The Influence of Big Data Analytics on E-Commerce: Case Study of the U.S. and China
Table 21
Lag order selection criteria.
Variable
Lag
Log
LR
FPE
AIC
SC
HQ
Lag order selection
Observed object
X02
0
-162.121
NA
27223.100
13.050
13.098
13.063
U.S.
1
-139.237
42.107
4728.674
11.299
11.396
11.326
◯
2
-138.811
0.749
4955.199
11.345
11.491
11.385
3
-138.625
0.313
5297.007
11.410
11.605
11.464
X69
0
-121.768
NA
1078.827
9.821
9.870
9.835
1
-108.126
25.101
392.517
8.810
8.908
8.837
2
-103.429
8.267
292.255
8.514
8.661
8.555
◯
3
-103.429
0.000
317.104
8.594
8.789
8.648
X04
0
-175.910
NA
82037.320
14.153
14.202
14.166
China
1
-130.324
83.878
2317.735
10.586
10.683
10.613
◯
2
-130.303
0.036
2508.760
10.664
10.811
10.705
3
-130.278
0.043
2716.554
10.742
10.937
10.796
X70
0
-83.390
NA
50.069
6.751
6.800
6.765
1
-73.001
19.117
23.630
6.000
6.098
6.027
2
-71.283
3.022
22.330
5.943
6.089
5.983
◯
3
-70.835
0.753
23.376
5.987
6.182
6.041
indicates lag order selected by the criterion. LR: sequential modified LR test statistic (each test at 5% level). FPE: final prediction error; AIC: Akaike information criterion; SC: Schwarz information criterion; HQ: Hannan-Quinn information criterion. Sample: 1990-2017. X02: searching subject term “E-Commerce” in the WoS (Core Collection). X04: searching subject term “E-Commerce” in CNKI (periodical). X69: searching subject term “Quantum Computing” in the WoS (Core Collection). X70: searching subject term “Quantum Computing” in CNKI (periodical).
