Doctoral Degrees (Logistics)
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- ItemInvestigating marine cargo insurance claims for signs of climate change through the South African fresh fruit export supply chain(Stellenbosch : Stellenbosch University, 2024-03) du Plessis, Francois; Goedhals-Gerber, Leila Louise; van Eeden, Joubert; Stellenbosch University. Faculty of Economic and Management Sciences. Dept. of Logistics.ENGLISH SUMMARY: This dissertation comprises four research articles that collectively explore the intersection of climate change events as a supply chain risk through investigating marine cargo insurance claims, specifically focusing on South Africa. The overarching aim is to gain insight into the impacts of climate-related perils on global supply chains and develop effective risk management strategies. The first article presents a systematic literature review and bibliometric analysis that identifies trends, gaps and limitations in published academic papers on climate change events and fresh fruit export supply chain risks. According to the study, there is insufficient peer-reviewed literature in this area, and a research agenda is proposed for future scientific contributions. The findings underscore the need for the comprehensive understanding and mitigation of risks associated with climate change events and their effect on supply chains. The second article examines the trends, differences and seasonality of weather-related marine cargo insurance claims in South Africa from 2013 to 2022. Through statistical and claims analysis, the research shows a significant increase in weather-related claims over the past decade, resulting in challenges and disruptions to the country’s supply chain network. The study also highlights the higher average values and seasonal patterns of weather-related claims compared to non-weather-related claims. Practical guidelines are provided for supply chain managers and insurers to manage weather-related risks effectively. The third article, based on feedback from a cohort of international participants, delves into understanding the perceptions of marine insurers about their organisation’s involvement in the Supply Chain Risk Management (SCRM) framework for climate change events. The research explores the influence of experience levels and World Bank country income classifications on insurers’ perceptions. The SCRM framework steps show significant variations, indicating different risk management practices within experience groups. Higher country income levels correlate with greater awareness and management of climate change risks. The study emphasises the need for comprehensive involvement in all steps of the SCRM framework to build resilient supply chains. The final article focuses on the interplay between climate change events, South African fruit exports and food safety, providing a comprehensive analysis of fruit damage claims. With the global temperatures witnessing a significant 1.1 °C surge since the pre-industrial times, scrutiny of the vulnerabilities of South Africa’s fruit export sector has increased. This industry contributes over $3 billion to the economy every year. By examining fruit damage claims from 2013 to 2022, the article illuminates distinct categories of claims, highlighting variations driven by elements such as weather patterns. Notably, the research identifies seasonal trends vital for risk mitigation planning. Both Seasonal Autoregressive Integrated Moving Average (SARIMA) and regression analytic models are employed to anticipate future claims. The conclusions drawn highlight the pressing need for tailormade policies, reinforced resilience tactics in maritime supply routes, thorough analysis of different fruit-type vulnerabilities, enriched data gathering, and fortified partnerships with key players. This strategic alignment is crucial to offset potential future damages and to safeguard the prosperity of South Africa’s fruit export sector amid mounting climate adversities. Overall, this dissertation contributes to the growing knowledge of climate change as a supply chain risk. It highlights the urgent need for comprehensive risk management practices and proactive measures to address the increasing frequency and severity of weather-related hazards. The findings offer practical guidelines for supply chain managers, marine insurers and policymakers in mitigating the impacts of climate change on global supply chains, particularly in the context of South Africa. The research also identifies gaps for further investigation and provides a foundation for future scientific contributions in this important study area.
- ItemThe impact of transport accessibility and spatial equity on employment outcomes(Stellenbosch : Stellenbosch University, 2024-03) Van der Merwe, Jacomina Magdalena; Krygsman, Stephan; Woolard, Ingrid, 1970-; Papps, Kerry; Stellenbosch University. Faculty of Economic and Management Sciences. Dept. of Logistics.ENGLISH SUMMARY: Addressing unemployment and income inequalities in transport and land-use policies is important, particularly in South Africa, which is currently experiencing one of the highest unemployment rates and income inequality in the world. South Africa has also seen a rise in the number of discouraged job seekers, which accounted for 14% of the labour force in 2021. These are individuals who want to work but have become too discouraged to actively search for employment. The primary aim of this research is to understand how transport, measured by accessibility and general transport cost components, such as commuting cost and travel time, affects the labour market in South Africa. It highlights the horizontal and vertical spatial equity impacts and the differentiated impact on different income groups. Previous research has proven the impact of a spatial mismatch on the probability of an individual becoming employed and the link between transport accessibility and employment status, but it ignores its impact on an employee’s decision to remain in employment, as well as the decision to stop searching for a job. This research first highlights the unequal distribution of accessibility across space and different income groups in the City of Cape Town. Using unique tax administrative data together with TomTom road network and speeds data, the research shows that the impact of congestion has a greater effect on access to job opportunities for residents of low-income locations compared to those from high-income locations. This reinforces spatial inequality. The research further focuses on the notion of job seekers becoming discourage and the impact of transport cost on their decision not to search for employment. Third, the research provides evidence that longer commuting distances between an employee’s residence and work location reduce employment duration for lower-income employees. The converse it true for higher income individuals. This shows a positive relationship between commuting distance and employment duration. The differentiated impact that transport has on the labour market for different income groups can be incorporated in transport and land-use policy and planning that aim to improve employment and equity outcomes. Last, the impact of land-use policy on accessibility is investigated in a case study, should affordable housing be provided closer to the two main employment hubs in the City of Cape Town. This could address vertical spatial equity, as measured by accessibility to employment in the city.
- ItemDistance-based road user charges as a road cost recovery method : a South African case study(Stellenbosch : Stellenbosch University, 2024-03) van Rensburg, Johann Andre; Krygsman, S. C.; Booysen, M. J.; Stellenbosch University. Faculty of Economic and Management Sciences. Dept. of Logistics.ENGLISH SUMMARY: Transport infrastructure, especially relating to the road sector, is an important pillar to facilitate economic development and growth in any country. Roads, however, are subject to large capital outlays for new construction and upgrades, requiring timely maintenance to ensure transport links that are in a satisfactory condition to meet road user demand, improve accessibility and mobility, and reduce vehicle-operating cost. Despite the background of the infrastructure’s importance, the road sector is continuing to experience funding deficits, meaning that the current financing and funding methods (also known as road cost recovery methods) are unable to meet budgetary requirements. This study argues that distance-based road user charges, using Global Positioning System enabled vehicle tracking devices coupled with a short-run marginal social cost fare structure, could potentially augment the research on road cost recovery for an improved road funding framework given the characteristics of the South African road sector. This hypothesis was tested by assessing i) how the South African road-funding framework currently performs in terms of its ability to secure funding for the road sector. Secondly assessing ii) how it will perform in the future, followed by calculating iii) the correct charges to be levied for road use. Lastly, iv) the public acceptability of road cost recovery methods and v) the operational and economic viability of implementing a distance-based road user charge system in South Africa was assessed. The findings indicate that the South African road funding framework currently collects a large amount of revenue from road users annually, but this is less than what is invested in actual road infrastructure. Compared to select developed countries in terms of how much revenue South Africa collects and spends on road infrastructure as a percentage of Gross Domestic Product, it is definitely not below the norm. The fuel levy, however, although collecting the bulk of the revenue from road users, is becoming increasingly unproductive. It was found that technological and societal trends will have an incremental impact on the future revenue collected from road users in the short to medium term, without necessarily being disruptive. Calculations indicate that the average road user might already be paying more than their fair share of road cost per kilometre of travel and that deriving a short-run marginal social cost fare structure which represents fair and efficient road user charges, as required by the user-pay principle, is by no means an easy endeavour. A public opinion survey indicated that road users in general do not know the amount of costs they pay for using the road network and that they still favour the fuel levy as the main road cost recovery method to be used in South Africa. Simultaneously, they view distance-based road user charges as an acceptable supplementary option. Through a vehicle tracking study, it was determined that a distance-based road user charge system is operationally feasible and economically viable in South Africa and that if implemented with a short-run marginal social cost fare structure could lead to more equitable pricing while possibly increasing the road funding revenue base. It is advised that distance-based road user charges be considered to form part of the current road funding framework in South Africa as a supplementary road cost recovery method. Although there are many issues that should still be addressed, it is an avenue worth considering especially from an equity perspective.
- ItemOrder picking optimisation on a unidirectional cyclical picking line(Stellenbosch : Stellenbosch University, 2020-12) Hofmann, Flora; Visagie, Stephan E.; Stellenbosch University. Faculty of Economic and Management Sciences. Dept. of Logistics. Logistics.ENGLISH SUMMARY : The order picking system in a company's distribution centre is the biggest contributor to the operational cost within the DC. Optimisation should thus aim at running this activity as effciently as possible. The order picking process consists of three main activities, namely walking to the stock, picking stock in fullment of a customer order and handling the picked stock for further processing. While the total amount of work for the picking and handling activities remain constant, the minimisation of walking distance becomes the main objective when minimising the total picking effort. The minimisation of walking distance can be translated into a reduced overall picking time which can lead to a decrease in the total cost of operating the picking system. The main objective of this dissertation is to optimise the order picking system on a unidirectional cyclical picking line. Order batching is introduced to the picking system, since it is an effective methodology that minimises walking distance in operations research literature. Order batching has been introduced to the standard single block parallel-aisle warehouse layout, but not to the specic layout of a unidirectional cyclical picking line. Additionally, the unidirectional cyclical picking line can offer two conguration options that change the physical set up and thereby inffuence the way in which pickers walk during the order picking process. Order batching is introduced to the unidirectional cyclical picking line through picking location based order-to-route closeness metrics. These metrics are further extended by taking the characteristics of the layout into account. The distribution centre of a prominent South African retailer provides real life test instances. Introducing the layout specic stops non-identical spans metric in combination with the greedy smallest entry heuristic results in a reduction of 48:3% in walking distance. Order batching increases the pick density which may lead to higher levels in picker congestion. In a discrete event simulation, the reduction of the overall picking time through a decrease in walking distance is thus conrmed. On tested sample picking waves, the overall picking time can be reduced by up to 21% per wave. A good number of pickers in the picking system is dependent on the pick density. The pick density, amongst other explanatory variables, can also be used to predict the reduction in picking time. The effects of different structural options of the unidirectional cyclical picking line, namely the U- and Z-conguration, are investigated. This results in four decision tiers that have to be addressed while optimising the order picking system. The rst decision tier assigns stock to picking lines, the second arranges stock around a picking line, the third chooses the conguration and the last sequences the orders to be picked. Order batching is added as an additional layer. An increase in pick density benets the reduction of walking distance throughout the decision tiers and supports the choice of the U-conguration after evaluating different test instances. The total completion time of a picking wave can thus be reduced by up to 28% when compared to benchmark instances. The dissertation is concluded by suggesting further research directions.
- ItemApplication of long short-term memory artificial neural networks to forecast water supply and demand in the Lake Chad Basin(Stellenbosch : Stellenbosch University, 2020-12) Fouotsa Manfouo, Noe Careme; Potgieter, Linke; Nel, Johanna H.; Stellenbosch University. Faculty of Economic and Management Sciences. Dept. of Logistics. Logistics.ENGLISH ABSTRACT: The implementation of effective water resources management in developing countries in general and in the Lake Chad Basin in particular, is hindered by the absence of reliable information on both the net water supply, as well as on the agricultural water demand. The main purpose of this research is to provide a methodology to determine and forecast total water supply and water demand in the context of scarce data for water resources management. In order to develop a forecasting methodology, a literature survey is first performed to understand the current environment and methodology of water resources management in the Lake Chad Basin, to highlight the main problems faced within the context, and to identify the opportunity for applied research. As part of this investigation, different stakeholders were visited during a field trip to the Lake Chad Basin. The main water users identified in the Lake Chad Basin do not have historical data on agricultural water demands, making it difficult to understand current water demand requirements or estimate future demand in the Lake Chad Basin. Literature available on the Lake Chad Basin were also considered. A hydrological model was developed in 2011 by Bader, Lemoalle, and Leblanc and reported on in the paper Modèle hydrologique du Lac Tchad [16]. The model provides information on the lake storage for the period 1956 to 2011, however, it does not consider upstream diversion. Therefore, the output of the model does not allow an exhaustive estimation of water supply in the Lake Chad Basin. In addition, the model is data intensive and uses variables that are neither easy to obtain, nor straightforward to compute, and requires expert hydrological knowledge to extend the use of the model for future water supply estimation beyond 2011. Moreover, there are currently no model developed for estimating water demand in the Lake Chad Basin. Long short-term memory is an artificial recurrent neural network that have been shown to perform exceptionally well in the context of time series forecasting, due to its ability to incorporate lags of unknown duration in the network structure. Despite the good track record of this methodology in forecasting time series, it is not widely used in the literature for water supply and demand estimation. In this dissertation, multivariate time series forecasting with long short-term memory is investigated as an alternative methodology for different aspects of water supply and demand estimation. Pearson correlation, random forest, extra trees classifiers and principal component analysis are investigated as input selection approaches to increase prediction accuracy. For water supply estimation, a lake storage forecasting model as well as a streamflow forecasting model are developed. Results indicate that long short-term memory can be used to predict Lake Chad Basin storage, with better performances than the state of the art results, obtained from artificial neural networks and support vector regression. The multivariate approach indicates that atmospheric data are both good and easily obtainable data for lake storage forecasting. The input variables, selected with both the principal component analysis and random forest approach are recommended for streamflow forecasting in the Lake Chad Basin. Random forest occupies the second position, by producing better predictions in the Ndjamena gauging station. A long-term temperature forecasting model as well as a precipitation forecasting model were developed and the outputs were used as input in the CROPWAT software to determine the irrigation water requirement per hectare per crop type. A comparison between the widely used statistical downscaling model and the forecasting models for long-term temperatures and precipitations developed in this research indicate better accuracy using the multivariate long short-term memory approach. Both the root mean square error and the mean absolute percentage error used to check the performances of the models indicate commendable accuracy. Four population dynamics models, namely the malthusian growth model; the logistic growth models with both constant and dynamic rates, as well a logistic growth model with dynamic rate and species interaction, are developed to estimate the size of land used for both crop and livestock, and to finally predict the total agricultural water demand in the Lake Chad Basin. The models are parameterised using long short-term memory. A case by case investigation of prediction performances across the three countries indicates that the malthusian growth approach produces better performances in 9 cases, the logistic growth model with constant rate performs better in 4 cases, and the logistic growth model with dynamic rate performs better in 7 cases. The malthusian approach is more suitable for variables with unstable trends, the logistic model with constant rate is more suitable for variables with almost concave or convex shapes and the logistic growth with dynamic rate is the most useful long-term crop land-use and livestock population forecasting. Finally, the best performing models for crop land-use and livestock population are downscaled to main water users level, in order to estimate total water demand per crop type and per livestock type. The investigation of the four population dynamics models, on both the crop land-use and livestock population dynamics, the characterisation of the competition type between species in the Lake Chad Basin case study as well as the estimation of water demand at water users’ level is a new contribution to literature.