The concept of metamemory proposes that supplementary to typically measured memory abilities, memory monitoring and control processes are used to optimise learning. Accurate memory monitoring appears to be underpinned by a range of cognitive, and possibly affective, contributions. In populations with these deficits, metamemory has been shown to be impaired. In Multiple Sclerosis (MS), only a limited metamemory literature exists, surprising given that MS is a leading cause of disability among people of working age, and cognitive and mood disorder is common. Using structural equation modelling, this study of 100 people with MS explored factors contributing to performance on episodic Judgment of Learning, Retrospective Confidence and Feeling of Knowing. Given its negative influence on cognitive domains in MS, the impact of information processing deficits on metamemory was also investigated. Finally, memory self-report, a frequently used clinical indicator of memory functioning, was assessed. Findings suggest that memory complaint is associated with mood, and is unrelated to tested memory. Second, Retrospective Confidence Judgments were predictive of memory performance, even in the presence of memory impairment. Third, an unusual finding of maintained underconfidence at delay was observed in the Judgment of Learning task. Finally, Feeling of Knowing judgments related to executive, but not to memory ability. A novel finding in respect of this judgment was of processing speed relating negatively to accuracy, in the context of executive dysfunction. This suggests that some top-down direction of processing resources may be a factor in supporting accuracy, rather than the speed at which information is processed. Of all the task-based judgments, accuracy in this judgment was the only one with a reliable association with mood. Faster processing speed, executive dysfunction and least depression symptomatology related to low accuracy, perhaps typifying a profile of disinhibition seen in MS, characterised by poorly constrained processing and apparently elevated mood.

Structural equation modelling (SEM) is carried out with the aim of testing hypotheses on the model of the researcher in a quantitative way, using the sampled data. Although SEM has developed in many aspects over the past few decades, there are still numerous advances which can make SEM an even more powerful technique. We propose representing the nal theoretical SEM by a Bayesian Network (BN), which we would like to call a Probabilistic Structural Equation Model (PSEM). With the PSEM, we can take things a step further and conduct inference by explicitly entering evidence into the network and performing di erent types of inferences. Because the direction of the inference is not an issue, various scenarios can be simulated using the BN. The augmentation of SEM with BN provides signi cant contributions to the eld. Firstly, structural learning can mine data for additional causal information which is not necessarily clear when hypothesising causality from theory. Secondly, the inference ability of the BN provides not only insight as mentioned before, but acts as an interactive tool as the `what-if' analysis is dynamic. / Mini Dissertation (MCom)--University of Pretoria, 2018. / Statistics / MCom / Unrestricted

Visitor expenditure can be affected by different economic, socio-demographic and psychological variables. Previous literature have focused on the use of observed tourists and destination characteristics as explanatory variables to explain visitor expenditure, whereas the use of psychological factors has been underresearched. The present study aims to fill in the gap in the existing literature through the exploration of more extensive use of psychological variables. This is accomplished by the use of structural equation modelling (SEM), a methodological approach which seems not to have been applied before in tourism expenditure econometric models. In econometrics expenditure research, Mortazavi (2018) found satisfaction to be an endogenous regressor of expenditure. Hence, the contribution of our model is that it allows for the relationship between visitor satisfaction and visitor expenditure, and vice versa, to be tested simultaneously. Consequently, under this context we may identify the magnitude of one variable impact on another while at the same time accounting for simultaneous relationship between the two paths. The findings of this study go in hand with previous literature and economic theory which have found a positive relationship between visitor satisfaction and visitor expenditure.

The need for online banking technology in the banking industry is important to allow financial institutions to serve their customers worldwide, without having the need to be present in person or face-to-face to benefit from the service. Despite the investment in informational technology and information system infrastructure by Saudi Arabian financial institutions, the Saudi banks have lagged their Western counterparts when it comes to provision of online banking services. Given a relatively recent adoption of online banking in Saudi Arabia, consumer trust in online banking is a critical challenge facing bank managers, warranting further research. The aim of this research is to develop a framework to improve consumer trust toward online banking services and its affect consumer intentions to use the online banking service and e-WOM. The literature included the assessment of relevant theories including social cognitive theory, technology acceptance model and commitment trust theory. These theories formed the basis of formulation of research framework, including development of 12 research hypotheses. Perceived usefulness, perceived ease of use, relationship termination cost, shared value, communication, privacy and demographic factors all have an important role in influencing the extent of trust and the subsequent intention of customers to engage in and use online banking services provided by the financial institutions. When it comes to the literature gap, there remains a relative lack of existence of research on the subject of consumer trust in online banking within Saudi Arabia (Zhou, 2012; Alanezi and Brooks, 2014; AL-Malkawi et al., 2016), which presents a gap in the literature warranting further research. Moreover, most of the prior research on the subject of consumer trust in online banking has concentrated on the information cues such as reputation and information quality (Montazemi and Qahri-Saremi, 2015). This is alongside relatively little attention given to other factors such as perceived usefulness, ease of use, shared value, and privacy/security, which are crucial factors in online banking services (Fatima, 2011; Aloul., 2012; Montazemi and Qahri-Saremi, 2015). Regarding methodology, the positivist research philosophy, deductive approach, survey questionnaire and quantitative data collection and analysis techniques were undertaken. A key rationale for selection of such a methodology is the review of relevant literature, which led to development of research hypotheses that are tested through the survey technique, which is consistent with positivist and deductive research approach. The survey questionnaire request was sent online to 800 research participants (users of online services in Saudi Arabia). Out of these 800, 585 responded (indicating a response rate of an impressive 73%). The response rate was improved through giving regular reminders to the research participants who had not responded to the survey earlier. The findings of this research support the argument that trust in e-bank website play an important role in maintaining long term relationship with customers. Therefore, online banks who deal with their customers in a confidential, transparent and honest manner and ultimately protect the consumers' interests are likely to contribute to greater adoption of online banking by customers in Saudi Arabia. Furthermore, it is also concluded that perceived ease of use, trust in online banking website, trust in technology, relationship termination cost, privacy/security, shared value, and communication have positive and significant effect on customer trust in e-bank website, intention to use online banking, and e-WOM.

Ample evidence from the literature suggests that in recent years, banks have been heavily investing in customer relationship management (CRM) systems. The reasons for this are traced to banks' emergent need to gain and sustain competitive advantage through greater knowledge of their customers. In turn, this increased knowledge is likely to also lead to increased: a) customer base, b) customer satisfaction, c) customer retention and, d) customer loyalty. The literature suggests that there is a knowledge gap, which relates to the reasons for CRM systems in adoption and usage as service delivery channels, as well as its effects on banks' customers. This is particularly the case with regards to the banks' customers' buying behaviour and is stemming from the fact that bank customers display some unique buying patterns. Based on the above, the aim of this study is to find out whether or not there is a potential influence of newly implemented CRM systems on consumer buying behaviour in the context of the Nigerian banking industry and also to assess the extent and nature of this influence (if any).

A key challenge facing dairy farming is to meet the increasing demand for dairy products from a growing and more affluent global population in a period of unprecedented socio-economic and environmental change. In order to address this challenge, policies are currently placing emphasis on ‘sustainable intensification’ (SI), i.e. producing ‘more’ outputs and services with ‘less’ resources and environmental impacts. Determining whether or not SI can deliver greater yet sustainable dairy production requires understanding of the relationships between sustainability pillars (environmental; economic; and social) and farm aspects (e.g. on-farm management; and animal productivity) under particular farming systems and circumstances (e.g. regional bio-physical conditions). Trade-offs between pillars and aspects is inevitable within a farming system. Many widely-used assessment methods that aim to measure, scale and weight these pillars and aspects are unable to fully capture trade-offs between them. The objectives of this thesis are: 1) to identify key trade-offs in dairy farming systems to inform greater yet sustainable food production; and 2) to introduce models and methodologies aiming at a more holistic measurement and better understanding of dairy farm sustainability. This thesis assesses the sustainability of French and UK dairy farming systems via a farm efficiency benchmarking modelling framework coupled with statistical analyses. It explores the relationships between pillars, aspects and technical, economic and environmental performance; and identifies important drivers/differentials in dairy farm efficiency. Importantly, it also suggests ways in which farm inputs and outputs can be adjusted so that improvements in environmental, technical and economic performance become feasible. Efficiency benchmarking was performed with the multiple-input – multiple-output productive efficiency method Data Envelopment Analysis (DEA). DEA calculates single aggregated efficiency indices per farm by accounting for several farm inputs and outputs which the DEA model endogenously scales and weights. In this work, the notion of farm inputs and outputs was extended to also include ‘undesirable’ outputs (greenhouse gas emissions) and environmental impacts (e.g. eutrophication, acidification etc.) of dairy farming. The DEA models employed belong to the family of ‘additive’ models, which have several advantages over ‘traditional’ DEA models. These include their ability (i) to simultaneously increase outputs and reduce inputs, undesirable outputs and environmental impacts; (ii) to identify specific sources of inefficiency. These ‘sources’ represent a farm’s shortfalls in output production and its excesses in input use and/or in undesirable outputs and environmental impacts, relatively to the other farms; (iii) to position undesirable outputs in the output set rather than consider them as inputs or ‘inverse’ outputs; and (iv) to rank farms by efficiency performance. Importantly, this thesis also proposes a new additive model with a ranking property and high discriminatory power. In a second stage, DEA was coupled with partial least squares structural equation modelling (SEM) so as to develop and relate latent variables for environmental performance, animal productivity and on-farm management practices. The results suggested that the efficacy of SI may be compromised by several on-farm trade-offs between pillars, aspects and farm inputs and outputs. Moreover, trade-offs depended on particular farming systems and circumstances. Increasing animal productivity did not always improve farm environmental performance at whole farm-level. Intensifying production at animal and farm-levels, coupled with high reliance on external inputs, reduced farm environmental performance in the French case, i.e. a significant negative relationship was found between intensification and environmental performance (SEM path coefficients ranged between -0.31 and -0.57, p < 0.05). Conversely, in the UK case, systems representing animal-level intensification (via genetic selection) for increased milk fat plus protein production performed better, on average, than controls of UK average genetic merit for milk fat plus protein production in terms of technical efficiency (DEA scores between 0.91– 0.92 versus 0.78–0.79) and environmental efficiency (scores between 0.92–0.93 versus 0.80), regardless of whether on a low-forage or high-forage diet. The levels of inefficiency in (undesirable) outputs, inputs and environmental impacts varied among farming systems and depended on the regional and managerial characteristics of each system. For instance, in France, West farms had higher eutrophication inefficiencies than East farms (average normalized eutrophication inefficiencies were, respectively 0.141 and 0.107), perhaps because of their more intensive production practices. However, West farms were more DEA-efficient than East farms as the former benefited from bio-physical conditions more favourable to dairy farming (mean DEA score ranks were 97 for West and 83 for East). Such findings can guide policy incentives for SI in different regions or dairy systems. The proposed modelling framework significantly contributes to current knowledge and the search for the best pathways to SI, improves widely-used modelling approaches, and challenges earlier findings based on less holistic exercises.

This study explores the previously less researched impact of corporate reputation on employees, more specifically on employee engagement. Employee engagement and corporate reputation are concepts that have been receiving attention in both business and academia alike, especially in view of the economic turmoil of the past decade as both constructs have been shown to affect profits. The study was designed in a way to measure the impact of employees’ perceptions of corporate reputation on their engagement with the corporation, while controlling for the state of their psychological contract with the organisation. An online survey of 509 employees from a large South African bank provided the data to which a Structural Equation Model (SEM) emanating from the theoretical background was fitted. The results of the model unequivocally confirmed that corporate reputation perceptions are an important predictor of employee engagement. It was also found that psychological contract breach influences both perceptions of reputation by employees and employee engagement directly. The implication is that corporate reputation can have a strong influence on tangible results through employee engagement. / Dissertation (MBA)--University of Pretoria, 2012. / Gordon Institute of Business Science (GIBS) / unrestricted

The rapid rate of increase in competition among the manufacturing industries has caused many organizations to continuously seek improvement in the quality of the products they manufacture to meet and exceed customer expectations. Organizations are under pressure to minimize the production costs to offer competitive prices for their products. The success story of Toyota Motor Company in implementing Lean Manufacturing (LM) has inspired many organizations around the world to adopt LM in order to improve their operational performance. There are, however, mixed results on the impact of LM on operational performance. Some studies have shown that its implementation increases operational performance while others have shown little to no improvement or even negative results. Institutional and contingency theories may provide insight into some of these contradictions and give a perception of why the implementation of LM has yielded different results on operational performance. The institutional theory states that organizations mimic the actions and practices of other organizations because of the pressure to remain competitive. Organizations in the developing countries also seem to have been imitating the Toyota Motor company that has been successful in implementing LM. On the other hand, the contingency theory states that corporations are organized according to external situations. Related to the contingency theory is the effect of Industry Clockspeed (IC). Some industries are transforming at a high speed while others are transforming at a low speed. The high IC industries are characterized by the quick development and release of new products, shorter development time and frequent changes in organizational structures. Low IC industries, however, manufacture products with a long life cycle, thus the products, processes and organizational structures for these industries change only after a long period. This study opines that the environment under which an organisation operates may affect the results of LM implementation process. The research was conducted in three parts and each of these parts is presented as chapters in this thesis. The first part (Chapter 4) gives a review and classifies the impact measurement models that have been used by various researchers to measure the success of implementing LM. These models can be classified as quantitative, qualitative, simulation-based and graphical measurement models. Pareto analysis is used to select the type of measurement model and Lean practices that are frequently used by researchers to develop Lean measurement models. The qualitative measurement model was preferred for evaluating the effect of implementing LM on operational performance because of its ability to use question structures that allow qualitative data collection for a rich analysis of opinion. With a proper structure, the questionnaire items can also be parsed and analyzed quantitatively with modern statistical techniques like Structural Equation Modelling. The Lean practices selected were Just In Time (JIT), Jidoka, People integration and Stability and standardization for building the model. This part concludes by developing a structural model that can be used to measure the impact of Lean implementation in industry, using Zimbabwean industry data. The second part (Chapter 5) evaluates the effect of implementing LM tools on operational performance across various industries in Zimbabwe. The major goal of this chapter was to develop an operational model (based on the lead from chapter 4) and test it in manufacturing organizations across various industries. A structured survey questionnaire was used for the collection of data in identified companies and 214 useful responses were obtained. The results of the study indicated that operational performance was improved by implementing the selected LM tools. The performance improvement variables that were significantly influenced were speed, flexibility and dependability. The third part (Chapter 6) analyzed the moderation effect of IC on the relationship between LM tools and operational performance. The industries grouped under low IC were pharmaceutical, agrochemicals, steel, automobile, timber production, battery, chemical and plastics. The high IC industries were food, beverage, electronics and garment. A structural equation model was proposed and investigated across the two groups. A structured survey questionnaire was used to collect empirical data from manufacturing companies. The data obtained from the responses was analysed using Smart PLS 3 and SPSS version 25. The results of the study showed that IC had a moderating effect on the relationship between LM practices and operational performance for both low and high IC industries. The last chapter summarises the findings, made recommendations and proposes directions for further research. / Thesis (PhD)--University of Pretoria, 2019. / Organization for Women in Science for the Developing World (OWSD) / Industrial and Systems Engineering / PhD / Unrestricted

Seam quality is affected by various fabric mechanical properties with a combination of their sewing parameters. Previously, a lot of research has been done on identifying the parameters that influencing seam quality by looking into correlation between fabric properties and sewing parameters. The purpose of this current study was to investigate the performance of seam quality in terms of seam appearance and strength constructed with different sewing parameters. Another aim was to identify parameters that influence the seam quality using the Structural Equation Modelling (SEM) by AMOS and leads to the development of multivariable predictive equations using SPSS. Finally, the validation between experimental and predicted results using newly developed equations was examined using a new set of fabrics. The investigation was done for five different fabric categories, namely light, light to medium, medium, medium to heavy and heavy weight. A total of 45 fabrics with different weave densities, fibre types and structures were used. Seams were produced using various sewing parameters such as threads with different fibre types and structures, needle sizes and stitch densities. All fabrics were tested for their mechanical properties using two established items of equipment known as Kawabata Evaluation System for Fabrics (KES-F) and Fabric Assurance by Simple Testing (FAST). Seam evaluations together with thread and fabric mechanical properties obtained from KES-F and FAST were used as input for modelling. From the experimental work, it was concluded that the usage of thicker threads did not always give better strength and the seam appearance was also poor. A combination of finer thread with moderate strength and a medium level of stitch density according to fabric weight category provided an effective result for both seam appearance and strength. From the modelling work, it was found that the extensibility, bending and shearing properties, together with thread properties including extensibility, tensile strength and size, were among the properties selected by SEM to be included in the predictive equations. The validation results showed that the standard deviation between fabric properties used to develop the equations and new fabric properties used for validation plays an important role. The principal conclusion was that the prediction equations developed using SEM and SPSS possible to be used and gave a strong validation between experimental and predicted results when the new fabric properties were within one standard deviation.

The effective management of organisational climate has become an increasingly important ingredient for business success. This has resulted in a need for up-to-date research and information on the subject, leading to the development of various measurement instruments. The main purpose of this study was to validate the Organisational Climate Measure (OCM) for the South African context. The OCM is designed to serve as a global multi-dimensional measure of organisational climate and is based on the competing values model developed by Quinn and Rohrbaugh. In this study a comprehensive literature review was conducted prior to the OCM’s administration to a sample of 200 individuals currently employed in a South African organisation. The reliability and validity of the OCM was evaluated by means of Cronbach’s alpha coefficient and confirmatory factor analysis. The results indicated strong correlations between factors and a good model fit. It was concluded that the OCM is a valid and reliable instrument for measuring organisational climate within the South African context. Copyright / Dissertation (MCom)--University of Pretoria, 2011. / Human Resource Management / unrestricted