Analyzing Drivers’ Distractions due to Smartphone Usage: Evidence from AutoLog Dataset

Table 4

Ordinal Logistic Regression Model for the perception about changing the smartphone interactions to an automatic contextual interface.

Automatic and contextual mode of interaction	Coefficient	Standard error	Z-Value
Exp	−0.949624	0.3103208	−3.06	0.002
Sex	12.3117	5.185264	2.57	0.010
Age	3.11290	1.955462	1.08	0.280
Qualification	5.54612	4.530418	1.00	0.316
Driving-mode	−3.83377	2.334614	−2.07	0.038
Traveling mode	19.5984	9.046204	2.39	0.017
Purpose of travel	4.57517	2.315121	1.54	0.123
Valid license	−2.75837	1.960209	−0.90	0.370
SN1Txt	5.67337	3.337954	2.00	0.046
SN2Txt	4.59828	2.382641	2.77	0.006
SN3Txt	−4.37022	2.185859	−1.54	0.123
SN4Txt	6.46458	3.378782	2.21	0.027
SN5Txt	−12.24350	4.894838	−2.28	0.023
SN6Txt	5.386821	1.979122	2.27	0.023
SN7Txt	5.860908	3.351189	2.08	0.038
SN8PCall	−13.53108	5.295263	−3.10	0.002
SN9PCall	−6.506811	2.111559	−2.18	0.029
SN10PCall	14.71013	6.223496	2.70	0.007
SN11PCall	−4.453164	1.480809	−2.27	0.023
SN1Mail	−10.44832	4.444549	−2.60	0.009
SN2Mail	8.524289	3.6931	2.55	0.011
SN3Mail	4.654765	4.396298	0.85	0.393
SN4Mail	−4.82445	4.444212	−0.89	0.376
SN5Mail	4.610155	2.380717	1.56	0.119
SN6Mail	13.546052	3.431265	3.34	0.001
Visual interface-1	1.15801	1.823014	1.12	0.261
Visual interface-2	4.33807	3.231024	1.00	0.316
Visual interface-3	7.233364	2.518425	3.23	0.001
Visual interface-4	−7.513761	3.553192	−2.42	0.015
Visual interface-5	2.850426	2.449121	0.80	0.423
Visual interface-6	−5.291706	2.012937	−2.63	0.009
Visual interface-7	−1.172993	1.066752	−1.10	0.272
/cut1	125.2839	39.44332
/cut2	152.8744	48.8225
/cut3	170.321	53.83508
No of observations = 59
Wald chi^2(32) = 57.29
Pseudo R^2 = 0.6730
Log pseudolikelihood = −19.236206