1. BACKGROUND What happens when a new medium challenges an existing one? Several previous examples: –radio and print “public” changes -- actually a cohort effect –television and film at first - film profits were hurt later - film developed it’s own niche

2. BACKGRO VIDEOS VERSUS MOVIE THEATERS UND Will availability of feature films on video affect theater attendance? Windowing: –(Owen & Wildman, 1992; Litman, 1999) A form of price discrimination films are released to theaters before video for a consumer, waiting offers a cost savings Here: Examination of CONSUMERS VIDEOS VERSUS MOVIE THEATERS

3. HYPOTHESES Who will attend movies? H1: Younger people H2: Higher incomes H3: Smaller households H4: People with more interest in newer products Who will watch videos? H1: Older people H2: Lower incomes H3: Larger households H4: People with less interest in newer products HYPOTHESES

4. DDB’s 1996 Lifestyles data –initial mailings of 5,000 –4,041 total respondents (70% response rate) –3,130 supplemental survey (77% response rate) This research: –age, income, household size –desire for the latest products –movie and video consumption questions METHODS

5. # last year Attended filmRented video Bought video None 965 (31.1%)1264 (41.4%) 931 (30.2%) 1-4 times 1051 (33.6%) 527 (17.1%) 932 (30.5%) 5-8 times 510 (16.3%) 455 (14.7%) 442 (14.5%) 9-11 times 265 (8.5%) 367 (11.9%) 226 (7.4%) 12-24 times 215 (6.9%) 414 (13.4%) 123 (4.0%) 25-51 times 68 (2.2%) 248 (8.0%) 45 (1.5%) 52 or more 29 (0.9%) 143 (4.6%) 23 (0.8%) MEAN 2.37 3.04 2.10 # OF FILMS AND VIDEOS SEEN LAST YEAR

6. RESULTS: # OF FILMS H1: Younger people Beta = -.191, p <.001 - SUPPORTED H2: Higher incomes Beta =.201, p <.001 - SUPPORTED H3: Smaller households Beta = -.137, p <.001 - SUPPORTED H4: People w/more interest in newer products Beta =.138, p <.001 - SUPPORTED RESULTS: NUMBER of FILMS

7. H1: Older people Beta =.153, p <.001 - SUPPORTED H2: Lower incomes Beta = -.082, p <.001 - SUPPORTED H3: Larger households Beta =.189, p <.001- SUPPORTED H4: People w/less interest in newer products Beta = -.192, p =.001- SUPPORTED RESULTS: RATIO of VIDEOS/FILMS

8. Compatible with windowing strategy –MOST MOVIES: People who value “latest” see more movies Younger people People with higher incomes People from smaller families –The desire to be the first to own a product predicts “windowing” price discrimination CONCLUSIONS