Background: Change is inevitable and as supply chain managers prepare for the future they face many challenges. Two major trends over the last few years are the growing importance of ‘big data’ and analysing these data though ‘analytics’. The data contain much value and companies need to capitalise on the variety of data sources by in-depth and proper analysis through the use of ‘big data’ analytics.Objective: This article endeavours to highlight the evolving nature of the supply chain management (SCM) environment, to identify how the two major trends (‘big data’ and analytics) will impact SCM in future, to show the benefits that can be derived if these trends are embraced and to make recommendations to supply chain managers.Method: The importance of extracting value from the huge amounts of data available in the SCM area is stated. ‘Big data’ and analytics are defined and the impact of these in various SCM applications clearly illustrated.Results: It is shown, through examples, how the SCM area can be impacted by these new trends and developments. In these examples ‘big data’ analytics have already been embraced, used and implemented successfully. Big data is a reality and using analytics to extract value from the data has the potential to make a huge impact.Conclusion: It is strongly recommended that supply chain managers take note of these two trends, since better use of ‘big data’ analytics can ensure that they keep abreast with developments and changes which can assist in enhancing business competitiveness.
Background: Freight transport infrastructure is an indispensable requirement for economic growth, development and prosperity. Public–private partnerships (PPPs), as a mechanism to fund and construct freight transport infrastructure, have been suggested by many in private and public sectors.Objectives: The concept of PPPs is dealt with, and the relevance of this mechanism is expanded upon. It is clear that PPPs in the rail environment present huge challenges and complexities. The objective was to determine whether PPPs are a viable mechanism to fund freight transport infrastructure in South Africa.Method: Experiences with rail PPPs worldwide have shown that many failures occurred implementing these. The challenges and complexities of PPPs, in the freight rail environment, are highlighted together with the benefits, risks and best practices of PPPs. It is shown that suitable policies, legislation and regulations concerning PPPs are in place in South Africa.Results: A proper framework and methodology to proceed should be in place. PPPs take time and are complex. Government involvement remains essential. Firm contractual agreements between parties are essential. Risk handling, risk sharing and the magnitude of risks should be clarified with agreement on where the risks reside. Financial viability, with value for money (VfM) and financial benefits for private sector role players are non-negotiable.Conclusion: Appropriate legislation for implementing PPPs must be in place while two further important elements are economic circumstances and proper project execution. Taking all these factors into consideration, the freight transport sector can only benefit from successfully negotiated and implemented PPPs.
General elections are held every five years in South Africa. During the 12 to 24 hour period after the close of the voting booths, the expected final results are of huge interest to the electorate and politicians. In the past, the Council for Scientific and Industrial Research (CSIR) has developed an election forecasting model in order to provide the media and political analysts with forecasts of the final results during this period of peak interest. In formulating this model, which forecasts the election results as the results from voting districts (VDs) become available, some assumptions had to be made. In particular, assumptions were made about the clustering of previous voting patterns as well as the order in which VD results are released. This election forecasting model had been used successfully for a number of elections in the past and in these previous elections, with around 5%-10% of the results available, the predictions produced by the model were very close to the final outcome, particularly for the ANC, being the largest party. For the 2014 national election, however, the predictions, with close to 50% of the voting district results known (equivalent to an estimated 40% of the total votes), were still not accurate and varied by more than 1% for both the ANC and the EFF. This paper outlines a post-election analysis to determine the reasons for these discrepancies and how they relate directly to the model assumptions. The aim is to highlight how practical realities can affect the assumptions and consequently their impact on the forecasted results. Reference is made to previous election forecasts and the 2014 post-election analysis is presented.
Background: At the start of the 20th century a need was identified for a dedicated scholarly journal that would publish research, case studies, new trends, et cetera covering transport, logistics and supply chain management. The Department of Transport and Supply Chain Management of University of Johannesburg launched the Journal of Transport and Supply Chain Management (JTSCM) in 2007.Objectives: The purpose of this study is to determine, through bibliometric analysis, what the impact of the journal is, which is measured over a period of 13 years.Method: The impact of the journal was determined through a variety of quantitative methods. A bibliographic database populated with journal data, was used to visualise co-authorship relationships using the tool, VOSviewer.Results: Over the period 2007 to 2019, a total number of 197 articles were published in the journal. Using Google Scholar, a total of 1987 citations for all the articles published were found. The top 10 articles with the highest number of citations are listed with numbers ranging from 27 to 160 respectively. Tables are presented with the most productive authors, the number of articles by authors from local academic institutions, the private and public sectors as well as the number of articles by international authors. A few co-authorship visualisation maps were produced which shows ‘clusters’ of research teams, networks or communities.Conclusion: The Journal of Transport and Supply Chain Management has made a significant impact over the period analysed as the number of citations and number of abstract and article views attest to.
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