Big data analytics: does organizational factor matters impact technology acceptance?

被引：43
作者：
Brock V. [1 ]
Khan H.U. [2 ]
机构：
[1] Department of Computer Science, University of Liverpool, Liverpool
[2] Department of Accounting and Information Systems, Qatar University, Doha
来源：
Journal of Big Data | 2017年 / 4卷 / 01期
关键词：
Big data; Mediation effect; Organizational learning capabilities (OLC); Structural equation model (SEM); Technology acceptance model (TAM);
D O I：
10.1186/s40537-017-0081-8
中图分类号：
学科分类号：
摘要：
Ever since the emergence of big data concept, researchers have started applying the concept to various fields and tried to assess the level of acceptance of it with renown models like technology acceptance model (TAM) and it variations. In this regard, this paper tries to look at the factors that associated with the usage of big data analytics, by synchronizing TAM with organizational learning capabilities (OLC) framework. These models are applied on the construct, intended usage of big data and also the mediation effect of the OLC constructs is assessed. The data for the study is collected from the students pertaining to information technology disciplines at University of Liverpool, online programme. Though, invitation to participate e-mails are sent to 1035 students, only 359 members responded back with filled questionnaires. This study uses structural equation modelling and multivariate regression using ordinary least squares estimation to test the proposed hypotheses using the latest statistical software R. It is proved from the analysis that compared to other models, model 4 (which is constructed by using the constructs of OLC and TAM frameworks) is able to explain 44% variation in the usage pattern of big data. In addition to this, the mediation test performed revealed that the interaction between OLC dimensions and TAM dimensions on intended usage of big data has no mediation effect. Thus, this work provided inputs to the research community to look into the relation between the constructs of OLC framework and the selection of big data technology. © 2017, The Author(s).
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