Spyridon Moulinos

• Αndreas Kanavos, Associate,  Department of Informatics, Ionian University (Supervisor)
• Ampeliotis Dimitrios, Assistant Professor, Department of Digital Media & Communication, Ionian University
• Nikolaos Karapilidis, Professor,  Department of Mechanical Engineering and Aeronautics, University of Patras 

Description

As organizations strive to achieve competitive advantage over their competitors, big data and business analytics now play an increasingly important role in achieving profitability and business performance (H.

Chen, Chiang, & Storey, 2012a). This has signaled an increased interest in the field of using big data and the technologies that accompany it by both researchers and practitioners, especially in recent years, with data now seen as one of the most valuable organizational business resources.

Recent studies have begun to empirically demonstrate the value of big data and business analytics on organizational outcomes such as decision-making agility (Ashrafi, Ravasan, Trkman, & Afshari, 2019), innovation ( Lehrer, Wieneke, vom Brocke, Jung, & Seidel, 2018) and competitive performance (Côrte-Real, Ruivo, & Oliveira, 2019; Mikalef, Krogstie, Pappas, & Pavlou, 2019). However, a recurring finding of these studies is that to derive value from big data, companies need to develop their organizational capacity, identify areas within their business that can benefit from the knowledge and information that data offers that's all. Thus, companies should plan and execute data analysis and clustering projects, with the right architecture so that the data can be a guide for strategic decisions (Gupta & George, 2016; Vidgen, Shaw, & Grant, 2017).

The topic of big data analysis and the effects that the use of business analytics creates on the performance of businesses is something that mainly concerns large companies today. Small and medium-sized enterprises (SMEs) have proven to be slow adopters of new big data analytics technology and risk being left behind. In Europe and especially in Greece, SMEs are a vital part of the economy and the challenges they face must be highlighted. This study will attempt to identify barriers to the adoption of analytics and big data by SMEs on a larger basis.