The need for small and medium enterprises (SMEs) to adopt data analytics has reached a critical point, given the surge of data implied by the advancement of technology. Despite data mining (DM) being widely used in the transportation sector, it is staggering to note that there are minimal research case studies being done on the application of DM by SMEs, specifically in the transportation sector. From the extensive review conducted, the three most common DM models used by large enterprises in the transportation sector are identified, namely “Knowledge Discovery in Database,” “Sample, Explore, Modify, Model and Assess” (SEMMA), and “CRoss Industry Standard Process for Data Mining” (CRISP‐DM). The same finding was revealed in the SMEs' context across the various industries. It was also uncovered that among the three models, CRISP‐DM had been widely applied commercially. However, despite CRISP‐DM being the de facto DM model in practice, a study carried out to assess the strengths and weakness of the models reveals that they have several limitations with respect to SMEs. This paper concludes that there is a critical need for a novel model to be developed in order to cater to the SMEs' prerequisite, especially so in the transportation sector context. This article is categorized under: Application Areas > Business and Industry Application Areas > Industry Specific Applications

A core subfield of knowledge management (KM) and data mining (DM) constitutes an integral part of the knowledge discovery in database process. With the explosion of information in the new digital age, research studies in the DM and KM continue to heighten up in the business organisations, especially so, for the small and medium enterprises (SMEs). DM is crucial in supporting the KM application as it processes the data to useful knowledge and KM role next, is to manage these knowledge assets within the organisation systematically. At the comprehensive appraisal of the large enterprise in the transportation sector and the SMEs across various industries-it was gathered that there is limited research case study conducted on the application of DM-KM on the transportation SMEs in specific. From the extensive review of the case studies, it was uncovered that majority of the organisations are not leveraging on the use of tacit knowledge and that the SMEs are adopting a more traditional use of ICTs to its KM approach. In addition, despite DM-KM is being widely implemented-the case studies analysis reveals that there is a limitation in the presence of an integrated DM-KM assessment to evaluate the outcome of the DM-KM application. This paper concludes that there is a critical need for a novel DM-KM assessment plan template to evaluate and ensure that the knowledge created and implemented are usable and relevant, specifically for the SMEs in the transportation sector. Therefore, this research paper aims to carry out an in-depth review

The advancement of technology and emergence of internet of things (IoT) has exponentially caused a data explosion in the 21st century era. As such, the arrival of IoT is set to revolutionize the development of the small and medium-sized enterprise (SME) organizations by shaping it into a more universal and integrated ecosystem. Despite evidential studies of the potential of advanced technologies for businesses, the SMEs are apprehensive towards new technologies adoption such as big data analytics and IoT. Therefore, the aim of this chapter is to provide a holistic study of big data and IoT opportunities, challenges, and applications within the SMEs context. The authors hope that the outcome of this study would provide foundational information on how the SMEs can partake with the new wave technological advancement and in turn, spurring more SMEs for adoption.

Abstract.Coaches are considered to be one of the safest modes of transport for children in the UK. In the last 10 years alone, 1191 children were injured in 371 coach crashes. Though the government has strict regulations to maintain road worthiness of the coaches, operator non-compliance was the major reason for these accidents. In last year alone, 137 coach operator licenses have been revoked due to operator non-compliance in the UK. Currently, there is no process to reliably mitigate the safety risks of children travelling by coaches. This has created a requirement to validate all the coach operators before using their coaches for school trips. This paper proposes a novel safety model for validation of coach operators prior to commencement of coach journeys.

E-commerce has proven to play a pivotal role in the economy growth. One of the key e-commerce functions is the collection of the vast amount of useful transactional data to help businesses in understanding their consumers' behaviour. With the rapid and large volume of data collected, it is posing a great challenge for businesses to analyse the data on a day-to-day basis. The key issue is not in the generation or collection of data; it is in the manipulation of the collected data to churn out new and insightful information. Information visualisation is an effective tool in converting data into interactive interfaces to unearth hidden trends. It provides a platform to explore the data in a more rapid and intuitive approach. There are several existing techniques to analyse multidimensional data. This chapter seeks to introduce a comprehensive and robust visualisation model and framework for adoption. The visualisation model consists of four major layers, which include acquisition and data analysis, data representation, user and computer interaction, and result storage.