표 3 분석 결과

변수 구간별 분석: 구간 1 구간별 분석: 구간 2 구간 통합 분석: 교차항X 구간 통합 분석: 교차항O
설명변수 (Intercept) –7.351 (1.879)** –6.323 (1.558)** –6.728 (1.177)** –6.657 (1.177)**
WeeklySpendingi .360 (.147)** .315 (.123)** .338 (.093)** .337 (.093)**
CommerceRatioi .007 (.007) .008 (.007) .007 (.005) .007 (.005)
PlatformRatioi .048 (.018)** .034 (.012)** .039 (.010)** .040 (.010)**
DigitalRatioi –.025 (.081) .003 (.035) –.001 (.031) –.002 (.032)
LeisureRatioi –.057 (.073) .063 (.032)** .032 (.028) –.065 (.073)
통제변수 DeliveryRatioi .058 (.022)** .006 (.017) .025 (.013)* .025 (.013)*
DiningRatioi .008 (.043) .008 (.022) .011 (.019) .011 (.019)
I(Birthi=1) .457 (.398) .260 (.286) .345 (.230) .355 (.230)
I(Birthi=2) 1.196 (.460)** .782 (.353)** .975 (.276)** .977 (.277)**
I(Marriedi=1) –.055 (.299) .045 (.226) –.001 (.179) .008 (.179)
I(HouseNoi=1) .295 (.286) –.268 (.208) –.043 (.166) –.059 (.166)
I(Incomei=1) –.244 (.285) –.271 (.233) –.282 (.178) –.286 (.179)
I(Incomei=2) .003 (.264) –.075 (.218) –.055 (.167) –.063 (.167)
I(ComTimei=1) –.177 (.259) –.251 (.203) –.234 (.159) –.227 (.159)
I(ComTimei=2) –.116 (.350) –.387 (.306) –.265 (.227) –.264 (.227)
I(ComCari=1) .202 (.320) .327 (.270) .288 (.204) .288 (.204)
I(SocialMediai=1) .023 (.286) .230 (.258) .146 (.189) .145 (.190)
I(RetailPayi=1) .152 (.376) –.199 (.355) –.043 (.256) –.042 (.255)
I(OnlinePayi=1) –.426 (.345) –.426 (.334) –.417 (.238)* –.423 (.238)*
AfterCovidi –.102 (.135) –.197 (.145)
LeisureRatioi ×AfterCovidi .128 (.079)
※ 회귀 분석의 회귀계수를 나타낸 표이며, 괄호 안은 회귀계수에 대한 표준 오차를 나타냄.
p < .05,
p < .1
회귀계수의 유의성에 대한 가설검정의 p값이 .104임.