Global Growth in International Sport; AMS Conference 2014

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Where firms define targeted niches geographically, building a diversified niche portfolio involves difficult decisions concerning international market expansion. Our study addresses this challenge empirically by utilizing the context of Formula One (F1) motor racing to advance the study of a niche-based growth strategy. Specifically, we develop and test a model that examines the importance of native resources to the success of an international expansion strategy featuring a portfolio of geographically-defined niches. In order to approximate the demand for the sport of F1 (dependent variable) across numerous countries, we utilize hierarchical regression with a data set that features the advertising rates for standard commercial time during the broadcast of every F1 grand prix from 2007 to 2010 in 19 different countries across five continents.
Transcript
  • 1. Global Growth in International Sport: A Niche Portfolio Strategy Joe Cobbs, Jonathan A. Jensen, & Mark Groza
  • 2. INTRODUCTION Organizational ecology niche perspective Niche: multi-dimensional resource space (Hutchinson 1957) • Not exclusive to small market segments Resource perspective in organizational ecology • Niche broad or narrow, based on the variance of the resources (Milne et al., 1996) Niche portfolio strategy diversifies market risk • Success relies heavily on amount and quality of resources within targeted niches (Milne et al., 1996)
  • 3. Niche marketing strategy INTRODUCTION Particular market niche (Porter, 1980) • geographic boundaries • type of customer • segment of product line • combination of these three elements Niche marketing (Kotler 2003) • collection of customers of sufficient size • willing to pay a premium • unlikely to attract similar competitors • represent profit and growth potential Where niches defined geographically, building diversified portfolio involves international market expansion
  • 4. INTRODUCTION Application of Niche Strategy to Formula One • Very high spectator consumption (588m), yet drastic variation by region (Sylt and Reid 2011) • Model the importance of native resources to success of international expansion strategy • Build on theoretical foundation of Milne et al. (1996), who applied niche marketing strategy to sport industry
  • 5. Examination of Niche-based Resources HYPOTHESES • Resource categorization: participants, spectators, sponsors, media • H1. Participant-based resources: number of (a) events, (b) teams, and (c) championships • H2. Spectator-based resources: (a) population size and (b) gross national income [GNI] • H3. Sponsorship-based resources: (a) current corporate sponsor support and (b) corporate support potential (In-country market cap) • H4. Media-based resources: (a) traditional and (b) new media
  • 6. Demand DV: TV advertising rates METHOD Standard commercial time—rate card—for broadcast of every F1 grand prix over 4-year period in 19 countries, across five continents • sourced from UK-based media agency • Call for utilization of broadcast-related metrics to measure demand (Fort 2006; Tainsky 2010) • Broadcast rights fees dominant revenue source in sport industry (McCarthy 2013; Ourand 2013) • Actual attendance figures closely guarded • media reports often gross estimates or wholly inaccurate
  • 7. METHOD Table 1 F1 Broadcast Network by Sample Country Country Network Country (cont.) Network (cont.) Australia Ten Greece Alpha Austria ORF-1 ANT1 ORF-2 Hungary RTL Klub RTL Italy Rai Due Bahrain Bahrain TV Rai Uno Belgium Canvas (North) Japan Fuji Eén (North) Malaysia ESPN Asia La Deux (South) NTV7 La Une (South) Star Sports RTBF ASTRO Brazil Rede Globo Netherlands RTL7 Canada RDS Spain Canal 9 TSN IB3 TSN2 La Sexta China CCTV-5 TPA Television Principado de Asturias Guangdong TV Sports TV3 Guangzhou TV Competition Telecinco Shanghai Documentary U.K. BBC One Shanghai Great Sports BBC Two Denmark TV3 Puls U.S. FOX TV2/TV2 Zulu FOX Deportes France TF1 Speed Germany RTL Premiere
  • 8. METHOD Table 2 Means, Standard Deviations and Correlations Among Study Variables Variables Mean S.D. 1 2 3 4 5 6 7 8 9 1. AdRate (Thousands USD) 424.60 500.30 2. Events .74 .53 .40** 3. Teams .56 .87 .55** .14 4. Championships 2.64 3.60 .59** .19 .52** 5. Population (Millions) 132.00 301.40 .17 .12 -.14 -.11 6. GNI (Thousands USD) 33.50 15.90 -.04 -.14** .23 .11 -.45** 7. SponsorSpend (Millions USD) 132.00 212.20 .41** -.04 .49** .14 .02 .27* 8. MarketCap (Trillions USD) 2.06 3.72 .01 -.08 -.02 .04 .37** .13 .39** 9. News 211.38 111.83 .10 -.32** .46** .00 -.33** .58** .65** -.01 10. Internet 63.74 17.80 -.04 .30* .20 .12 -.52** .85** .35** .07 .64** * p < .05; ** p < .01
  • 9. RESULTS Table 3 Regression Results for Participant, Spectator, Sponsor and Media Resources effect on Ad Rates Independent Variables Model 1 Model 2 Model 3 Model 4 Model 5 2008 -.04 (0.27) -.03 (0.25) -.03 (0.26) -.07 (0.81) -.08 (0.90) 2009 -.05 (0.37) -.01 (0.08) -.01 (0.08) -.05 (0.49) -.04 (0.42) 2010 .05 (0.37) .06 (0.59) .05 (0.54) .06 (0.71) .08 (0.86) Participant Resources Events (H1a) .30** (3.36) .29** (3.04) .30** (3.50) .29** (3.17) Teams (H1b) .32** (3.14) .33** (3.27) .08 (0.78) .08 (0.68) Championships (H1c) .37** (3.63) .38** (3.90) .47** (5.24) .46** (4.80) Spectator Resources Population (H2a) .25** (2.67) .32** (3.38) .28** (2.78) GNI (H2b) .07 (0.71) .09 (0.85) .27 (1.71) Sponsor Resources SponsorSpend (H3a) .40** (4.08) .52** (4.04) MarketCap (H3b) -.28** (2.93) -.32** (3.16) Media Resources News (H4a) -.13 (0.81) Internet (H4b) -.19 (1.09) F-statistics .21 11.71 10.43 12.34 11.50 R2 .01 .52 0.57 .67 .69 ΔR2 .51** .05* .10** .02 Note: Standardized coefficents reported β; (t-value in Parentheses) * p < .05; ** p < .01
  • 10. H1, H2, & H3 supported RESULTS Participant-based resource variables are significant • (H1a) Events (β = .30, p < .01), (H1b) Teams (β = .32, p < .01) and (H1c) Championships (β = .37, p < .01) each yield significant coefficients Spectator-based resource supported by change in R2 (p < .05) • (H2a) Population (β = .25, p < .01), but (H2b) Income not supported (β = .07, p > .05) Sponsor-based resource supported by change in R2 (p < .05) • (H3a) Sponsor Spend (β = .40, p < .01), but (H3b) Market Cap negative effect (β = -.28, p < .01), based on low demand for F1 in US and China Media-based resource (H4) not supported
  • 11. DISCUSSION Application Example: Failure of F1 in Turkey First race in 2005; abandoned by 2012 (Cary, 2012) Media blamed poor attendance (BBC Sport, 2011) • Symptom of lack of demand for the sport in geographic niche Turkey as geographic niche • No participant resources (driver, team or event) • Marginal spectator resources (only 73 million consumers) • Minimal sponsor resources: 1 current corporate sponsor (Ofisi, who had spent $350,000 with Honda)
  • 12. Russia niche shows promise DISCUSSION • First race in Russian Federation in 2014 (BBC Sport, 2010) • Participant resource: Russia has boasted drivers (Vitaly Petrov, Daniil Kvyat) and team (Marussia Virgin Racing team) • Spectator resource: Population of 141 million above mean of study • Strong sponsor involvement • Race slated for Sochi, site of 2014 Winter Olympics and 2018 FIFA World Cup
  • 13. Questions? Joe Cobbs (cobbsj1@nku.edu) Jonathan A. Jensen (jensen.205@osu.edu) Mark Groza (mgroza@niu.edu)
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