Research on the Impact and Utility of Rural Revitalization Big Data Service on Farmers Based on Integrated Technology Acceptance Model
Table 2
Statistical results of latent variables and observable variables in the questionnaire based on the integrated technology acceptance model.
Latent variable name
Observable variable
Performance expectancy (A)
A1: increase rural household income A2: save agricultural production time A3: more efficient access to crop information
Effort expectancy (B)
B1: understand the interaction with the platform B2: big data is convenient and simple to operate
Social influence (C)
C1: agricultural technology promoters recommend big data services C2: big data service recommended by large growers or breeders C3: friends recommend big data services
Facility condition (D)
D1: the network coverage in the area is good D2: big data service quality is high D3: big data services are efficient
Perceived cost (E)
E1: the price of smart phone terminal is high E2: information service subscription price is high E3: the monthly rent is high E4: high traffic cost
Data quality (F)
F1: big data is easy to understand F2: the timeliness of big data is high F3: the reliability of big data is high F4: big data is highly accurate
Behavior intention (G)
G1: plan to use big data services G2: willing to use big data services frequently G3: plan to recommend big data services to other farmers
User behavior (H)
H1: help other farmers use big data services H2: has already started production through big data services
