Big data analytics-A review of data-mining models for small and medium enterprises in the transportation sector <s> Supplemental Intangible Barriers <s> Argues that the way in which the UK Government, through its various departments and quangos, approaches designed to approve the effectiveness of the small business sector, is based on a flawed understanding of how small businesses actually operate. Argues that this naive, over‐simplistic understanding of the motivation of those in the small business sector means that many government interventions that are made, are blunt instruments destined to fail, given the limited understanding shown of the complexity of the small business market. Presents evidence from two recent studies amongst small firms; a series of large‐scale qualitative studies undertaken for a blue chip company and a mixed study on the Business Link network. The emphasis is based on – using qualitative research – getting to grips with the emotion, ambiguity and complexity that characterises this market. <s> BIB001 </s> Big data analytics-A review of data-mining models for small and medium enterprises in the transportation sector <s> Supplemental Intangible Barriers <s> Big data, the authors write, is far more powerful than the analytics of the past. Executives can measure and therefore manage more precisely than ever before. They can make better predictions and smarter decisions. They can target more-effective interventions in areas that so far have been dominated by gut and intuition rather than by data and rigor. The differences between big data and analytics are a matter of volume, velocity, and variety: More data now cross the internet every second than were stored in the entire internet 20 years ago. Nearly real-time information makes it possible for a company to be much more agile than its competitors. And that information can come from social networks, images, sensors, the web, or other unstructured sources. The managerial challenges, however, are very real. Senior decision makers have to learn to ask the right questions and embrace evidence-based decision making. Organizations must hire scientists who can find patterns in very large data sets and translate them into useful business information. IT departments have to work hard to integrate all the relevant internal and external sources of data. The authors offer two success stories to illustrate how companies are using big data: PASSUR Aerospace enables airlines to match their actual and estimated arrival times. Sears Holdings directly analyzes its incoming store data to make promotions much more precise and faster. <s> BIB002
In addition to the discussions in respect of adoption barriers in Sections 1 and 1.1, it is worth considering the supplemental intangible barriers that may also hinder the adoption of analytics for SMEs. These intangible barriers relate to SME's organisational culture, organisation structure and decision-making. First and foremost, in terms of organisational culture -given that SMEs are highly domain-specialised, they have little or no interest in new management trends that might be beneficial for the organisation  . This culture of intrinsic conservatism is leading the SME's attitude in taking big data analytics as a management hype instead of an opportunistic viewpoint. The second aspect of organisational structure implies the need to have a fitting management concept within an organisation, in order to create an economic success on the adoption of analytics BIB002 . Unlike the large enterprise, the organisational structures of most SMEs are flat with few or no levels of middle management between the executives and staffs  . The flat organisational structure of SMEs would in turn impact; on the way the organisation makes it decisions. The decision makers in SMEs are often the business owners, which are in a way usually tied up with the owner's identity and life  . The decision making within the large enterprise tends to be more rational because of the complexity of the organisation structure and decision making units BIB001 . In view of the scarcity of resources and expertise, SMEs would be in a limiting position to make a complex decision, as it is often reliant on the business owner's intuition BIB001 . In other words, if the business owner is not personally attuned with the latest business trends of analytic adoption, it will be an intricate barrier to overcome.