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Orientation: South Africa’s cultural and linguistic diversity requires special measures to ensure that the assessments used in employment settings are scrupulously fair. To this end, Section 8 of The Employment Equity Act requires that psychometric tests are scientifically proved to be valid and reliable and not to discriminate unfairly against any individual or group. The South African Personality Inventory (SAPI) sets out to meet these criteria by incorporating culture-specific elements and by providing versions in each of South Africa’s 11 official languages. o Research purpose: The key determination of this study was to investigate the psychometric properties of the Afrikaans version of the South African Personality Inventory (SAPI). The aforementioned properties include item analysis, exploratory factor analysis (EFA), reliability analysis, product-moment correlation and multivariate analysis of variance (MANOVA). o Motivation for the study: To contribute to the fair, valid and reliable use of the SAPI questionnaire in all language versions of the instrument by examining the psychometric properties of the Afrikaans version and comparing it with the validated English version. Once this has been done for each of the 11 official South African languages versions, a culturally neutral instrument will be available for the full diversity of employment settings in South Africa. o Research design, approach and method: This study used a quantitative cross-sectional research design with an emic approach, objectivist ontology and a post-positivist research paradigm. Primary data was collected by administering the Afrikaans version of the SAPI questionnaire to a non-probability sample of 201 purposively selected white Afrikaans-speaking South Africans who are economically and non-economically active and have a minimum qualification of Grade 12. An online Afrikaans version of the SAPI along with a biographical questionnaire was used to collect data. Item analysis was investigated by means of a descriptive statistical analysis. An initial principle component analysis followed with exploratory factor analysis was performed to determine the instrument’s factor structure. A reliability analysis was conducted in order to measure the internal consistency of the instrument. Product-moment correlations explored the relationships between variables. Further analysis was done to detect the relationships of the variables and to detect differences. Main findings: The White Afrikaners attach immense importance to the social-relational factors. From the six factors, only three factors were extracted, namely the Social-relational Positive, combined Social-relational Negative/Conscientiousness, and Intellect/Openness factors. These factors showed adequate validity and reliability. The item functionality needs to be re-evaluated in order to measure all the six factors of the SAPI and different analytical techniques should be applied. The relationships between the remaining three factors were sufficient, and only age differences were detected in the experience of Social Relational Negative/Conscientiousness o Practical/managerial implications: The results of this study provide a firm foundation for the further investigation of the validity of the Afrikaans version of the questionnaire. Furthermore, insight is given to researchers and practitioners on the need to develop, adapt or translate psychometric instruments, especially for use in an environment which is multicultural and multilingual. o Contribution/value-add: This study contributes to cultural-specific research on the assessment of personality in South Africa. Its thorough investigation and attempt to validate the Afrikaans version of the SAPI is supported by an extensive body of literature relevant to standardizing the SAPI. Practitioners and organisations will now be able to administer a culturally informed personality assessment where the home language of the employees is Afrikaans. / Dissertation (MCom)--University of Pretoria, 2019. / Human Resource Management / MCom / Unrestricted

Traditionellt har fokus i bildundervisningen varit att eleverna ska lära sig tekniska färdigheter, vilket kan leda till att de sociala och subjektiva aspekterna förbises. Samtidigt glöms elevernas förmåga att utforska och tänka kritiskt bort, vilket minskar den sociala interaktionen i klassrummet och hindrar eleverna från att fördjupa sin förståelse och insikt i viktiga samhällsfrågor genom diskussioner och dialog med varandra som ett kollektivt samarbete i klassrummet. I mitt examenarbete undersöker jag vilken potential har kritiskt utforskande samtal om aktuella nyhetshändelser i bildundervisning på högstadiet? Och på vilket sätt utvecklas elevers uppfattningar om bildskapande i mötet med metoder relaterade till samtida konstutövande, genom arbete med kollektivt undersökande, kritiskt tänkande och skapande metoder? Studien syftar till att undersöka potentialen i en kritisk och utforskande metodik i bildundervisningen, där högstadieelever i årskurs 9 kollektivt utforskar nyhetshändelser och skapar kritiska koncept relaterade till samhälleliga frågor för att besvara studiens syfte och frågeställningar. Studiens empiriska material består av elevarbeten, ljud- och filmmaterial från workshopen. Jag observerade både elevernas arbete och diskussioner mellan lärare och elever. Resultaten och tolkningen av den insamlade data kommer att presenteras i mitt gestaltningsarbete genom visuella tolkningar av data och analysresultaten. Till exempel har jag i min gestaltning försökt tolka elevernas samtal och deras visuella arbete, med utgångspunkt i det omfattande arbete som deltagarna i studien har utfört. De genomgående och betydelsefulla teman som framträdde i flera av deras gestaltningar var "skolskjutningar", "psykisk ohälsa" och "krig och konflikt". Genom att analysera och tolka deras verk har jag strävat efter att belysa de djupgående och mångfacetterade uttrycken av deltagarnas visuella verk, samtal och engagemang i undersökningen. Samtidigt har jag också undersökt aspekter av social interaktion, kritiskt utforskande och en relationell syn på kunskap.

The Expectation confirmation model (ECM) is commonly employed to investigate technological advances and customer satisfaction with chatbots. However, customer satisfaction is a multifaceted concept intertwined with emotions and subjective perceptions, comprehending customer satisfaction fully can therefore be challenging. Consequently, the purpose of this exploratory study was to develop and refine the concept of customer satisfaction by answering the research question: How does the integration of underlying factors to the Expectation Confirmation Model (ECM) affect customer satisfaction with chatbot services?. The study incorporated underlying factors such as anthropomorphic behavior, brand perception, trust and word of mouth, which were integrated into the existing components of the ECM. Through a unique research approach involving 20 semi-structured interviews and observations, this study captured and reflected on the subjective impressions and emotions of customers while using chatbots. An array of findings are presented, such as the importance of distinguishing between usability and problem-solving efficiency of chatbots performance, the emphasis on accurate answers over human-like characteristics for chatbots, and the impact of experience, familiarity and age on customer satisfaction with chatbots. In conclusion, this study advocates for further qualitative research to explore  the potential impact of other underlying factors' on customer satisfaction for ECM.

In early 2020, many businesses (including gyms) were instructed to shut down for an unspecified period of time as a response to the SARS-CoV-2 virus (Casagrande et al., 2020, p.1; Erskine, M., 2020, para.1; O’Brien, 2020, Gyms and Health Centers section, para.1-16). As a result, many people experienced a change in how much they exercised and the quality and quantity of their sleep (Antunes et al., 2020, pp.3,5; Bigalke et al., 2020, p.7; Cellini et al., 2021, pp.113- 115, 117; Constandt et al., 2020, p.4; Pérez-Carbonell et al., 2020, pp.164, 166; Puccinelli et al., 2021, p.6). There was also an increase in the levels of negative mental states, such as anxiety and depression in various populations (Daly et al., 2020, pp.2-5). This study primarily explored changes in exercise and sleep (quality and quantity) as a result of the pandemic in a highly athletic adult population of rowers and triathletes. The data collected from the study also touched upon the changes in the mental states of the participants. A survey was sent across Canada to rowing and triathlon clubs from SurveyMonkey that had both qualitative and quantitative questions to examine these areas of contention. A majority of participants indicated that their sleep quality had worsened as a result the COVID-19 pandemic. However, there wasn’t enough evidence to indicate that the pandemic affected the length of their sleep. The athletic performance of the athletes, as measured by self-report, decreased during the pandemic in an overwhelming number of participants. Finally, although there were many indications of worsened mental health states (such as reports of increased anxiety), there wasn’t a validated questionnaire used to measure changes in mental health concerns in the population related to the COVID-19 pandemic. Some mental health concerns that were shared by the participants indicated other causes than only the pandemic. Future research should include more objective measures of sleep duration and anxiety and depression scores to better clarify those hypotheses. / Graduate

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[pt] As visualizações de dados são cada vez mais comuns na mídia tradicional e nas redes sociais. No entanto, a alfabetização visual da população não acompanhou essa crescente popularidade. É necessário para quem cria os gráficos montar uma comunicação visual que contenha as informações necessárias de forma atrativa e de fácil compreensão. Em contrapartida, é necessário para quem os consome, captar as informações representadas pelos gráficos e extrair as análises do que vê. A importância da alfabetização visual é a capacidade de ler um gráfico, ou seja, olhar para um gráfico e identificar informações relevantes, tendências e discrepâncias em um determinado cenário. Neste trabalho, realizamos quatro estudos para explorar os fatores que influenciam o sucesso da análise de dados visuais. No primeiro estudo descobrimos como as pessoas tentam dar sentido a visualizações de dados específicas, através de perguntas que elas fazem ao encontrar uma visualização pela primeira vez. No segundo estudo exploramos como as distribuições de dados podem afetar a eficácia e eficiência das visualizações de dados. No terceiro estudo investigamos quando não especialistas identificam que uma visualização não é adequada para responder uma pergunta de análise específica, quando eles fazem boas sugestões de alteração para tornar essas visualizações adequadas e quando avaliam bem a adequação de algumas sugestões oferecidas a eles. No quarto estudo, criamos um teste para avaliar a compreensão das pessoas sobre os aspectos aplicados (responder perguntas de análise com o apoio de uma visualização) e conceituais (questões sobre a função e estrutura) da visualização de dados. Nossos resultados fornecem recursos para o desenvolvimento de material didático e ferramentas para recomendação de visualizações de dados relacionadas a perguntas que se visa responder. Uma contribuição adicional deste trabalho aos resultados dos estudos foi a estruturação de uma lista unificada de diferentes tarefas de visualização que encontramos na literatura. / [en] Data visualizations are increasingly common in traditional media and social networks. However, the visualization literacy of the population did not follow this growing popularity. It is necessary for those who create the charts to assemble a visual communication that contains the necessary information in an attractive and easy-to-understand way. By contrast, it is necessary for those who consume them to capture information represented by the charts and extract the analyses of what they see. The importance of visual literacy is the ability to read a chart, i.e., look at a chart and identify relevant information, trends, and outliers in a given scenario. In this work, we conducted four studies to explore factors related to the success of visual data analysis. We identified issues ranging from data distribution to formulating good questions to enrich exploration. The first study discovered how people try to make sense of specific data visualizations through questions they ask when they first encounter a visualization. In the second study, we explored how data distributions can affect the effectiveness and efficiency of data visualizations. In the third study, we investigated when non-experts identify that particular visualization is not adequate to answer a specific analysis question, when they make good suggestions for changes to make these visualizations adequate, and when they evaluated well the adequacy of some suggestions offered to them. In the fourth study, we created a test to assess people s understanding of the applied (answering analysis questions supported by a visualization) and conceptual (questions about function and structure) aspects of data visualization. Our results provide resources for developing of educational material and tools for recommending data visualizations to answer specific data-relation questions. An additional contribution of this work to the results of the studies was the structuring of a unified list of different visualization tasks that we found in the literature.

The term electronic commerce (e-commerce) refers to a business model that allows companies and individuals to buy and sell goods and services over the internet. The focus of this thesis is on online pharmacies, a segment of the ecommerce market. Even though internet pharmacies are still subject to the same stringent rules imposed on pharmacies that limit the scope for their market growth, it has shown a notable increase in the past decades. The main goal of this thesis is to develop a data-driven marketing strategy based on a Swedish based online pharmacy’s daily sales data. The methodology of the data analysis includes exploratory data analysis (EDA) and market basket analysis (MBA) using the Apriori algorithm and the application of marketing frameworks and theories from a data-driven standpoint. In addition to the data analysis, this paper proposes a conceptual framework of a digital marketing strategy based on the RACE framework (reach, act, convert, and engage). The result of the analysis has led to the following data-driven marketing strategy: Special attention should be paid to association rules with a high lift ration value; high gross profit margin percentile (GPMP) products should have a volume-based marketing strategy that focuses on lower prices on subsequent items; and price bundling is the best marketing strategy for low GPMP products. Some of the practical ideas mentioned in this thesis paper include optimizing keyword search for a high GPMP product type and sending reminder emails and push alerts to avoid cart abandonment. The findings and recommendations presented in this thesis can be used by online pharmacies to extract knowledge that may support several decisions ranging from raising overall order size, marketing campaigns, to increasing the sales of products with a high gross profit margin.

Managing water in urban areas is an ever increasingly complex challenge. Technology enables sustainable urban water management and with integrated smart metering solutions, massive amounts of water consumption data from the end users can be collected. However, the possibility of generating data from the end user holds no value in itself. It is with the use of data analysis the vast amount of the collected data can provide more insightful information creating potential benefits. It is recognized that a deeper understanding of the end user could potentially provide benefits for operational managers as well as for the end users. A single case study of a data set containing high frequency end user water consumption data from rental apartments has been conducted, where the data set was analyzed in order to see what possible information that could be extracted and interpreted based on an exploratory data analysis (EDA). Furthermore, an interview with the operational manager of the buildings under study as well as a literature review have been carried out in order to understand how the gathered data is used today and to which contexts it could be extrapolated to provide potential benefits at a building level. The results suggests that the EDA is a powerful method approach when starting out without strong preconception of the data under study and have successfully revealed patterns and a fundamental understanding of the data and its structure. Through analysis, variations over time, water consumption patterns and excessive water users have been identified as well as a leak identification process. Even more challenging than to make meaning of the data is to trigger actions, decisions and measures based on the data analysis. The unveiled information could be applied for an improved operational building management, to empower the customers, for business and campaign opportunities as well as for an integrated decision support system. To summarize, it is concluded that the usage of smart water metering data holds an untapped opportunity to save water, energy as well as money. In the drive towards a more sustainable and smarter city, smart water meter data from end users have the potential to enable smarter building management as well as smarter water services.

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