Table 10 Hypotheses tests

From: How generative AI shapes user perceived value and adoption intention in digital museum experiences

H

Paths

β

M

SD

T

P

Results

H1

SR → PV

0.104

0.105

0.05

2.070

0.039

Supported

H2

CA → PV

0.112

0.111

0.052

2.161

0.031

Supported

H3

PU → PV

0.111

0.111

0.051

2.173

0.030

Supported

H4

PE → PV

0.123

0.123

0.057

2.144

0.032

Supported

H5

PN → PV

0.129

0.128

0.051

2.518

0.012

Supported

H6

RA → PV

0.096

0.097

0.044

2.176

0.030

Supported

H7

SP → PV

0.014

0.016

0.053

0.273

0.785

Not supported

H8

HC → PV

-0.015

-0.014

0.053

0.287

0.774

Not supported

H9

CO → PV

-0.122

-0.122

0.049

2.461

0.014

Supported

H10

PR → PV

-0.094

-0.094

0.043

2.194

0.028

Supported

H11

PV → AI

0.864

0.865

0.029

30.040

0.000

Supported

H12

PI x PV → AI

0.462

0.462

0.032

14.396

0.000

Supported

H13

IN x PV → AI

0.340

0.340

0.039

8.729

0.000

Supported

  1. SR semantic relevance, CA contextual adaptability, PU perceived usefulness, PE perceived enjoyment, PN perceived novelty, RA relative advantage, SP service personalization, HC habit change, CO complexity, PR perceived risk, PV perceived value, AI adoption intention, PI perceived innovativeness, IN interactivity.
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