Browsing by Author "Scott, Leanne"
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- ItemOpen AccessAgent-based model of the market penetration of a new product(2014) Magadla, Thandulwazi; Durbach, Ian; Scott, LeanneThis dissertation presents an agent-based model that is used to investigate the market penetration of a new product within a competitive market. The market consists of consumers that belong to social network that serves as a substrate over which consumers exchange positive and negative word-of-mouth communication about the products that they use. Market dynamics are influenced by factors such as product quality; the level of satisfaction that consumers derive from using the products in the market; switching constraints that make it difficult for consumers to switch between products; the word-of-mouth that consumers exchange and the structure of the social network that consumers belong to. Various scenarios are simulated in order to investigate the effect of these factors on the market penetration of a new product. The simulation results suggest that: ■ A new product reaches fewer new consumers and acquires a lower market share when consumers switch less frequently between products. ■ A new product reaches more new consumers and acquires a higher market share when it is of a better quality to that of the existing products because more positive word-of-mouth is disseminated about it. ■ When there are products that have switching constraints in the market, launching a new product with switching constraints results in a higher market share compared to when it is launched without switching constraints. However, it reaches fewer new consumers because switching constraints result in negative word-of-mouth being disseminated about it which deters other consumers from using it. Some factors such as the fussiness of consumers; the shape and size of consumers' social networks; the type of messages that consumers transmit and with whom and how often they communicate about a product, may be beyond the control of marketing managers. However, these factors can potentially be influenced through a marketing strategy that encourages consumers to exchange positive word-of-mouth both with consumers that are familiar with a product and those who are not.
- ItemOpen AccessBuilding a question answering system for the introduction to statistics course using supervised learning techniques(2020) Leonhardt, Waldo; Er, Sebnem; Scott, LeanneQuestion Answering (QA) is the task of automatically generating an answer to a question asked by a human in natural language. Open-domain QA is still a difficult problem to solve even after 60 years of research in this field, as trying to answer questions which cover a wide range of subjects is a complex matter. Closed-domain QA is, on the other hand, more achievable as the context for asking questions is restricted and allows for more accurate interpretation. This dissertation explores how a QA system could be built for the Introduction to Statistics course taught online at the University of Cape Town (UCT), for the purpose of answering administrative queries. This course runs twice a year and students tend to ask similar administrative questions each time that the course is run. If a QA system can successfully answer these questions automatically, it would save lecturers the time in having to do so manually, as well as enabling students to receive the answers immediately. For a machine to be able to interpret natural language questions, methods are needed to transform text into numbers while still preserving the meaning of the text. The field of Natural Language Processing (NLP) offers the building blocks for such methods that have been used in this study. After predicting the category of a new question using Multinomial Logistic Regression (MLR), the past question that is most similar to the new question is retrieved and its answer is used for the new question. The following five classifiers, Naive Bayes, Logistic Regression, Support Vector Machines, Stochastic Gradient Descent and Random Forests were compared to see which one provides the best results for the categorisation of a new question. The cosine similarity method was used to find the most similar past question. The Round-Trip Translation (RTT) technique was explored as an augmentation method for text, in an attempt to increase the dataset size. Methods were compared using the initial base dataset of 744 questions, compared to the extended dataset of 6 614 questions, which was generated as a result of the RTT technique. In addition to these two datasets, features for Bag-of-Words (BoW), Term Frequency times Inverse Document Frequency (TF-IDF), Latent Semantic Analysis (LSA), Latent Dirichlet Allocation (LDiA), pre-trained Global Vector (GloVe) word embeddings and customengineered features were also compared. This study found that a model using an MLR classifier with TF-IDF unigram and bigram features (built on the smaller 744 questions dataset) performed the best, with a test F1-measure of 84.8%. Models using a Stochastic Gradient Descent classifier also performed very well with a variety of features, indicating that Stochastic Gradient Descent is the most versatile classifier to use. No significant improvements were found using the extended RTT dataset of 6 614 questions, but this dataset was used by the model that ranked eighth in position. A simulator was also built to illustrate and test how a bot (an autonomous program on a network that is able to interact with users) can be used to facilitate the auto-answering of student questions. This simulator proved very useful and helped to identify the fact that questions relating to the Course Information Pack had been excluded from the data that had been initially sourced, as students had been asking such questions through other platforms. Building a QA system using a small dataset proved to be very challenging. Restricting the domain of questions and focusing only on administrative queries was helpful. Lots of data cleaning was needed and all past answers needed to be rewritten and standardised, as the raw answers were too specific and did not generalise well. The features that performed the best for cosine similarity and for extracting the most similar past question were LSA topics built from TF-IDF unigram features. Using LSA topics as the input for cosine similarity, instead of the raw TF-IDF features,resolved the “curse of dimensionality”. Issues with cosine similarity were observed in cases where it favoured short documents, which often led to the selection of the wrong past question. As an alternative, the use of more advanced language-modelling-based similarity measures are suggested for future study. Either, pre-trained word embeddings such as GloVe could be used as a language model, or a custom language model could be trained. A generic UCT language model could be valuable and it would be preferable to build such a language model using the entire digital content of Vula across all faculties where students converse, ask questions or post comments. Building a QA system using this UCT language model is foreseen to offer better results, as terms like “Vula”, “DP”, “SciLab” and “jdlt1” would be endowed with more meaning.
- ItemOpen AccessBusiness process modelling and simulation with application to a start-up actuarial firm(2015) Gweshe, Tatenda Mark; Scott, LeanneIn our research, we set out to model, understand and evaluate the business process at a start-up actuarial firm which employs Report Writers (RWers) who specialise in quantifying actuarial matters. We simulated various "what-if" and extreme scenarios relating to (1) the impact of qualitative variables (stress, morale and health) on RWer productivity, (2) hiring policies for RWers who have various skills sets, (3) the allocation of RWers to various roles within the process, (4) the impact that a high turnover of experienced RWers has on productivity, (5) the impact of introducing a flexible working arrangement (flexitime). This was done through business process modelling and simulations. The business process we modelled was governed by numerous potentially complex inter-relationships between variables and inter-relationships, which we believed could lead to potentially significant feedback loops. The models we built were then simulated over a period of 3 to 7 years to gain insights into the behavioural trends of the firm's business process over time when subject to "what-if" scenarios and policy implementations. The model simulations allowed us to get an understanding of the behaviour of processes over time, and the key variables and relationships involved in bringing about such behaviour as certain variables were subjected to changes in levels, as set out in our objectives. We made use of relevant literature, expert opinion, past data, questionnaires and cognitive mapping techniques to build simulation models. Guided by methodologies used in literature on modelling qualitative variables, bearing in mind the dangers in modelling for them, we modelled for the complex inter-relationships between qualitative and quantitative variables.
- ItemOpen AccessDeveloping decision support for Foodbank South Africa's allocation system: an application of operational research techniques to aid decision-making at a not-for-profit organization(2011) Watson, Neil Mark; Stewart, Theodor J; Scott, LeanneThere is a dearth of research on the application of hard Operational Research (OR) techniques (simulation, linear programming, goal programming, etc.) in determining optimal ordering, inventory and allocation policies for goods within distribution systems in developing countries. This study aims to assist decision making at a not-for-profit organization (NPO), Foodbank South Africa (FBSA), within its allocation system through a combined ‘soft-hard’ OR approach. Two problem-structuring tools (soft OR), Causal Mapping (CM) and Soft System Methodology’s Root Definitions (RDs), are used to structure the organization's goals (in order to gain a comprehensive understanding of the decision-context) and gain a better understanding of the ‘decision-issues’ in the allocation system at its Cape Town warehouse.
- ItemOpen AccessLegitimacy and decision making in developmental local government : participative MCDA in Stellenbosch(2003) Scott, Leanne; Parnell, Sue; Ellis, GFRThis thesis is concerned with the problem of how to effectively address the complex issue of poverty in the context of limited resources. Poverty is a multi-dimensional problem that affects different communities in different ways. In order to use the available resources in such a way as to most effectively tackle poverty, a means of measuring and benchmarking outcomes as well as evaluating choices of intervention is required. However, smart methods of allocating scarce resources are not in themselves sufficient, if they are not regarded as legitimate by the participants of the process. The imperative of legitimacy demands that we both address the issue of quantitative rigour in resource allocation methods and that we look beyond and explore too the mechanics of effective participatory methods. The approach of developmental local government adopted by the new South African government post apartheid, places this complex problem in the sphere of local government. The primary tool available to local administrators for addressing poverty, amongst other issues, is that of integrated development planning. This process draws together the stakeholders who fall broadly into three groups of participants, namely the communities that live in the municipality, the municipal officials and the elected politicians, and allocates them the task of identifying and prioritising community and municipal issues, and developing appropriate plans to address them. This package of plans or projects is compiled into a municipal budget that targets priority issues for the area, in an integrated and coherent manner. This thesis proposes a new method for tackling this specific group decision making problem, namely Participative Multi-Criteria Decision Analysis. This method was developed in an action research setting in the municipality of Stellenbosch, South Africa, and applied to their 2001/2002 integrated development planning process. The method is grounded in the principles of participative action research in which the participation of all interested and affected patties is valued, and in which there is a commitment to work for change to the fundamental fabric of knowledge and power, leading to a greater empowerment of ordinary people. This participative framework strengthens the legitimacy of the approach by promoting a stronger sense of ownership of process and products by all participants. Within this participative framework, tools of multi-criteria decision analysis are used to support the decision making process by quantifying difficult decisions that need to be addressed. It is the synthesis of these two approaches (action research and multi-criteria decision analysis) that provides both legitimacy and rigour for this method within a highly contested and complex public decision making arena. In the spirit of action research, the method is developed by drawing on theory about developmental local government and poverty, as well as multi-criteria decision analysis. In the process of the research, over forty community workshops were held throughout the Stellenbosch municipal area. Community representatives identified and prioritised the issues of their areas; and in conjunction with municipal officials, developed and evaluated projects in response to these issues. These evaluations assisted the local council to compile the final budget for 2001/2002 in Stellenbosch. In this process, the communities (divided into nine development areas) also developed community development measurement scales which formed the basis for the project evaluations and an ongoing basis for monitoring progress in these communities. It unfolded during the course of this research that a fundamental component of this proposed participative public decision making approach is the role of a central co-ordinating person, not connected to or answerable to any of the constituent groups, who can manage the process of participation, promote an awareness of effective and informative data; ensure the appropriate use of quantification tools and maintain a focus on sustainable poverty alleviation. The method developed in this thesis was successfully applied to the process of identifying, prioritising and making choices about community issues in Stellenbosch, under conditions of significant polarisation of the constituent decision making groups, conclude that this method can be used to implement key aspects of integrated development planning as it addresses the issues of legitimacy and rigour in participative public decision making.
- ItemOpen AccessPrototype learning analytics dashboard (LAD) for an introductory statistics course at UCT(2021) Gajadhur, Suvir; Scott, LeanneA learning analytics dashboard (LAD) is an application that illustrates the activity and progress of a user in a self-regulated, online learning environment. This tool mines source data to provide meaningful information that supports decision making and positively impacts learning behaviour. Research on this topic explores how learning activities and pedagogical goals are impacted by integrating LADs into learning and/or teaching environments. Currently, the majority of the research is centred around predicting student academic performance and identifying students that are at risk of failing. The popularity of integrating technology into educational practices has led to the adoption of LADs into learning management systems (LMS) or massive open online courses (MOOCs). The objective of this paper is to develop a concept for a standalone prototype LAD, for an Introductory Statistics course (STA 1000), to be potentially integrated into the University of Cape Town's (UCT) LMS, Vula. The dashboard aims to create and incorporate meaningful visualisations, that have the potential to primarily assist students as well as educators. Visualised information in the LAD aims to positively impact students to enhance and drive effective learning, which could consequentially aid educators. Additionally, the dashboard will aim to provide actionable feedback, derived from predictive modelling and course analytics, that positively impacts learning behaviour and identifies factors that the student could most effectively use to leverage their chances of passing and improve academic performance. Predictive analytics aim to identify academic factors, that a student has control over, such as course assessments and engagement variables, at certain time points in the academic semester and provide a useful course of action at those time points. Other than variables measured throughout the course, the predictive modelling takes certain prior academic information into consideration.
- ItemOpen AccessRobben Island penguin pressure model: a decision support tool for an ecosystems approach to fisheries management(2012) Cecchini, Lee-Anne; Scott, Leanne; Stewart, Theodore; Jarre, AstridThe African penguin (Spheniscus demersus) population in southern Africa has declined from approximately 575 000 adults at the start of the 20th century to 180 000 adults in the early 1990s. The population is still declining, leading to the International Union for the Conservation of Nature upgrading the status of African penguins to Endangered on the Red List of Threatened Species. This dissertation uses a systems dynamics approach to produce a model incorporating all important pressures. The model is stochastic and spatially explicit, and uses expert opinion where data are not available. The model has been produced and revised with the help of the Penguin Modelling Group, based at the University of Cape Town. The modelling process culminated in a workshop where participants experimented with the model themselves. The model in this dissertation is only applicable to the penguin population on Robben Island and, as such, conclusions drawn cannot necessarily be applied to other penguin colonies.
- ItemOpen AccessTeaching fundamental concepts in statistical science(2011) Barr, Graham; Scott, LeanneThese modules are essentially crafted as teaching tools and the experience of first year students would be of the lecturer leading the students through the simulations at an appropriate pace, allowing plenty of opportunity for discussion and clarification. Lab based tutorials also support this process. A suite of VBA simulation programmes used at first year level containing a number of tools for teaching introductory statistics at university level. Note that these are written for MS Excel 2007 (or later versions). The modules roughly follow chapters in the first year statistics textbook, Introstat (LG Underhill) and essentially support and supplement that book. They are to a significant extent self explanatory for those with some knowledge of statistics and simulation.
- ItemOpen AccessThe use of data mining as a decision making tool for municipal performance management in the Western Cape(2007) Rasmussen, Erica L; Scott, Leanne; Stewart, TheodorThis thesis proposes the use of data mining tools within an operations research process, allowing the integration of ever increasing amounts of data collected worldwide. It is further argued that the wealth of information delivered by DM tools, with their strong visual emphasis, can be used by enhance the transfer of knowledge of stakeholders. The discipline of operations research could benefit greatly from the methods offered within the field of data mining, used to analyse the ever increasing amounts of data collected worldwide. However, the subject also offers a wealth of information that could aid in decision making, along with visual representations of this information that might assist in the transferral of knowledge to problem stakeholders. The advantages offered by data mining are not limited to problem contexts containing high-quality data, but could also assist within the development contexts containing high-quality data, but could also assist within the development context where traditionally resources and relevant skills are scarce. The benefits of data mining within this context are illustrated through the use of municipal performance data supplied by the Department of Local Government and Housing in the Western Cape of South Africa. The results of these analyses are presented to the department in order to assess the potential contribution of data mining to decisions surrounding municipal support.
- ItemOpen AccessThe use of inventories in student learning research : a case study(2006) Short, Heidi; Case, Jenni; Scott, LeanneThis study examines the practical use of student learning inventories in the higher education setting, using Vermunt's (1998) Inventory of Learning Styles in the context of a second year Business Statistics course at the University of Cape Town. The theoretical underpinnings of the inventory, as well as its predictive value, are investigated. This is done through the use of simple, yet effective, statistical techniques, some of which have not yet been attempted on an inventory of this kind. Data were collected through an online course website and student responses to the inventory were analysed along with their final results for the course in question.
- ItemOpen AccessThe use of problem structuring methods to explore the functioning and management of a selected NGO(2007) Anyogu, Alexander A; Scott, Leanne; Stewart, TheodorPoverty eradication is one of the major challenges facing South Africa and the rest of the continent. Concern around poverty alleviation in South Africa encompasses lack of capacity as well as inefficiency in the management and administration of poverty alleviation projects. Therefore, poverty alleviation agencies ought to be mindful of the issues that could affect their organizational efficiency, especially issues around organizational management. Addressing issues of management amongst the poverty alleviation agencies is necessary to assist role players in the implementation of efficient and effective poverty alleviation programs. The research explored issues around the management structure of a selected non-government organisation (SHAWCO). The objective was to develop a shared understanding of the organizational structure, amongst the members of the management team, and identify (if any) inefficiencies within the structure of the organisation. Problem Structuring Methods have been identified as a collection of tools that assist decision makers in addressing complex societal problems, and seek to alleviate or improve situations characterized by uncertainty, conflict and complexity. The study used Problem Structuring Methods to investigate the possible difficulties SHAWCO is facing as a result of management inefficiency. Interviews were used to uncover issues around the functioning and management of the organization, and an interactive problem structuring workshop was later conducted to develop a shared understanding of the identified issues.