Abstract

Substantial energy savings during the use phase of internal combustion and electric automobiles can be achieved by increasing eco-driving behavior, particularly reduced acceleration and braking. However, motivating widespread adoption of this behavior is challenging due to incompatibility with drivers’ values and priorities, and disassociation between drivers’ actions and observable consequences. Informational approaches, e.g., training programs and educational campaigns, are either difficult to scale up or largely ineffective, with drivers reluctant to make long-term changes. Alternatively, behavior can be influenced by redesigning the context within which the behavior occurs. Such an intervention must be effective across demographics and underlying behaviors to achieve ubiquity. The current study investigates the perceived effect on the driving style of a simple graphical dashboard display depicting an animated coffee cup. This display incorporates associative mental models and contextual relevance to increase the salience of inefficient vehicle movements and nudge drivers to adopt smoother driving. An online Amazon Mechanical Turk survey (92 participants) revealed a significant preference for the coffee-cup over a dial-gauge display when controlling for demographic variables. This result offers a preliminary indication that a behavioral nudge may be effective in influencing drivers to adopt eco-driving practices.

References

References
1.
Telenko
,
C.
,
O’Rourke
,
J. M.
,
Conner Seepersad
,
C.
, and
Webber
,
M. E.
,
2016
, “
A Compilation of Design for Environment Guidelines
,”
ASME J. Mech. Des.
,
138
(
3
), p.
031102
. 10.1115/1.4032095
2.
Mashhadi
,
A. R.
, and
Behdad
,
S.
,
2018
, “
Environmental Impact Assessment of the Heterogeneity in Consumers’ Usage Behavior: An Agent-Based Modeling Approach
,”
J. Ind. Ecol.
,
22
(
4
), pp.
706
719
. 10.1111/jiec.12622
3.
Barkenbus
,
J. N.
,
2010
, “
Eco-Driving: An Overlooked Climate Change Initiative
,”
Energy Policy
,
38
(
2
), pp.
762
769
. 10.1016/j.enpol.2009.10.021
4.
Sivak
,
M.
, and
Schoettle
,
B.
,
2012
, “
Eco-Driving: Strategic, Tactical, and Operational Decisions of the Driver That Influence Vehicle Fuel Economy
,”
Transport Policy
,
22
, pp.
96
99
. 10.1016/j.tranpol.2012.05.010
5.
Natural Resources Canada (NRCan)
, “
Fuel-Efficient Driving Techniques
,” Available: www.nrcan.gc.ca/energy/efficiency/transportation/21038, Accessed Jan. 23, 2020.
6.
Withanage
,
C.
,
Hölttä-Otto
,
K.
,
Otto
,
K.
, and
Wood
,
K.
,
2016
, “
Design for Sustainable Use of Appliances: A Framework Based on User Behavior Observations
,”
ASME J. Mech. Des.
,
138
(
10
), p.
101102
. 10.1115/1.4034084
7.
Steg
,
L.
, and
Vlek
,
C.
,
2009
, “
Encouraging Pro-Environmental Behaviour: An Integrative Review and Research Agenda
,”
J. Environ. Psychol.
,
29
(
3
), pp.
309
317
. 10.1016/j.jenvp.2008.10.004
8.
Shu
,
L. H.
,
Duflou
,
J.
,
Herrmann
,
C.
,
Sakao
,
T.
,
Shimomura
,
Y.
,
De Bock
,
Y.
, and
Srivastava
,
J.
,
2017
, “
Design for Reduced Resource Consumption During the Use Phase of Products
,”
CIRP Ann.
,
66
(
2
), pp.
635
658
. 10.1016/j.cirp.2017.06.001
9.
Ramani
,
K.
,
Ramanujan
,
D.
,
Bernstein
,
W. Z.
,
Zhao
,
F.
,
Sutherland
,
J.
,
Handwerker
,
C.
,
Choi
,
J.-K.
,
Kim
,
H.
, and
Thurston
,
D.
,
2010
, “
Integrated Sustainable Life Cycle Design: A Review
,”
ASME J. Mech. Des.
,
132
(
9
), p.
091004
. 10.1115/1.4002308
10.
Abrahamse
,
W.
,
Steg
,
L.
,
Vlek
,
C.
, and
Rothengatter
,
T.
,
2005
, “
A Review of Intervention Studies Aimed at Household Energy Conservation
,”
J. Environ. Psychol.
,
25
(
3
), pp.
273
291
. 10.1016/j.jenvp.2005.08.002
11.
Bao
,
Q.
,
Burnell
,
E.
,
Hughes
,
A. M.
, and
Yang
,
M. C.
,
2018
, “
Investigating User Emotional Responses to Eco-Feedback Designs
,”
ASME J. Mech. Des.
,
141
(
2
), p.
021103
. 10.1115/1.4042007
12.
Kahneman
,
D.
,
2003
, “
A Perspective on Judgement and Choice: Mapping Bounded Rationality
,”
Am. Psychol.
,
58
(
9
), pp.
697
720
. 10.1037/0003-066X.58.9.697
13.
Stanovich
,
K. E.
, and
West
,
R. F.
,
2000
, “
Individual Differences in Reasoning: Implications for the Rationality Debate?
,”
Behav. Brain Sci.
,
23
(
5
), pp.
645
726
. 10.1017/S0140525X00003435
14.
Evans
,
J. St B. T.
,
1984
, “
Heuristic and Analytic Processes in Reasoning
,”
Br. J. Psychol.
,
75
(
4
), pp.
451
468
. 10.1111/j.2044-8295.1984.tb01915.x
15.
Chaiken
,
S.
,
1980
, “
Heuristic Versus Systematic Information Processing and the Use of Source Versus Message Cues in Persuasion
,”
J. Pers. Soc. Psychol.
,
39
(
5
), pp.
752
766
. 10.1037/0022-3514.39.5.752
16.
Thaler
,
R.
, and
Sunstein
,
C.
,
2008
,
Nudge: Improving Decisions About Health, Wealth, and Happiness
,
Yale University Press, New Haven
,
CT
.
17.
Lehner
,
M.
,
Mont
,
O.
, and
Heiskanen
,
E.
,
2016
, “
Nudging—A Promising Tool for Sustainable Consumption Behaviour?
,”
J. Cleaner Prod.
,
134
, pp.
166
177
. 10.1016/j.jclepro.2015.11.086
18.
Kollmuss
,
A.
, and
Agyeman
,
J.
,
2002
, “
Mind the Gap: Why Do People Act Environmentally and What Are the Barriers to Pro-Environmental Behavior?
,”
Environ. Educ. Res.
,
8
(
3
), pp.
239
260
. 10.1080/13504620220145401
19.
She
,
J.
, and
MacDonald
,
E. F.
,
2017
, “
Exploring the Effects of a Product’s Sustainability Triggers on Pro-Environmental Decision-Making
,”
ASME J. Mech. Des.
,
140
(
1
), p.
011102
. 10.1115/1.4038252
20.
MacDonald
,
E. F.
, and
She
,
J.
,
2015
, “
Seven Cognitive Concepts for Successful Eco-Design
,”
J. Cleaner Prod.
,
92
, pp.
23
36
. 10.1016/j.jclepro.2014.12.096
21.
Goucher-Lambert
,
K.
, and
Cagan
,
J.
,
2015
, “
The Impact of Sustainability on Consumer Preference Judgments of Product Attributes
,”
ASME J. Mech. Des.
,
137
(
8
), p.
081401
. 10.1115/1.4030271
22.
Goucher-Lambert
,
K.
,
Moss
,
J.
, and
Cagan
,
J.
,
2017
, “
Inside the Mind: Using Neuroimaging to Understand Moral Product Preference Judgments Involving Sustainability
,”
ASME J. Mech. Des.
,
139
(
4
), p.
041103
. 10.1115/1.4035859
23.
Ranney
,
T.
,
Mazzae
,
E.
,
Garrott
,
R.
, and
Goodman
,
M.
,
2000
,
NHTSA Driver Distraction Research: Past, Present, and Future
,
National Highway Traffic Safety Administration
,
East Liberty, OH
.
24.
Deci
,
E. L.
, and
Ryan
,
R. M.
,
1987
, “
The Support of Autonomy and the Control of Behavior
,”
J. Pers. Soc. Psychol.
,
53
(
6
), pp.
1024
1037
. 10.1037/0022-3514.53.6.1024
25.
Stutts
,
J.
,
Feaganes
,
J.
,
Reinfurt
,
D.
,
Rodgman
,
E.
,
Hamlett
,
C.
,
Gish
,
K.
, and
Staplin
,
L.
,
2005
, “
Driver’s Exposure to Distractions in Their Natural Driving Environment
,”
Accid. Anal. Prev.
,
37
(
6
), pp.
1093
1101
. 10.1016/j.aap.2005.06.007
26.
Higgins
,
E. T.
,
2000
, “
Making a Good Decision: Value From Fit
,”
Am. Psychol.
,
55
(
11
), pp.
1217
1230
. 10.1037/0003-066X.55.11.1217
27.
Lockwood
,
P.
,
Jordan
,
C. H.
, and
Kunda
,
Z.
,
2002
, “
Motivation by Positive or Negative Role Models: Regulatory Focus Determines Who Will Best Inspire Us
,”
J. Pers. Soc. Psychol.
,
83
(
4
), pp.
854
864
. 10.1037/0022-3514.83.4.854
28.
Dahlinger
,
A.
,
Tiefenbeck
,
V.
,
Ryder
,
B.
,
Gahr
,
B.
,
Fleisch
,
E.
, and
Wortmann
,
F.
,
2018
, “
The Impact of Numerical vs. Symbolic Eco-Driving Feedback on Fuel Consumption—A Randomized Control Field Trial
,”
Transport. Res. Part D: Transport Environ.
,
65
, pp.
375
386
. 10.1016/j.trd.2018.09.013
29.
Orfila
,
O.
,
Saint Pierre
,
G.
, and
Messias
,
M.
,
2015
, “
An Android Based Ecodriving Assistance System to Improve Safety and Efficiency of Internal Combustion Engine Passenger Cars
,”
Transport. Res. C: Emerg. Technol.
,
58
, pp.
772
782
. 10.1016/j.trc.2015.04.026
30.
Hibberd
,
D. L.
,
Jamson
,
A. H.
, and
Jamson
,
S. L.
,
2015
, “
The Design of an In-Vehicle Assistance System to Support Eco-Driving
,”
Transport. Res. C: Emerg. Technol.
,
58
, pp.
732
748
. 10.1016/j.trc.2015.04.013
31.
Vagg
,
C.
,
Brace
,
C.
,
Hari
,
D.
,
Akehurst
,
S.
, and
Ash
,
L.
,
2013
, “
A Driver Advisory Tool to Reduce Fuel Consumption
,”
SAE Technical Papers, 3
.
32.
Lee
,
J. D.
,
Wickens
,
C. D.
,
Liu
,
Y.
, and
Boyle
,
L. N.
,
2017
,
Designing for People: An Introduction to Human Factors Engineering
, 3rd ed.,
CreateSpace, Charleston
,
SC
.
33.
St. John
,
M.
,
Cowen
,
M. B.
,
Smallman
,
H. S.
, and
Oonk
,
H. M.
,
2001
, “
The Use of 2D and 3D Displays for Shape-Understanding Versus Relative-Position Tasks
,”
Hum. Factors: J. Hum. Factors Ergonom. Soc.
,
43
(
1
), pp.
79
98
. 10.1518/001872001775992534
34.
Cohen
,
J.
,
1988
,
Statistical Power Analysis for the Behavioral Sciences
, 2nd ed.,
Lawrence Earlbaum Associates
,
Hillsdale, NJ
.
35.
McIlroy
,
R. C.
, and
Stanton
,
N. A.
,
2017
, “
What Do People Know About Eco-Driving?
,”
Ergonomics
,
60
(
6
), pp.
754
769
. 10.1080/00140139.2016.1227092
36.
Ross
,
J.
,
Six Silberman
,
M.
,
Zaldivar
,
A.
, and
Tomlinson
,
B.
,
2010
, “
Who Are the Crowdworkers?: Shifting Demographics in Amazon Mechanical Turk
,”
Conference on Human Factors in Computing Systems—Proceedings
,
Atlanta, GA
,
Apr. 10–15
, pp.
2863
2872
.
37.
van Sonderen
,
E.
,
Sanderman
,
R.
, and
Coyne
,
J. C.
,
2013
, “
Ineffectiveness of Reverse Wording of Questionnaire Items: Let’s Learn From Cows in the Rain
,”
PLoS One
,
8
(
7
), p.
e68967
. 10.1371/journal.pone.0068967
38.
McCartt
,
A. T.
,
Mayhew
,
D. R.
,
Braitman
,
K. A.
,
Ferguson
,
S. A.
, and
Simpson
,
H. M.
,
2009
, “
Effects of Age and Experience on Young Driver Crashes: Review of Recent Literature
,”
Traffic Inj. Prev.
,
10
(
3
), pp.
209
219
. 10.1080/15389580802677807
39.
Lyu
,
N.
,
Xie
,
L.
,
Wu
,
C.
,
Fu
,
Q.
, and
Deng
,
C.
,
2017
, “
Driver’s Cognitive Workload and Driving Performance Under Traffic Sign Information Exposure in Complex Environments: A Case Study of the Highways in China
,”
Int. J. Environ. Res. Public Health
,
14
(
2
), pp.
203
228
. 10.3390/ijerph14020203
40.
Kormos
,
C.
, and
Gifford
,
R.
,
2014
, “
The Validity of Self-Report Measures of Proenvironmental Behavior: A Meta-Analytic Review
,”
J. Environ. Psychol.
,
40
, pp.
359
371
. 10.1016/j.jenvp.2014.09.003
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