2. Structure of the Presentation
Fuel Retailing: Overview
Topic- 1 : Accessibility as a determinant of
consideration sets
Topic – 2: Modeling gas station choice as an “on-
the-fly” choice process
3. Fuel Retailing : Overview
• Product
– Homogeneity (product specification, price)
– No direct substitutes.
• Industry
– Horizontal and vertical integration
– Importance to economy (Ma et.al, 2011)
• Spatial Economic
– Spatial correlation
– Firm’s spatial competitive behaviour (Hotelling’s law)
– Spatial Interaction.
4. Fuel Retailing : Overview
• Consumer Behaviour
– Mental Map (Dingemans et.al 1986)
– Spatio – temporal bounded rationality (Kitamura and Sperling
1987)
– Asymmetric competition ( Cooper and Jones 2007)
– Choice or Search ? (Dingemans et.al 1986) (Dellaert & Haubl,
2012)
• Modelling :“ spatial choice conducted “while in motion”
On-The-Fly (OTF) Choice ModelOn-The-Fly (OTF) Choice Model
5. Several complexities in modeling OTF choice….
1. The choice (shopping location) is NOT the
destination of the trip!
• Distance ‘decay’ definitions?
• Accounting of consumer path trajectory
1. Choice set endogeneity
• Numerous alternatives
• The applicability of stage wise process
• Spatio-temporal limitation
1. Accounting for Spatial Structure
• Relativity to Consumer Movement
6. Research Objectives
• Investigating the choice set generation
process
• Developing a choice model for the planned
choice and ad-hoc search situation.
• Investigate the nature of spatial competition
among gas stations.
7. Topic- 1 : Accessibility as a determinant of consideration sets
(*)
• Research questions :
– Role of consideration set in spatio-temporally limited situation
• Method : Monte Carlo simulation (estimation: MNL and CMNL)
• Findings :
– The role of the consideration set depends on level of accessibility.
The more restrictions are imposed on access, the more important the
consideration set becomes in setting the outcome of the choice process.
– Two stage model only performs better in a limited accessibility condition,
otherwise it is at par with a one stage model.
– The importance of non-spatial attribute is moderated by spatio-temporal
limitation
(*) Has been published in the Journal of Choice Modeling, 5(1), 22 - 45.
8. Topic- 2 : Modeling consumer behavior during refueling as an “on-the-fly” choice
process
Planned Refueling Ad-hoc Search
Behaviour mode Choice mode Search mode
Decision making Compensatory binary
Hierarchical Sequential
Modelling Two-stage One-stage
Trade off betwen
spatial & non
spatial
Importance of
spatial attribute
over non-spatial
9. Model : Fixed Effect Conditional Logit (McFadden 1977)
or also referred as Multinomial Logit
Probability of consumer j, characterized by attribute Gj, choosing gas station i,
with attributes Xi,j , is calculated as :
Xi,j is vector of spatial and non spatial attributes of i in regards to j
Gj is vector of contextual attributes of individual j
Ii,j is dummy indicating whether i is inside or outside j’s Feasibility Set
n = the total number of gas stations in the set
10. Regular model OTF model
Spatial
Separation effect
(distance decay
effect)
Distance (or travel cost)
between the shopper and
the store (or gas station)
Detour distance : the
length of deviation from
the shopper’s original O-D
route needed to reach the
store (or fuel station).
Spatial Structure
effect
(agglomeration
effect)
Spatial correlation (or
interdependence) among
stores (or fuel stations) i.e.
clustering or spatial
differentiation.
Spatial dominance: The
relative intervening
sequence of the stores (or
fuel stations) in regard to
the shopper’s O-D path.
(Cascetta & Papola, 2009)
Accounting for Spatial Attributes : OTF vs Regular spatial model
14. MNL Choice Search
Coeff t-stat Coeff t-stat OTF t-stat
Cons 1.447837 5.73 1.536715 5.98 -0.1018341 -0.2
cons2 -12.72077 -0.02 -15.99286 -0.02 -1.544937 -0.6
Detour -0.0006438 -9.24 -0.0005171 -6.14 -0.0002847 -4.84
Quality 0.0622467 1.82 0.2163645 3.59 0.001141 0.04
log (dominance) -0.7883585 -5.03 -0.7952468 -5.07 -1.202707 -4.61
detour x midday -0.0003127 -2.25 -0.0002737 -2.01 -0.0001101 -1.17
quality x
midday -0.0362741 -0.66 -0.0110604 -0.2 0.0186984 2.03
dominance x
mid day 0.1240502 0.49 0.12658 0.5 -0.1208099 -0.29
detour x low
tank 0.0001003 0.92 0.0000681 0.66 -0.0000653 -0.59
quality x low
tank 0.0161144 0.3 0.0009624 0.2 -0.023841 -3.54
dominance x
low tank 0.3653381 1.52 0.3698403 1.53 0.650738 1.44
threshold (�) 18.08971 18.09 1.076813 1.82
� x quality -0.1988119 -0.2 -0.0045611 -0.69
FOS 1.092104 3.82
FOS x tank 0.2120251 0.44
FOS x off peak -0.885995 -2.03
Importance of Station Quality only in
two -stage
Importance of Station Quality only in
two -stage
Location is more important in searchLocation is more important in search
In off-peak hours motorists are less
concern about location
In off-peak hours motorists are less
concern about location
In off-peak hours Quality becomes
slightly important in search mode
In off-peak hours Quality becomes
slightly important in search mode
But if the tank is low ... they don’t care
about quality
But if the tank is low ... they don’t care
about quality
Evidence of Feasibility SetEvidence of Feasibility Set
Motorists stick to their “mental map”Motorists stick to their “mental map”
15. 0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
0 250 500 750 1000 1250 1500 1750 2000 2250 2500 2750 3000
Probabilitytobechoosen
distance (meters)
Quality=92
Quality=87
Quality=85
Quality=83
Quality=81
Quality=93
Quality=91
The impact of distance for different Station Quality level
1. Consumer is first concern about distance (only choose stations within < 1.5 Km) .
2. Except for best quality stations , they allow for additional 500 – 750 meters
16. Willingness To Travel
Consumers in search are more affected by spatio-temporal limitations,
compare to consumers in regular planned choice
17. Choice mode
Search mode
Role of Spatial Dominance
Consumers in search mode will
most likely to stop in station 1,
regardless the quality of station-2.
Consumers in choice mode will most
Likely to continue to station-2 if
It has at least 2 quality score higher than
station1
18. SSM = Spatial Structure Model (Timmermans & Borgers (1985)
CDM = Competing Destinatin Model (Fotheringham, 1988)
Our model outperforms
the previous model
Our model outperforms
the previous model
Comparison with existing Model
20. Map of sales in gas station (kiloliters/day)
The origin location of demand (kiloliters/day)
Our model can be used
To predict the origin of
demand based on the sales
in gas station
Example :
city of Bandung, Indonesia
21. Conclusions
• Both modes of Refueling activity (Choice and Search) can be effectively modeled as “on the
fly” spatial choice model based on typical MNL framework.
• Choice mode is more aligned with planned behaviour.
– compensatory trade offs between both spatial and non spatial attributes
– 2 stage processes (Consideration stage + Choice stage).
• Search mode tends to be a sequential decision behaviour,
– Importance of spatio temporal limitations
– Saptial over non-spatial attractiveness
– stage wise choice set development become less relevant.
• The study introduce the methodology to account for complexity casued by decision
maker’s movement in the spatial choice model.
– Spatial cognition (Mental Map)
– Spatio-temporal limittaion
22. Implication & Further Research
The On-The Fly model could potentially be applied for study
about :
– Perceptual (behavioral) based spatial competition modelling.
– Multipurpose shopping (activity) modelling.
– Studies involving analysis of path movement (Hui, Fader & Bradlow
2009):
• Supermarket (Grocery) shopping
• Eye tracking movement
• Web browsing
• Pedestrian movement
