Transcript RM performance drivers

AoM OM Doctoral Consortium
Welcome!
Title
Date
Carrie Crystal
About me
Defended proposal Aug. 3
Anticipated graduation: Summer 2007
Committee Members:
Mark Ferguson A, Jeff Stratman A, Soumen Ghosh,
Koert van Ittersum (Marketing), Laurie Garrow
(Civil Engineering: RM)
Research Questions & Methodology
What influences revenue management success?
Example: To what degree do aligned incentives
impact performance?
How do firms differ in how they implement RM?
Cross sectional survey
Unit of analysis: hotel
Research contributions
Interplay of RM culture, RM capability on RM
performance
• Empirical test of RM performance drivers
• First rigorous study of culture in RM
• Prescription of how to improve RM
Revenue Management (RM)
Supply
Demand
Revenue
Management
(RM)
Revenue Management (RM)
P1
P2
P
Lost
Sales
P3
P4
Consumer
Surplus
Q
Q4
Q3
Q2
Q1
Literature Review
OR/ OM
McGill & van Ryzin (1999); Bitran & Caldentey
(2003); Talluri & van Ryzin (2004)
Hotels/ Hospitality
Kimes (1989); Donaghy et al. (1997); Farrell &
Whelan-Ryan (1998); Brotherton & Turner
(2001); Skugge (2003)
Airlines vs. Hotels
Airlines
Hotels
HQ
HQ
Examples
Project Approval
Continuous improvement or ROI based projects?
Alignment of Incentives
Salesperson’s preferred
Revenue Manager’s
customer
preferred customer
$200
- $20
$180
$190
Overview
Revenue Management
Capability
Revenue
Management Culture
Revenue
Management
Performance
Where should a firm invest valuable and scarce
resources to improve RM performance?
RM Capability
The technical processes and routines that facilitate
revenue management
Market
Segmentation
Pricing
Forecasting
Capacity
Allocation
IT
Revenue
Management
Capability
RM Culture
Executive
Commitment
a system of shared values and norms that
define appropriate attitudes and
behaviors for employees regarding
revenue management practices
Aligned
Incentives
Organizational
Structure
Education &
Training
Learning
Revenue
Management
Culture
Market
Segmentation
Pricing
Direct Model
Forecasting
H1a
Capacity
Allocation
IT
RM
Performance
RM Capability
RM Culture
Executive
Commitment
Aligned
Incentives
Learning
Organizational
Structure
Education &
Training
Market
Segmentation
Pricing
Moderating Model
Forecasting
H1b
Capacity
Allocation
IT Resources
RM
Performance
RM Capability
RM Culture
Executive
Commitment
Aligned
Incentives
Learning
Organizational
Structure
Education &
Training
Market
Segmentation
Mediating Model
Pricing
Forecasting
H1c
Capacity
Allocation
IT Resources
RM
Performance
RM Capability
RM Culture
Executive
Commitment
Aligned
Incentives
Learning
Organizational
Structure
Education &
Training
Competing Models
– Direct model indicates direct, simple impact
– Moderating model indicates multiplicative impact on
ROI
• Managers should balance resource allocation for best
return on investment
– Mediating model indicates temporal precedence,
impossibility of one without the other
Hotel data
• Hotels: experience, sample size, variation
• Respondents
– Revenue managers (unit of analysis: individual
hotel)
– Initial support from VPs of several major chains
• Responses
– Perceptual – IV
– Hotel specific performance metric, objective – DV
• Control
– Brand/ Class
– Location
– Management structure (franchised, owned, etc)
Hotel data - operationalization
• Pricing/ segmentation: marketing literature
– We understand the value our customers place on a
room and set rates accordingly.
– We promote our hotel differently to different groups
of customers.
• IT: OM literature/ RM users
– Our reservations and revenue management systems
are integrated
– The RM IT system meets business needs
• Etc.
• 3 rounds of q-sorting for indication of survey
validation
Contributions
•
•
•
•
Scale development
Empirical validation of analytical work
First rigorous study of culture in RM
Validation from and ongoing collaboration with
industry contacts
• Benchmark data for hotels
• Prescription of how to improve RM
• General framework for revenue management
Questions
• Multidimensional constructs
– Controversy in OB (Edwards, 2001)
– Acceptance in OM?
• Scale development paper – is it a good idea?
• Other suggestions/ questions?
Back up slides
Cross-Industry Data
• Purpose
– To see broad trends across industries
• Survey Respondents
– GT/ INFORMS conference participants
– Manugistics contact list
• Responses
– Perceptual – both independent and dependent
variables
Initial Observations
• Sample size = 27
• Significant, positive correlations:
Performance and…
– Pricing
– Executive commitment
– Learning (Experimentation,
Benchmarking, Feedback, Suggestions)
– Education and Training