Presenting a model of cloud business intelligence in industrial SMEs: Meta-synthesis and interpretive structural modelling approaches

• Published in: Technology analysis & strategic management Vol. 36; no. 4; pp. 779 - 796
• Main Authors: Hamidinava, Fatemeh, Ebrahimy, Abdolhamid, Samiee, Roohallah, Didehkhani, Hosein
• Format: Journal Article
• Language: English
• Published: Abingdon Routledge 02-04-2024; Taylor & Francis Ltd
• Subjects: Cloud Business Intelligence (Cloud BI); Cost analysis; Data analysis; Decision analysis; Fuzzy Delphi method (FDM); Information management; Intelligence; Intelligence (information); Meta-Synthesis-Interpretive Structural Modelling (ISM); Modelling; Scripts; SMEs; Step-wise Weight Assessment Ratio Analysis (SWARA); Synthesis
• ISSN: 0953-7325; 1465-3990
• DOI: 10.1080/09537325.2022.2060071

One of the essential tools for predicting the business environment and analysis and timely and low-cost decisions for SMEs is cloud business intelligence. This research paper aims to present a model of cloud business intelligence for SMEs.In the current study, the Meta-synthesis method has been utilised to identify the fundamental categories of cloud business intelligence. The model is presented by exploiting the interpretive structural modelling. In this regard, the data analysis process has been performed by MATLAB and MicMac software. Consequently, presented Six main factors; 24 sub-factors were obtained from the extracted parameters of relevant researches scripts. It is evident that 'Drivers' is the most influential variable of the model. They then used SWARA to rank the sub-Factors.