Department of Marketing

www.buseco.monash.edu

Modelling The Behaviour of Fuel Retail Consumers

Ari Pramono

Department of MarketingMonash University

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

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.

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

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

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.

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.

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

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 jIi,j is dummy indicating whether i is inside or outside j’s Feasibility Set

n = the total number of gas stations in the set

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

Methodology

Field Survey

Choice

Station Data

Trip Data Quality Index

StationCoordinates

Centroid coordinate

Distance matrices calculation

Detour distanceSpatial Dominance

OTF Model Development

Regional Digital Map

O-D Data

Tank levelTime of day

RevealedRevealed

StatedStated

Model Estimation : Sensitivity Method

origin Destination

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 Set Evidence of Feasibility Set

Motorists stick to their “mental map”Motorists stick to their “mental map”

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Probability to be choosen

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

Willingness To Travel

Consumers in search are more affected by spatio-temporal limitations, compare to consumers in regular planned choice

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

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

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Cumulative Probability

The maximum predicted Rank of the actual choice

OTF

SCM

CDM

Predictive Capability

Our model can predict the consumer’s preffered choice alternatives with 80% accuracy

Map of sales in gas station (kiloliters/day)

The origin location of demand (kiloliters/day)

Our model can be usedTo predict the origin ofdemand based on the salesin gas station

Example : city of Bandung, Indonesia

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

Implication & Further ResearchThe 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