De l'influence des green nudges sur les problèmes environnementaux

Bibliographie

Sebastian Berger, »The Power of the Nudge to Change Our Energy Future», Scientific America, 29/12/2015

Cialdini R.B. et al. (1990), »A focus theory of normative conduct: Recycling the concept of norms to reduce littering in public places», Journal of Personality and Social Psychology, vol. (58)6

Chouteau (2015), »Les nudges, du concept à la mise en oeuvre»

Centre d'analyse stratégique, directeur de la publication Vincent Chriqui, (2011), »Nudges verts»: de nou-

velles incitations pour des comportements écologiques.

15

Christophe Demarque, Laetitia Charalambides, Denis J.Hilton, Laurent Waroquier, (2015) »The use of descriptive norms to promote a minority behavior in a realistic online shopping environment», »Journal of Environmental Psychology»

Goldstein N.J. et al. (2008), »A room with a viewpoint: Using social norms to motivate environmental conservation in hotels», Journal of Consumer Research, vol. 35(3)

Nolan J. et al. (2008), »Normative social influence is underdetected», Personality and Social Psychology Bulletin, vol. 34.

Schultz P.W. (1998), »Changing behavior with normative feedback interventions: A field experiment on curbside recycling», Basic and Applied Social Psychology, vol. 21(1)

Eric Singer (2015), »Green Nudge, réussir à changer les comportements pour changer la planète», Pearson France

Richard Thaler, Cass Sunstein (2008), »Nudge: Improving Decisions about Health, Wealth, and Happiness»

Fawaz Teffahi, »Canibal veut rendre le recyclage ludique», L'Express Entreprise, 22/08/2014

6. Annexes

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Statistics/Data Analysis

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(R)

User: onj Project: inj

1.0000

scoreenvir

voussentez~l

0.5673 1.0000

/__ / ____/ / ____/

___/ / /___/ / /___/ 12.0 Copyright 1985-2011 StataCorp LP

Statistics/Data Analysis StataCorp

4905 Lakeway Drive

Special Edition College Station, Texas 77845 USA

800-STATA-PC http://www.stata.com

979-696-4600 [e-mail]

979-696-4601 (fax)

Single-user Stata network perpetual license: Serial number: 93611859953

Licensed to: Kamara Mamadi

MK-00

Notes:

1. (/v# option or -set maxvar-) 5000 maximum variables

1 . use " C:\Users\mamad\Desktop\Economie de l'environnement\Exposé économie de l'environnement\ex

2 . do " C:\Users\mamad\AppData\Local\Temp\STD01000000.tmp"

3 . reg scoreenvir age voussentezvousconcernparlesprobl visionéco3 visionéco5 visionéco6 visionéc

Source	SS	df	MS			Number of obs F( 17, 234)			= =	252 13.44
Model	18664.8786	17	1097.93403			Prob > F			=	0.0000
Residual	19111.5371	234	81.6732355			R-squared			=	0.4941
						Adj R-squared			=	0.4573
Total	37776.4157	251	150.503648
						Root MSE			=	9.0373
scoreenvir				Coef.	Std. Err.		t	P>|t|			[90% Conf.	Interv
age				.1403468	.0522461		2.69	0.008			.0540681	.2266
voussentezvousconcernparlesprobl				2.269547	.2794074		8.12	0.000			1.808136	2.730
visionéco3				2.601616	1.417107		1.84	0.068			.2614177	4.941
visionéco5				6.220313	2.280841		2.73	0.007			2.453752	9.986
visionéco6				-4.313382	1.668992		-2.58	0.010			-7.069541	-1.557
visionéco8				-13.78411	6.564212		-2.10	0.037			-24.62419	-2.944
branche2				-6.163113	2.37119		-2.60	0.010			-10.07888	-2.24
branche4				-4.198495	1.623983		-2.59	0.010			-6.880327	-1.516
dpt
2				-2.399681	2.657606		-0.90	0.367			-6.788429	1.989
3				2.058735	4.480073		0.46	0.646			-5.33962	9.45
4				-6.447568	4.883281		-1.32	0.188			-14.51178	1.616
5				-2.496338	2.440195		-1.02	0.307			-6.526056	1.53
6				-6.463806	2.300971		-2.81	0.005			-10.26361	-2.664
7				-7.148199	2.675907		-2.67	0.008			-11.56717	-2.729
8				-5.882972	3.192581		-1.84	0.067			-11.15517	-.6107
9				-4.660442	2.297798		-2.03	0.044			-8.455006	-.8658
10				-6.427616	2.995782		-2.15	0.033			-11.37483	-1.480
_cons				13.23524	3.436512		3.85	0.000			7.560215	18.91

4 . corr scoreenvir voussentezvousconcernparlesprobl (obs=253)

scoree~r vousse~l

_u Friday March 17 15:16:40 2017 Page 2

5 . reg scoreenvir Source	voussentezvousconcernparlesprobl SS df MS			Number of obs F( 1, 251)		= =	253 119.09
Model	12208.3291	1	12208.3291
				Prob	> F	=	0.0000
Residual	25731.4713	251	102.515822	R-squared		=	0.3218
				Adj	R-squared	=	0.3191
Total	37939.8004	252	150.554763
				Root	MSE	=	10.125

scoreenvir

Coef. Std. Err. t P>|t| [95% Conf. Interv

voussentezvousconcernparlesprobl

_cons

2.944926 .269862 10.91 0.000 2.413443 3.476

7.128082 2.036919 3.50 0.001 3.116452 11.13

6 . alpha scorerecycl scorecomp scorelabel scoretravail Test scale = mean(unstandardized items)

Average interitem covariance: 1.083668

Number of items in the scale: 4

Scale reliability coefficient: 0.6434

7 . gen scorerecycl2= 2* scorerecycl

8 . gen scorelabel2 =2.5* scorelabel

9 . gen scoretravail2= 2* scoretravail

10 . alpha scorerecycl2 scorelabel2 scoretravail2 scorecomp Test scale = mean(unstandardized items)

Average interitem covariance: 3.475949

Number of items in the scale: 4

Scale reliability coefficient: 0.6424

11 . reg scoreenvir age voussentezvousconcernparlesprobl visionéco3 visionéco5 visionéco6 visionéc

Source	SS	df	MS			Number of obs F( 18, 233)			= =	252 12.99
Model	18923.8494	18	1051.32497			Prob > F			=	0.0000
Residual	18852.5662	233	80.9123015			R-squared			=	0.5009
						Adj R-squared			=	0.4624
Total	37776.4157	251	150.503648
						Root MSE			=	8.9951
scoreenvir				Coef.	Std. Err.		t	P>|t|			[90% Conf.	Interv
age				.1397878	.0520031		2.69	0.008			.0539088	.2256
voussentezvousconcernparlesprobl				2.178157	.2827555		7.70	0.000			1.711209	2.645
visionéco3				2.744417	1.412747		1.94	0.053			.4113797	5.077
visionéco5				6.391495	2.272207		2.81	0.005			2.639129	10.14
visionéco6				-4.583293	1.668036		-2.75	0.006			-7.33792	-1.828
visionéco8				-12.7097	6.561104		-1.94	0.054			-23.54484	-1.874
branche2				-6.498887	2.367569		-2.74	0.007			-10.40874	-2.589
branche4				-4.310841	1.617619		-2.66	0.008			-6.98221	-1.639
femme				2.135075	1.193425		1.79	0.075			.1642303	4.10
dpt
2				-2.93174	2.661863		-1.10	0.272			-7.327593	1.464
3				2.543337	4.467374		0.57	0.570			-4.834173	9.920
4				-6.523569	4.860665		-1.34	0.181			-14.55057	1.50
5				-2.679909	2.430968		-1.10	0.271			-6.694457	1.334
6				-6.829498	2.299331		-2.97	0.003			-10.62666	-3.032
7				-6.961777	2.66545		-2.61	0.010			-11.36355	-2.559
8				-5.820639	3.177865		-1.83	0.068			-11.06863	-.5726
9				-4.771961	2.287918		-2.09	0.038			-8.550274	-.9936
10				-6.499668	2.982066		-2.18	0.030			-11.42431	-1.575
_cons				12.99561	3.423087		3.80	0.000			7.342657	18.64

_u Friday March 17 15:16:40 2017 Page 3

12 . alpha scorerecycl2 scorelabel2 scoretravail2 scorecomp, std item label Test scale = mean(standardized items)

item-test item-rest interitem

Item	Obs	Sign	corr.	corr.	corr.	alpha	Label
scorerecycl2	253	+	0.7372	0.4933	0.3026	0.5655
scorelabel2	253	+	0.7305	0.4828	0.3088	0.5728
scoretrava~2	253	+	0.6508	0.3641	0.3839	0.6515
scorecomp	253	+	0.7065	0.4458	0.3315	0.5980
Test scale					0.3317	0.6650	mean(standardized items)

13 .

end of do-file

14 .

User: Romain Vasseur

___ ____ ____ ____ ____ (R)

/__ / ____/ / ____/

___/ / /___/ / /___/ 12.0 Copyright 1985-2011 StataCorp LP

Statistics/Data Analysis StataCorp

4905 Lakeway Drive

Special Edition College Station, Texas 77845 USA

800-STATA-PC http://www.stata.com

979-696-4600 [e-mail]

979-696-4601 (fax)

Single-user Stata network perpetual license: Serial number: 93611859953

Licensed to: Romain Vasseur

Notes:

1. (-set maxvar-) 5000 maximum variables

1 . use "/Users/Romain/Desktop/Projet eco environnement/Expose_eco_environnement.dta"

2 . gen travailecolo1=9*travailecolo

3 . gen infoecolo=9*infoeco

4 . gen clima=9*climatique

5 . gen alibio=9*bio

6 . gen recycle=2.25*recyclage

7 . gen visioneco=9*vision

8 . alpha travailecolo1 infoecolo clima alibio recycle visioneco recycle moyen concerne engager, std item l

> l

Test scale = mean(standardized items)

Item	Obs	Sign	item-test corr.	item-rest corr.	interitem corr.	alpha	Label
travaile~lo1	253	+	0.5255	0.3546	0.2165	0.6885
infoecolo	253	+	0.6104	0.4575	0.2015	0.6688
clima	253	+	0.3270	0.1303	0.2514	0.7288
alibio	253	+	0.6484	0.5051	0.1948	0.6594
recycle	253	+	0.6197	0.4691	0.1999	0.6665
visioneco	253	+	0.4599	0.2781	0.2280	0.7026
moyen	253	-	0.3564	0.1621	0.2463	0.7233
concerne	253	+	0.7069	0.5804	0.1845	0.6442
engager	253	+	0.6757	0.5399	0.1900	0.6524
Test scale					0.2126	0.7084	mean(standardized items)

9 .

10 . gen idf1=0 if dpt==1

(226 missing values generated)

mardi '( mars '*(+ à ('-'' Page (

User: Romain Vasseur

11 . replace idf1=0 if dpt==10 (15 real changes made)

12 . replace idf1=0 if dpt==. (1 real change made)

13 . replace idf1=1 if idf1==. (210 real changes made)

14 . reg score2 age femme sport polvert etudiant transportcommun culturelle association idf1,level(90)

Source	SS		df		MS		Number of obs =			253
							F( 9, 243) =			11.69
Model	23426.1434		9		2602.90482		Prob > F =			0.0000
Residual	54118.5582		243		222.710116		R-squared =			0.3021
							Adj R-squared =			0.2763
Total	77544.7016		252		307.71707		Root MSE =			14.923
score2		Coef.		Std. Err.		t		P>|t|	[90% Conf.		Interval]
age		.3928805		.1177896		3.34		0.001	.1983924		.5873687
femme		6.33292		1.971896		3.21		0.001	3.077027		9.588812
sport		5.124088		2.017583		2.54		0.012	1.79276		8.455416
polvert		14.83286		2.053416		7.22		0.000	11.44236		18.22335
etudiant		5.176987		3.052236		1.70		0.091	.1372929		10.21668
transportcommun		-3.378128		2.13026		-1.59		0.114	-6.895503		.139248
culturelle		5.153255		2.634975		1.96		0.052	.8025199		9.503989
association		4.157866		2.423506		1.72		0.088	.1562985		8.159434
idf1		-2.658051		2.742871		-0.97		0.333	-7.186939		1.870836
_ cons		17.71709		5.954463		2.98		0.003	7.885392		27.5488

15 .

mardi '( mars '*(+ à ('-'' Page '