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Theses and dissertations (Accounting and Informatics)

Permanent URI for this collectionhttp://ir-dev.dut.ac.za/handle/10321/4

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Start date: 2020Subject: search.filters.subject.Technological innovations

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    Evaluating the level of satisfaction in higher education students with technical support services provided using fuzzy TOPSIS decision method
    (2024) Pursan, Geeta; Adeliyi, Timothy T.; Joseph, Seena
    The use of information and communication technologies at higher education institutions is no longer an option, but rather a need. Information Technology support is an essential factor that entails giving end users assistance with hardware and software components. Technical support for information technology has been recognized as a crucial element linked to student satisfaction because it helps students understand, access, and use technology efficiently. IT technical support services are essential for higher education students to succeed in their studies. However, the quality of IT technical support services can vary widely from institution to institution. Student satisfaction with IT technical support services is an important measure of the quality of education that students receive. Conversely, evaluating student satisfaction is a complex task, as it involves subjective assessments of service quality. This dissertation used a framework that combines three approaches: Principal Component Analysis (PCA), Service Quality (SERVQUAL), and Fuzzy TOPSIS. The successful implementation of IT technical support is aided by identifying the essential success criteria that enable efficient and effective support for students and instructors. Hence the main aim of this study is to identify and rank the key success factors for the successful implementation of IT technical support at higher education institutes. 81 key success factors identified from 100 research papers were analyzed using principal component analysis. The findings led to the identification and ranking of 25 PCs. From these findings, the SERVQUAL dimensions that featured at the top-most rankings were selected, and that being: tangibility, reliability, assurance, empathy, and responsiveness. These factors were used in the development of the questionnaire that was sent to students which measured student perceptions of the five dimensions of service quality. The proposed approach is implemented in a higher education institution in South Africa. The questionnaires were administered to a specific target of students, only those student participants’ who had contacted the IT technical team for IT technical support via the WhatsApp service communication method formed part of the study. Once data was collected, SERVQUAL which is a well-established scale for measuring service quality was used to calculate the average score for each dimension of service quality. The dimensions of service quality where students were most and least satisfied were identified. Finally, Fuzzy TOPSIS, which is a multi-criteria decisionmaking (MCDM) method that handles uncertainty and vagueness in data was used to rank the IT technical support services based on student satisfaction. The SERVQUAL results showed that the overall satisfaction level of students with IT technical support services led to a final score of 60 percent, meaning that the support services rendered were acceptable to students. The Fuzzy TOPSIS rankings identified the sub-criteria, overall being satisfied with the support services rendered as rank number one. As can be deduced that since both the SERVQUAL and Fuzzy TOPSIS methods have nominated satisfaction level as the common factor, this research indicates that the IT technical support services rendered by the IT technical support team are adequately sufficient and that the needs of the students are met and that the services rendered are highly appreciated by the students at the Durban University of Technology. This research proves that the IT support team is compliant with the quality of IT technical support services rendered to students at the Durban University of Technology however, the IT support service can be improved by the proactiveness of the technical team. This research contributes by providing useful information highlighting factors that can be used to examine areas in educational institutions that need to receive continuous and special care to generate high student satisfaction; ensure future success and gain a competitive advantage. These factors can assist the management of HEI in determining the success or failure of an institution in terms of the technical support provided to students and student satisfaction. The results of this evaluation can be used by other HEIs to improve the quality of IT technical support services and to ensure that they are meeting the needs of students.
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    A framework for supporting technological innovation by manufacturing small and medium enterprises in KZN
    (2024) Bingwa, Luyanda Loraine; Ngibe, Musawenkosi
    Unemployment is an ongoing phenomenon in every country. It is rapidly increasing, which leads to a decline in the economy and other societal problems. This is particularly evident in developing countries such as South Africa, where the unemployment rate is 32.9%. The South African government has identified small and medium-sized enterprises (SMEs) as a key aspect of its strategy to reduce unemployment rates and to realise the vision outlined in the National Development Plan 2030. SMEs are major job creators and contribute significantly to the gross domestic product (GDP) of South Africa. They account for the majority of employment opportunities in the country, especially in sectors such as agriculture, manufacturing, and services. SMEs also support economic growth through their capacity for innovation and swift market adaptation. They are ideal for generating innovative ideas due to their pioneering role in adopting new technologies and are particularly adept at identifying gaps in the market which could be addressed through innovative solutions. There are ongoing debates about the uptake of technology by SMEs in African countries, including South Africa. Some scholars argue that manufacturing SMEs in South Africa have been hesitant to adopt modern technologies, which has hindered their growth and their ability to reach full potential. However, there are counterarguments that provide a more nuanced perspective on the challenges and opportunities for technology adoption among manufacturing SMEs in KwaZulu-Natal (KZN), South Africa. One significant issue is SME owners' inability to fully grasp the complexity of information and communications technology (ICT), which has a negative impact on their decision to adopt ICT. Furthermore, government regulations and compliance requirements have been a crucial factor affecting the viability and growth of manufacturing SMEs. Without a comprehensive understanding of ICT, SMEs find it challenging to make informed decisions about their investments in this field. Critically evaluating the use of Fourth Industrial Revolution (4IR) technologies as a way of improving success rates amongst manufacturing SMEs in KZN will enable the development of a framework which can provide practical guidance for the adoption of 4IR technologies by manufacturing SMEs in KZN. The objectives of this study are supported by a pragmatic methodology, which considerably expands the area of the investigation. 384 manufacturing SMEs in KZN are the target population for this study, and approaches for identification and selection of the sample size include convenience and purposive sampling. The study utilises both primary and secondary research. Interviews and questionnaires are utilised as data collection instruments. The review of literature and relevant theories such as the technology acceptance model (TAM), the technology-organisation-environment (TOE) framework, dynamic capability theory (DCT), the theory of planned behaviour (TPB), task-technology fit, process virtualisation, and the unified theory of acceptance and use of technology (UTAUT) assist in identifying and addressing potential barriers that may arise during the technology adoption process, such as cost, skills, resistance to change, and compatibility with existing systems. The primary results of this study demonstrate that digital competencies and thorough ICT knowledge are lacking in manufacturing SMEs in KZN. In addition, ICT adoption and usage in manufacturing SMEs in KZN is significantly low, which diminishes the potential of ICT as a long-term strategy. This is evident in the investigation of several factors relating to the acceptance and use of ICT by manufacturing SMEs as a longterm tool for business success. The findings of this study also suggest that manufacturing SMEs do not have the capacity to identify and implement appropriate and adequate ICTs as a sustainable strategy to improve their business viability. Based on the key findings, the study recommends that manufacturing SMEs prioritise digital literacy, which will enhance their comprehension of the potential benefits of ICT adoption. Consultation with IT professionals is recommended as a valuable means for SME owners to obtain reliable guidance and to discuss the complexities of ICT. The government should consider creating platforms to enable SMEs to express objections to regulations, contribute to amendments, and provide insight into the impact of legislation on their business.
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    Development of a clustering algorithm for universal color image segmentation
    (2023-01-01) Joseph, Seena; Olugbara, Oludayo O.
    Image segmentation is an important stage of many real-world image applications in the domain of computer vision as a core method for understanding and analyzing digital images. It is aimed to segregate the most salient objects in an image by clustering homogenous regions based on the characteristics of image pixels. Segmentation of salient objects is a complex process because of the existence of numerous inherent characteristics of images that can impede the performance of the process. Due to these diverse image characteristics, a model that is suitable for one category of images is essentially inappropriate for other image categories, which makes image segmentation an open problem. Myriads of classical segmentation algorithms have been developed over the years, yet generalization and universal optimum performance are far from ideal levels. Clustering algorithms have been developed in recent times for the effective segmentation of images. However, the performance of the majority of the existing clustering-based segmentation algorithms substantially relies on the selection of an optimal number of initial clusters. Incorrect cluster count selection may result in uneven highlighting of the target object and be susceptible to under- or oversegmentation of images. This opens an avenue to fully discover a universal clustering algorithm for image segmentation that would be appropriate for manifold classes of images. In this study, the color histogram clustering algorithm has been proposed to automatically determine a suitable number of clusters that indicates homogenous regions in an image. The aim was to segment the most salient object from its surrounding regions using color histogram clustering that characterizes homogenous regions based on primitive features. The segmentation algorithm starts with histogram clustering-based on the quantized RGB color image to automatically identify the clusters that correspond to the homogenous regions in the image. The perceptual homogeneity of the input RGB color image is achieved by the transformation to L*a*b* color model based on four primitive features. The primitive features are color contrast, contrast ratio, spatial feature, and center prior that are extracted to compute the descriptor of each cluster. The cluster level saliency score is then computed as a function of the four primitive features extracted from the color image. The cluster level saliency is used to compute the final saliency score of each pixel to highlight the target object. The color histogram clustering method of this study combines the Otsu thresholding algorithm with the saliency map to represent the segmented image in a silhouette format. Morphological operations are finally performed to remove the undesired artifacts that may be present at the segmentation stage. Hence, this present study has introduced a novel, simple, robust, and computationally efficient color histogram clustering algorithm that agglutinates color contrast, contrast ratio, spatial feature, and central prior for efficiently segmenting the target objects in diverse image categories. The performance of the proposed algorithm was evaluated using the widely used metrics of precision, recall, F-measure, mean absolute error, and overlap ratio on six different categories of images selected from five benchmarked corpora of MSRA10K, ASD, SED2, ImgSal, and DUT OMRON. Moreover, 1000 images from ECSSD, 4447 images from HKU-IS, and 1500 images from COCO datasets were selected to validate the performance of the algorithm on more complex natural datasets. Experimental results have indicated that the proposed algorithm outperformed 30 bottom-up non-deep learning and seven top-down deep learning salient object detection algorithms. The performance of the proposed algorithm was further evaluated on four medical image datasets and the effects of image preprocessing were comprehensively investigated. The performance of the proposed image segmentation algorithm was analyzed in terms of accuracy, sensitivity, specificity, and dice similarity on 10015 images from HAM10000, 2594 images from ISIC2018 dataset, and 200 images from the PH2 dataset against six supervised and six unsupervised benchmark segmentation algorithms. The performance of the proposed algorithm was further validated on the segmentation of 1145 leukocyte nuclei images from the Raabin-WBC dataset in terms of accuracy, sensitivity, specificity, Dice similarity, and Jaccard index. In total, 22307 images with a variety of properties were used to test the performance of the proposed algorithm. In addition, the effects of image preprocessing on the performance of the proposed algorithm were further investigated in this study. The statistical results obtained have shown that the proposed algorithm is free from image preprocessing, and demonstrated its application on a wide class of images without any bounding to the heterogeneous characteristics of the input images. The novelty of the work reported in this thesis has demonstrated that the proposed algorithm is superior to the investigated supervised deep learning and prominent unsupervised segmentation algorithms in terms of quantitative results and visual effects.
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    The impact of office automation on service delivery : a case of uMshwathi Municipality
    (2022-01-27) Mkhize, Yiphathe Michael; Ngibe, Musawenkosi; Govender, Rosaline
    The adoption of automation at the uMshwathi Municipality has been often associated with reform programmes aimed at reducing the inefficiencies generated by the administrative load. The uMshwathi Municipality’s mission is to promote social and economic development through sustainable, effective and efficient use of resources and dependable delivery of basic services in line with the constitutional mandate, and to continually strive to remain a green municipality. The purpose of this quantitative study is to ascertain the effectiveness of automated systems towards the improvement of service delivery within the uMshwathi Municipality and reveal the challenges and opportunities of automation within the uMshwathi Municipality. Based on the empirical findings, automation facilitated the workflow, thereby improving work performance at uMshwathi Municipality, which impacted the service delivery. This study found that computer programmes were most commonly used in the automation process. This was followed by other tools and programmes including the scanner, intranet, selfservice, digital signature and filing system. The study concluded that automation improves the process of service delivery within the uMshwathi Municipality. This study therefore recommends that uMshwathi Municipal management should consistently maintain its strong reputation of quality service to regularly meet customer service expectations and also keep a good administrative environment that has a compatible automation system that will assist in enhancing employee work satisfaction. The study also recommended that the uMshwathi Municipality should provide a comprehensive training for employees on how to use automation effectively and efficiently as well as how to fix possible automation errors. Furthermore, the study recommends that the uMshwathi Municipality to use remote technical support whereby a technician can resolve computer problems without being physically present in the area where the computers are located. Municipal management should improve the work environment by providing adequate equipment such as work equipment and modernised automation to personnel in order for them to perform their jobs more effectively and efficiently. Automation advancements such as an updated website can facilitate the development of an intranet system and interactive software could encourage more communication between municipal employees and the citizens. Continuous training of administrative employees is also very important as it helps all the municipal departments to improve quality service delivery to its citizens.