campbell, M. C. & Keller, K. L. (2003). Brand familiarity and ad repetition effects. Journal of Consumer Research, 30(2), Erdogan, B. Z. (1999). Celebrity endorsement: A literature review. Journal of Marketing Management, 15(4), Hastie, T., Tibshirani, R. & Friedman, J. (2009). The elements of statistical learning: Data mining, inference, and prediction (2nd ed.). Springer. tibs/ ElemStatLearn/ Hovland, C. I. & Weiss, W. (1951). The influence of source credibility on communication effectiveness. Public Opinion Quarterly, 15(4), (1993).., 1(1), Krugman, H. E. (1972). Why three exposures may be enough. Journal of Advertising Research, 12(6), Maclnnis, D. J. & Jaworski, B. J. (1989). Information processing from advertisements: Toward an integrative framework. Journal of Marketing, 53(4), Ohanian, R. (1990). Construction and validation
21 TVCM 105 of a scale to measure celebrity endorsers perceived expertise, trustworthiness, and attractiveness. Journal of Advertising, 19(3), (2007)... Petty, R. E., Cacioppo, J. T. & Schumann, D. (1983). Central and peripheral routes to advertising effectiveness: The moderating role of involvement. Journal of Consumer Research, 10(2), Pieters, R. & Wedel, M. (2004). Attention capture and transfer in advertising: Brand, pictorial, and text-size effects. Journal of Marketing, 68(2), Pieters, R., Wedel, M. & Zhang, J. (2007). Optimal feature advertising design under competitive clutter. Management Science, 53(11), Pieters, R., Wedel, M. & Batra, R. (2010). The stopping power of advertising: Measures and effects of visual complexity. Journal of Marketing, 74(5), Rossiter, J. R. & Percy, L. (1997). Advertising communications & promotion management (2nd ed.). McGraw Hill Higher Education. Schweidel, D. A., Bradlow, E. T. & Williams, P. (2006). A feature-based approach to assessing advertisement similarity. Journal of Marketing Research, 43(2), Singh, S. N. & Rothschild, M. L. (1983). Recognition as a measure of learning from television commercials. Journal of Marketing Research, 20(3), Singh, S. N., Rothschild, M. L. & Churchill Jr, G. A. (1988). Recognition versus recall as measures of television commercial forgetting. Journal of Marketing Research, 25(1), Smith, R. E., MacKenzie, S. B., Yang, X., Buchholz, L. M. & Darley, W. K. (2007). Modeling the determinants and effects of creativity in advertising. Marketing Science, 26(6), Stewart, D. W. & Furse, D. H. (1986). Effective television advertising: A study of 1000 commercials. Lexington Books. Stewart, D. W. & Koslow, S. (1989). Executional factors and advertising effectiveness: A replication. Journal of Advertising, 18(3), Strobl, C., Boulesteix, A. L., Zeileis, A., & Hothorn, T. (2007). Bias in random forest variable importance measures: Illustrations, sources and a solution. BMC Bioinformatics, 8:25. (1996).., 4(1), Vakratsas, D. & Ambler, T. (1999). How advertising works: What do we really know? Journal of Marketing, 63(1), Wells, W. D., Leavitt, C. & McConville, M. (1971). A reaction profile for TV commercials. Journal of Advertising Research, 11(6), Zhang, Z., Wedel, M. & Pieters, R. (2009). Sales effects of attention to feature advertisement: A bayesian mediation analysis. Journal of Marketing Research, 46(5),
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