Faculty of Accounting and Informatics
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Item Evolving a framework to observe and analyse customer experience on the Twitter platform using machine learning techniques(2024) Moodley, Thaneshni; Thakur, SurendraRetailers have become more focused on retaining and turning existing customers into longterm clients because retailers have become more competitive, customers more demanding, and competitors more aggressive. The 2020 COVID-19 pandemic has forced a transformation for retailers. Within months, a revolution has taken place, constituting major changes to how consumers view cash, how they shop online and what they expect from retailers as part of a positive buying experience. Consumers increasingly expect retailers to create a seamless customer experience. This often means leaning on digital capabilities to create a seamless, omni-channel experience by linking different aspects of the customer shopping experience. The usage of big data analytics has primarily been implemented outside of South Africa to better understand customer connections and experiences, highlighting a noticeable research gap in South Africa. It has been proven to be an effective tool for retailers in predicting customer behaviour. There is a need to reduce the complexities in understanding which are the most appropriate machine learning techniques for sentiment analysis of online customer experience and to capitalise on development. Thereafter, online retailers are better equipped to tailor machine learning tools to craft analytical tools. Given the massive migration to online transactions, this work presents a rigorous analysis of social media posts, which is paramount for modern-era retailers. Businesses can use sentiment analysis to determine how well their brand is performing in the marketplace, learn more about the attitudes of their customers and determine whether their items receive more positive or negative feedback. A longitudinal study was adopted to analyse a dataset of retail-related tweets for the identification of customer complaints using a sentiment analysis hybrid approach, which is a combination of lexicon and machine learning approaches. A conceptual framework was developed to observe and analyse customer experiences on the Twitter platform using machine learning techniques. The framework encompasses components such as data preparation, natural language processing pre-processing techniques, calculating sentiment using sentiment lexicon and ML techniques, and thereafter a selection of the best-performing machine learning technique for sentiment analysis within the developed conceptual framework. The extracted dataset contains 240 000 tweets posted between 01 January 2017 and 31 January 2019, out of which 27 233 tweets were selected for the study. Natural language pre-processing techniques were applied to the dataset, including tokenisation, stemming, lemmatisation, part-of-speech tagging, and name-of-entity recognition. Supervised and deep machine learning gave the best results of 61.75 and 60.25. This study has identified deep learning as a good technique for sentiment analysis when NLP pre-processing methods are done in a certain order. A study on analysing retail complaints posted on the Twitter platform using a sentiment analytic framework has not been done in South Africa before. This study has proven that the sentiment analysis hybrid approach is highly capable of analysing social media data.Item The impact of communication skills as a subject in the programme Cost and management accounting at the Durban University of Technology(2014-02-18) Naidoo, Suntharmurthy Kristnasamy; Penceliah, Darry; Moodley, VivThe aim of this research is to evaluate the communication proficiency of students studying Cost and Management Accounting (CMA) and to assess whether the subject communication, as a course, is having any positive influence on students who are lacking critical thinking and literacy skills. It is necessary to analyse the factors affecting communication because of the diversity of the Durban University of Technology (DUT) students coming from different cultural, ethnic and geographic backgrounds before evaluating the communication proficiency of students. The field of accounting is broadly quantitative in nature, but Management Accounting, although a branch of this broad knowledge is more qualitative in nature. Data analysis, report writing and decision making are fundamental to Management Accounting. The target population for the study was CMA students. This population entails students enrolled for the first time in 2007 and current second and third year students. It was necessary to follow the progress of the 2007 cohort of students to establish whether students were achieving their qualification within the specified three year period as required by the CMA course and whether communication skills were an issue if they were unsuccessful. The objective to include second and third year students registered in the Department of Management Accounting at DUT in 2012 was to acquire current and pertinent information with regard to student perception on the subject relating to communication skills. An analytical type of research approach was used to conduct the study and quantitative data was collected using questionnaires and computer reports to gain an insight into the impact of communication skills as a subject in the CMA programme. The study confirmed that gender and the location of schools played a role in the academic performance of students. The overall performance between the genders revealed that female students performing slightly better than their male counterparts. English First Language (EFL) female students demonstrated much better academic performance than the EFL male students. Irrespective of language differences, if a student had an aptitude and performed well in the English Language at grade 12 or matric, the student has a better chance of being more successful with the CMA programme The number of EFL and English Second Language (ESL) students acknowledging that the English language affected them in obtaining better grades in CMA was fifty one per cent. Since the second and third year CMA students perceive that their lecturers were unaware of their poor understanding of the English language after completing the subject Communication Skills in the first year of study indicates that the subject is not having the desired affect. Both EFL and ESL students also acknowledged the vital role that Communication Skills play in education, social and economic development. This study, inter alia, recommends a screening of new students for English proficiency and providing academic support for students who have problem with literacy skills. It also recommends increasing the subject content of Communication Skills and extending the duration from one semester to two semesters.