Big data analytics-A review of data-mining models for small and medium enterprises in the transportation sector <s> Background: SMEs Adoption Barriers in Big Data Analytics <s> Big data is big news, and large companies in all sectors are making significant advances in their customer relations, product selection and development and consequent profitability through using this valuable commodity. Small and medium enterprises (SMEs) have proved themselves to be slow adopters of the new technology of big data analytics and are in danger of being left behind. In Europe, SMEs are a vital part of the economy, and the challenges they encounter need to be addressed as a matter of urgency. This paper identifies barriers to SME uptake of big data analytics and recognises their complex challenge to all stakeholders, including national and international policy makers, IT, business management and data science communities. ::: ::: The paper proposes a big data maturity model for SMEs as a first step towards an SME roadmap to data analytics. It considers the ‘state-of-the-art’ of IT with respect to usability and usefulness for SMEs and discusses how SMEs can overcome the barriers preventing them from adopting existing solutions. The paper then considers management perspectives and the role of maturity models in enhancing and structuring the adoption of data analytics in an organisation. The history of total quality management is reviewed to inform the core aspects of implanting a new paradigm. The paper concludes with recommendations to help SMEs develop their big data capability and enable them to continue as the engines of European industrial and business success. Copyright © 2016 John Wiley & Sons, Ltd. <s> BIB001 </s> Big data analytics-A review of data-mining models for small and medium enterprises in the transportation sector <s> Background: SMEs Adoption Barriers in Big Data Analytics <s> This short article reflects upon the task of informing policymaking and investment decisions in times of deep uncertainty, in the face of problems that are more 'wicked' than 'tame' and in the context of ever present biases. <s> BIB002
Aside from the transport and storage sector, the SMEs group are straggling with the implementation of big data analytics in their businesses. This raises an alarm as to what is the hindering factor(s) that is curbing the SMEs from advancing with the evolution of big data technology. In a recent in-depth study by Coleman et al., they uncover several core factors contributing to the slow acceptance of big data analytics by SMEs in the European continent BIB001 . The factors are listed below: (1) Minimal cognizance in the big data analytics domain. (2) Little or no interest in new management trends. (3) Insufficient in-house data analytics experts. (4) Increasing shortage of competent data analyst in the labour market. (5) Lack of exemplary successful case studies for SMEs to refer to. (6) Lack of effective analytics consulting services. BIB002 Highly complex analytics solutions in the software market. (8) Data security concerns. (9) Data protection and privacy concerns. (10) Lack of financial access to invest in new technologies.