In recent years South Africa has experienced numerous service delivery protests. These protests are a result of the lack of delivery of basic services such as water and sanitation (amongst others). To address this, local governments have taken part in benchmarking initiatives (National Benchmarking Initiative, Municipal Benchmarking Initiative) and regulation programmes (BlueDrop,GreenDrop) in an effort to improve the quality of potable water and sanitation services. The latter of these focuses on the quality of the water services delivered and neither focus on the efficiency with which this delivery is achieved. This study uses both nonparametric (data envelopment analysis) aswell as parametric (stochastic frontier) methods to assess the efficiency of water service provision in South Africa over a six year period from 2005 to 2010. Subsequently, the method which is most suited for use in the South African context is proposed. In addition, this study demonstrates how these methods can be used to determine the effectiveness of benchmarking initiatives, namely the National Benchmarking Initiative, in improving the efficiency of water service provision. Furthermore, additional insight into the selection ofm in them out of n bootstrap procedure for efficiency evaluations is established through a simulation study. The inclusion of efficiency evaluations into South African benchmarking initiatives provides new and important insight into the standard of water service delivery. As such, the techniques used in this study illustrate how efficiency analysis can enhance benchmarking initiatives in South Africa.

M.A. (Development Studies) / This study examines water service provision models in KwaZulu-Natal and asks to what extent the intention behind the implementation of a specific model of water service provision correlates with residents’ experiences of the service delivery model that is implemented within their township? Using a case study method this question was examined in two poor communities in the KwaZulu-Natal province of South Africa that were characterised by different models of water service delivery. In the first case, namely Kwadukuza, municipal service provision is the operating model, whilst in the second case, Etete, a Public-Private Partnership governs water service delivery. In examining the different models of water service delivery in the two communities and how they are perceived and experienced by stakeholders, this research primarily expands on existing literature on water service provision within South Africa. It furthermore contributes to broader discussions on decentralisation and citizen participation, whilst building on scholarly debates on water privatisation and partnerships in the context of townships in South Africa. The study begins with a consideration of relevant literature, examining the growing impetus of decentralisation globally, as well as the concurrent emergence of neoliberal thinking and New Public Management strategies. Thereafter, debates on water privatisation are explored, before moving on to a consideration of the policy and practice of water provision in the South African context. At this juncture, the study draws on in-depth interviews as it considers the two models of water service provision within the Ilembe District Municipality – the factors that influenced their implementation and, thereafter, the relationships between and experiences of stakeholders (both implementers and beneficiaries alike) of the service delivery model that operates within their municipality. The study submits that the proposed benefits of decentralisation in the South African context are questionable, specifically as they relate to the delivery of services to the poorest of the poor. It is argued that this is owing considerably to inadequacies at the level of local government. In this respect, it is suggested that existing participatory mechanisms are falling short of the mark. In light of this, the study advances the manifold advantages of multiple stakeholders and partnership arrangements for service delivery models in the South African context. At its core, the study highlights residents’ experiences of water service delivery into their townships in an attempt to measure these against other reported experiences.

This master thesis describes and proves how companies can improve their operational performance and supplier relationships by using modern collaborative and planning practices, specifically the Collaborative Planning Forecasting and Replenishment (CPFR) concept. The theoretical part depicts main developments in supply chain planning over time, shows common challenges in the world of supply chain and offers possible solutions in terms of collaborative supply chain planning practices. The practical part analyzes the CPFR process between one of the leading providers of telecommunications services T-Mobile and its major mobile handset supplier Nokia. The concluding part defines gaps between an ideal to-be process of supply chain collaboration and the status quo process. Status quo benefits of current CPFR processes are described as well.

PhDRDV / Institute for Rural Development / Potable water supply is a fundamental human right and protected by international conventions and national laws. Access to it and having in place an appropriate water supply system remain the building blocks to improving and maintaining the welfare of any community for it to enjoy a healthy and productive life. The supply of potable water, especially in Africa's rural areas, however, remains a challenge. The demand for a system to provide sustainable water supply has been on the increase due to population growth and the climate change phenomenon. Vhembe District Municipality (VDM), as the responsible authority for water supply in sections of the Limpopo Province, faces many challenges, including - aging water supply infrastructure, lack of capacity of officials, and lack of funds for maintenance; these often lead to a breakdown of the supply system. This challenge results, for example, in increased health hazards that often cause tension between the District and the residents. The study’s main objective was to investigate the water supply system in Vhembe so as to suggest an effective intervention strategy for potable rural water supply system to improve the supply in the Vhembe District Municipality of the Limpopo Province. The specific objectives were - to determine the current potable water supply sources in rural communities of the VDM, examine the system’s ability to meet the needs of the rural communities in VDM and to identify the challenges and coping strategies used to meet potable water supply in VDM. A mixed-method, of both qualitative and quantitative research designs and techniques, was adopted and focus group discussions and in-depth interviews were used to gather data. From the four local municipalities of VDM, 14 wards were purposively selected through proportional representation of 448 households, which were randomly selected. Three municipal officials responsible for the water supply system in the VDM were selected through census. Key-informant discussions were held with councillors from the 14 wards, with focus group discussions used to engage the 448 households, and traditional leaders. Thematic content analysis was used to identify common themes, ideas, and patterns of meaning that came up frequently from qualitative data. The IBM Statistical Package for the Social Science (SPSS) version 25 was used to analyse data using descriptive statistics, one way ANOVA and Chi-Square test.The results revealed that in Vhembe District Municipality, the primary sources of water were boreholes (45.3%) followed by piped water from the dams (35.3%). The majority of the households (53.6%) obtain water from boreholes once per week, with 4% resorting to obtaining water from rivers, 5.4% obtained water from fountains and 10% obtained their water from Municipality water tankers (truck tankers). These results indicate that the District continues to face challeges in its efforts to fulfill its mandate as the responsible authority for water supply, in the rural communities due to lack of a sustainable system to supply the required minimum water needs for households. The study recommended that all stakeholders should join hands to invest in a system that has more water supply options to sustainably meet the needs of the growing population. The system should have management ii structures relevant for villages, as critical pillars to assist - with the management system, address minor maintenance requirements, and monitor and report any water supply system-related issues. It was also suggested that rural communities be encouraged to pay for water supply services, for the system's sustainability and that the system in VDM would be improved when stakeholders (communities, government, and NGOs) come together. / NRF

Oliver Tambo Institute of Governance and Policy Studies / MPM

Thesis (MPAM.) -- University of Limpopo, 2021 / The South African government introduced the Supply Chain Management Framework in 2003, with a vision of creating a seamless system intended to play a critical role in service delivery to communities while achieving the objectives of cost-effectiveness, fairness, equity, transparency and ethics. This study focused on the impact of Supply Chain Management Policy Implementation in the Limpopo Office of the Premier. Qualitative data were collected, primarily in the form of semi-structured interviews using an interview schedule consisting of both closed and open-ended questions with the Chief Financial Officer, Director (SCM), Deputy Directors (Demand, Acquisition, Logistics and Inventory, Asset and Transport Management) and SCM nineteen SCM practitioners. These officials provided sufficient information concerning the effect of Supply Chain Management policy implementation in the Limpopo Office of the Premier. The study established that failure to implement SCM policy hurts service delivery. The effective implementation results in improved service delivery, whereas poor implementation results in the poor quality of service to the public, fraud and corruption, irregular and fruitless expenditures as well as negative departmental image.

Modern supply chains are often characterized by carefully planned and interconnected processes that seamlessly integrate with each other. Supply chains are often efficientduring a stable business environment but are highly vulnerable to risks and disruptions.When any link in the supply chain is negatively impacted, challenges can arise for all the companies in the supply chain. This has expanded the goal of supply chain management tocreate resilient supply chains that incorporate event readiness, provide efficient and effective responses, and can return to their original state after a disruption. During Covid19 businesses all over the world were affected and the pandemic led to disruptions in supply chains. Small and medium-sized enterprises (SME) were especially affected because of lack in financial resources, technical capabilities, and low resilience. SMEs play a crucial role in the global economy but there is still a limited amount of research onhow SME can achieve resilience in their supply chains. Furthermore, there is a lack ofresearch comparing changes in supply chain resilience before and after Covid-19. To address this research gap, the purpose of the study is to explore how Covid-19 affected the supply chain resilience in Swedish SMEs. To understand the effects of Covid-19 we will examine supply chain resilience in SMEs before, during and after the pandemic. To address our purpose, we have conducted a qualitative study using an inductive approach and exploratory research design. We collected primary data from semi-structuredinterviews with nine managers from manufacturing Swedish SMEs. The data gathered through the interviews was analysed by using a thematic analysis that led us to our findings. Our findings revealed that prior to the pandemic, risk awareness was not a top priority for the respondent companies. However, Covid-19 exposed vulnerabilities in their supply chains highlighting the importance of both proactive and reactive strategies. Swedish SMEs experienced various challenges including transportation problems, component shortages and fluctuations in customer demand. Tomeet these challenges, the companies showed flexibility by changes in product assemblingand increased inventory levels during Covid-19. Furthermore, strengthened communication with suppliers and customers played a significant role in increasing supply chain visibility and collaboration. As a result of the Covid-19 disruption, our study show that the responding companies have become more aware of risks and incorporated practices into in their operations as adoption of alternative suppliers, optimization of safety stocks and improved communication. Overall, the findings suggested that the pandemic prompted the respondent SMEs to strengthen their supply chain resilience. By learning from the impact of the crisis, these companies have become more resilient and created supply chains that can better withstand future disruptions. This study contributes to understanding how supply chain resilience in Swedish SMEs was affected by Covid-19 and how SMEs can enhance their supply chain resilience

Background: COVID-19 pandemic had a vast and significant impact on today’s societies, in terms of economic, societal, and even environmental aspects. Global supply chains had to adapt to this changing landscape rapidly. Both supply and demand witnessed repercussions. The effects of COVID-19 on supply chains have been evident, with lockdowns and inconsistent supply and demand causing issues for international trade. Indeed, many companies were constrained to stop supply and production and could not deliver their goods.   Purpose: This study aims to investigate the impact of the COVID-19 pandemic on transportation operations in logistics companies, more precisely by using the case of DHL to emphasize our study. The purpose is to analyze the impacts that the crisis had on Logistics operations, by focusing on DHL and the way the company was impacted, understood and overcame the disruption. This study will take into consideration economic, social and environmental aspects.   Method: The research will be based on a case study and empirical evidence to provide a comprehensive understanding of the impact of the COVID-19 pandemic on DHL’s supply chain operations and more precisely on logistics and transport. We used the Triple Bottom Line approach to measure the economic, social, and environmental performances of DHL. Further, the analysis used in this paper is an inductive thematic analysis, to emphasize the findings and provide a better accuracy to our results.   Results: The study aims to identify the effects that COVID-19 had on logistics operations, and it more particularly seeks to highlight the strategies used by logistics companies that could be useful for other companies that need to build more resilient and flexible supply chains in the face of future disruptions. The findings of this thesis will be valuable to businesses, supply chain managers, and policymakers seeking to understand the role of improving their supply chains. Thanks to the interviews that were conducted, the findings highlighted several strategies that have been implemented by companies, such as the acceleration in automation, efforts put towards employee conditions, and restructuring companies.

M. Tech. (Department of Logistics Management, Faculty of Management Sciences), Vaal University of Technology. / The successful implementation of supply chain strategy has received significant attention among literature and practitioners, due to its importance in contributing to company success. The success of the FMCG industry in South Africa has also been attributed to the effectiveness of its supply chain strategies. However, the industry faces numerous challenges such as miscellaneous risks that include the potential loss of key suppliers, innovation, and risk, planning and forecasting, power outages in manufacturing plants and the fact that only a limited amount of safety stock can be held to offset uncertainty. It also faces difficulties in improving supply and demand, which further extends to transforming supplier relationships into effective collaboration. Thus, this study applies supply chain strategy to the FMCG industry in South Africa, and seeks to establish the connection between supply chain strategies, flexibility (SCF) and performance (SCP) in the sector. The methodological procedure in this study was guided by the positivist paradigm which is embedded in quantitative and causal designs. A sample of 228 respondents purposively drawn from the FMCG industry in Gauteng province participated in the survey. The collected data were tested using descriptive and inferential statistics. The specific statistical techniques applied included the analysis of frequency distributions, percentages, mean scores, exploratory factor analysis (EFA), confirmatory factor analysis (CFA) and hypotheses tests using partial least squares-based structural equation modelling. The empirical results showed that two supply chain strategies, namely, organisational learning and supplier integration contribute significantly to SCF. In turn, SCF contributes positively to financial and non-financial performance. Supply chain strategies such as innovation, risk management and customer orientation were statistically insignificant in predicting SCP. The study is significant because it identifies that supply chain strategies are important in developing flexible FMCG supply chains in South Africa. It also confirms the importance of SCF in improving the performance of FMCG supply chains. The study may therefore be used as a reference source for information on the improvement of SCP in FMCG supply chains.

In the era of Industry 4.0, conventional supply chains are undergoing a transformation into digital supply chains with the wide application of digital technologies such as big data, cloud computing, and Internet of Things. A digital supply chain is an intelligent and value-driven process that has superior features such as speed, flexibility, transparency, and real-time inventory monitoring and management. This concept is further included in the framework of Supply Chain 4.0, which emphasizes the connection between supply chain and Industry 4.0. In this context, data analytics for supply chain management presents a promising research opportunity. This thesis aims to investigate the use of data analytics in supply chain decision-making, including modelling, monitoring, and optimization. First, this thesis investigates supply chain monitoring (SCMo) using data analytics. The goal of SCMo is to raise an alarm when abnormal supply chain events occur and identify the potential reason. We propose a framework of SCMo based on a data-driven method, principal component analysis (PCA). Within this framework, supply chain data such as inventory levels and customer demand are collected, and the normal operating conditions of a supply chain are characterized using PCA. Fault detection and diagnosis are implemented by examining the monitoring statistics and variable contributions. A supply chain simulation model is developed to carry out the case studies. The results show that dynamic PCA (DPCA) successfully detected abnormal behaviour of the supply chain, such as transportation delay, low production rate, and supply shortage. Moreover, the contribution plot is shown to be effective in interpreting the abnormality and identify the fault-related variables. The method of using data-driven methods for SCMo is named data-driven SCMo in this work. Then, a further investigation of data-driven SCMo based on another statistical process monitoring method, canonical variate analysis (CVA), is conducted. CVA utilizes the state-space model of a system and determines the canonical states by maximizing the correlation between the combination of past system outputs and inputs and the combination of future outputs. A state-space model of supply chain is developed, which forms the basis of applying CVA to detect supply chain faults. The performance of CVA and PCA are assessed and compared in terms of dimensionality reduction, false alarm rate, missed detection rate, and detection delay. Case studies show that CVA identifies a smaller system order than PCA and achieves comparable performance to PCA in a lower-dimensional latent space. Next, we investigate data-driven supply chain control under uncertainty with risk taken into account. The method under investigation is reinforcement learning (RL). Within the RL framework, an agent learns an optimal policy that maps the state to action during the process of interacting with the non-deterministic environment, such that a numerical reward is maximized. The current literature regarding supply chain control focuses on conventional RL that maximizes the expected return. However, this may be not the best option for risk-averse decision makers. In this work, we explore the use of safe RL, which takes into account the concept of risk in the learning process. Two safe RL algorithms, Q-hat-learning and Beta-pessimistic Q-learning, are investigated. Case studies are carried out based on the supply chain simulator developed using agent-based modelling. Results show that Q-learning has the best performance under normal scenarios, while safe RL algorithms perform better under abnormal scenarios and are more robust to changes in the environment. Moreover, we find that the benefits of safe RL are more pronounced in a closed-loop supply chain. Finally, we investigate real-time supply chain optimization. The operational optimization problems for supply chains of realistic size are often large and complex, and solving them in real time can be challenging. This work aims to address the problem by using a deep learning-based model predictive control (MPC) technique. The MPC problem for supply chain operation is formulated based on the state space model of a supply chain, and the optimal state-input pairs are precomputed in the offline phase. Then, a deep neural network is built to map the state to input, which is then used in the online phase to reduce solution time. We propose an approach to implement the deep learning-based MPC method when there are delayed terms in the system, and a heuristic approach to feasibility recovery for mixed-integer MPC, with binary decision variables taken into account. Case studies show that compared with solving the nominal MPC problem online, deep learning-based MPC can provide near-optimal solution at a lower computational cost. / Thesis / Doctor of Philosophy (PhD)