Empirical Study on Influencing Factors of big data adoption in SME based on TOE theory
Date
2022
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
Abstract
Description
Leading the future development of Information Technology (IT), Big data technology is recognized as a disruptive change in information systems. In the face of the hot big data technology, many large enterprises have already adopted big data technology and benefited from it. SMEs, another main body of the market, which have the functions of creating employment opportunities, promoting economic growth, and improving social benefits, however, have not followed suit. Thus, the factors that SMEs consider when making adoption decisions are the focus of research scholars. However, there is limited research concerning the reasons which SMEs adopt big data analytic technology. To address this gap, the present study employs the technology-organization-environment theory and resource-based view theory to elucidate the influence factor that SMEs, BDA adoption in China. We tested the research hypothesis using primary data collected from 226 questionnaires in Chinese SMEs.This study uses SPSS 19.0 to analyze data, and under the premise of verifying the reliability and validity of the data, multiple linear regression is used to test the correlation between various factors and the willingness to adopt. The results of data analysis show complexity, trialability, and organization have the greatest impact on the adoption intention of SMEs. The second is observability and market disturbance. Market competition, relative advantage, and compatibility have a general influence on SMEs' adoption intention. On the other side, resource readiness, high-level leader support, and government policy have no significant impact on adoption intention. Based on the results, a few suggestions were proposed pertaining to business strategies for SMEs and big data providers. The proposed findings and suggestions offer valuable input for BDA technical adoption researchers in building a more reliable and accurate model.
Detailed description:
goals: 1. What are the factors that influence SMEs in China to adopt BDA?
2. Do the identifying factors play a significant role in the current Chinese SME BDA adoption?
methods : quantitative approach,TOE model,questionnaire.
variables : Relative Advantages (RA), Compatibility (COMP), Complexity (CXTY), Trialability (T), Observability (O), Business Scale (BS),Information Infrastructure (II),Human Resource
(HR),Business Resource (BR), Supports of High-level Leaders (SH), Level of Market Competition (MC), Market Disturbance (MD), Government Policies (GP).
Keywords
Big Data, IT Adoption, Chinese SMEs, Multiple Linear Regression, SPSS