1 Farm Team Shuffle: The Effects of Major League Affiliations in Minor League Baseball Nola Agha, University of San Francisco Joe Cobbs, Northern Kentucky University
Jun 24, 2015
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Farm Team Shuffle: The Effects of Major League Affiliations in
Minor League Baseball
Nola Agha, University of San FranciscoJoe Cobbs, Northern Kentucky University
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Minor League Baseball (MiLB)
• 19 leagues• 6-16 teams per
league• Attendance gains
24 of last 29 seasons
• 40+ million attendees (2010)
• Shifting geographic trend in parent affiliation
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Club Affiliation Decision
• Major League Administratorso Cannibalize attendance?o Player/Administrator travel timeo Administrative costso Managerial oversight/ownership
• Minor League Administratorso Attendance +/-o Fan identificationo Brand association/equity
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Research Questions
1. Does geographical proximity benefit the minor league team?
2. Do quality features of the major league club benefit the minor league team?
3. Does switching to a better affiliation benefit the minor league team?
4. Is there a switchingcost?
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Demand Theory in Baseball
• Attendance = f[price, quality, substitutes, income]
• MiLB: classifications not homogeneous(Agha, 2012; Branvold, Pan, & Gabert, 1997; Gitter & Rhoads, 2010)
o Win percentage non-significant at AAA; significant at AA
• New MiLB stadium• MLB team within 100 miles (-)• New MLB stadium
H1
H2
H3
H4
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Organizational Alliance Theory
• Smaller firms align with larger firms to establish marketplace legitimacy (Sarkar, Echambadi, & Harrison, 2001)
o Alliance strategy entails switching costs
• Alliance partner characteristics(Castellucci & Ertug, 2010; Dyer & Singh, 1998)
o Status: enhanced endorsement (Sarkar et al., 2001)
o Proximity: knowledge sharing, relational assets (Dyer & Singh, 1998)
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Alliance-based Hypothesis
• Alliance partner characteristics o Geographic distance (miles)o Status of MLB affiliate
o Market sizeo Popularity (attendance)o Win percentage H6c
H6b
H6a
H5
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Switching-based Hypothesis
• Switching costo Negative effect on MiLB team demand
• Attenuated by new partner characteristicso Geographic distance (miles)o Status of MLB affiliate
o Market sizeo Popularity (attendance)o Win percentage
H7
H9c
H9b
H9a
H8
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Data
• 15 years: 1992-2006o AAA: American Association, International
League, Pacific Coast Leagueo AA: Eastern League, Southern League,
Texas League
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Model
yjt = β1Xjt + β2Zjt + υj + εjt
yjt = natural log annual attendanceβ1 = vector of demand parametersXjt = vector of demand variablesβ2 = vector of MLB club parametersZjt = vector of MLB club variablesυj = PMSA specific fixed-effect εjt = random disturbance
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Results• Analysis 1: Do quality and distance to
alliance partner matter? (yes)
Variable AAA AA
H1. 36% Win percent 0.216 ***0.364
H2. 24% New MiLB Stadium ***0.215 0.075
H3. -53%, -13% Number of MLB in PMSA ***-0.749 **-0.141
H4. 6% New MLB Stadium **0.059 0.029
Strike 94/95 0.006 0.057
H5. 0.024% Affiliate Distance -0.00023258 ***0.0002
H5. -0.00001% Affiliate Distance Squared 0.0000001 ***-0.0000001
H6a. -0.000001% Affiliate Population **-0.00000001 0.00000001
H6b. 43% Affiliate Win Percent **0.434 0.343
H6c. -0.00001% Affiliate Attendance **-0.00000005 -0.00000002
***p<0.01, **p<0.05
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Results• Analysis 2: Does switching to a better or
closer affiliate matter? (no) • Is there a switching cost? (yes)
Variable AAA AAH1. 42% Win percent 0.280 ***0.424H2. 22% New MiLB Stadium ***0.200 0.081H3. -51%, -13% Number of MLB in PMSA ***-0.711 **-0.134H4. 6% New MLB Stadium **0.060 0.031
Strike 94/95 0.035 **0.075H7. -25% Affiliate Change Dummy -0.024 ***-0.293H8. Change to Closer Affiliate -0.129 0.059
H9a. Change to Affiliate with Higher Population -0.096 0.027
H9b.Change to Affiliate with Higher Win Percent 0.002 0.132
H9c.Change to Affiliate with Higher Attendance -0.144 0.134
***p<0.01, **p<0.05
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Discussion
• Consistent with demand theoryo AAA fans more concerned with MLB
affiliate successo MLB is substitute for MiLB
• Alliance implicationso AAA status as decision criteria for
affiliate decisionso AA switching costs, proximity as
decision criteria for affiliate decisions