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BACKGROUND

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. VIDEOS VERSUS MOVIE THEATERS.

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BACKGROUND

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  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. VIDEOS VERSUSMOVIE THEATERS BACKGRO VIDEOS VERSUSMOVIE 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

  3. HYPOTHESES 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

  4. METHODS • 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

  5. # OF FILMS AND VIDEOS SEEN LAST YEAR # last year Attended film Rented 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

  6. RESULTS:NUMBER of FILMS 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

  7. RESULTS:RATIO of VIDEOS/FILMS 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

  8. CONCLUSIONS 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

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