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You searched for +publisher:"University of South Africa" +contributor:("Njuho, Peter M"). Showing records 1 – 2 of 2 total matches.

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University of South Africa

1. Burombo, Emmanuel Chamunorwa. Statistical modelling of return on capital employed of individual units .

Degree: 2014, University of South Africa

Return on Capital Employed (ROCE) is a popular financial instrument and communication tool for the appraisal of companies. Often, companies management and other practitioners use untested rules and behavioural approach when investigating the key determinants of ROCE, instead of the scientific statistical paradigm. The aim of this dissertation was to identify and quantify key determinants of ROCE of individual companies listed on the Johannesburg Stock Exchange (JSE), by comparing classical multiple linear regression, principal components regression, generalized least squares regression, and robust maximum likelihood regression approaches in order to improve companies decision making. Performance indicators used to arrive at the best approach were coefficient of determination ( ), adjusted ( , and Mean Square Residual (MSE). Since the ROCE variable had positive and negative values two separate analyses were done. The classical multiple linear regression models were constructed using stepwise directed search for dependent variable log ROCE for the two data sets. Assumptions were satisfied and problem of multicollinearity was addressed. For the positive ROCE data set, the classical multiple linear regression model had a of 0.928, an of 0.927, a MSE of 0.013, and the lead key determinant was Return on Equity (ROE),with positive elasticity, followed by Debt to Equity (D/E) and Capital Employed (CE), both with negative elasticities. The model showed good validation performance. For the negative ROCE data set, the classical multiple linear regression model had a of 0.666, an of 0.652, a MSE of 0.149, and the lead key determinant was Assets per Capital Employed (APCE) with positive effect, followed by Return on Assets (ROA) and Market Capitalization (MC), both with negative effects. The model showed poor validation performance. The results indicated more and less precision than those found by previous studies. This suggested that the key determinants are also important sources of variability in ROCE of individual companies that management need to work with. To handle the problem of multicollinearity in the data, principal components were selected using Kaiser-Guttman criterion. The principal components regression model was constructed using dependent variable log ROCE for the two data sets. Assumptions were satisfied. For the positive ROCE data set, the principal components regression model had a of 0.929, an of 0.929, a MSE of 0.069, and the lead key determinant was PC4 (log ROA, log ROE, log Operating Profit Margin (OPM)) and followed by PC2 (log Earnings Yield (EY), log Price to Earnings (P/E)), both with positive effects. The model resulted in a satisfactory validation performance. For the negative ROCE data set, the principal components regression model had a of 0.544, an of 0.532, a MSE of 0.167, and the lead key determinant was PC3 (ROA, EY, APCE) and followed by PC1 (MC, CE), both with negative effects. The model indicated an accurate validation performance. The results showed that the use of principal components… Advisors/Committee Members: Njuho, Peter M (advisor).

Subjects/Keywords: Classical multiple linear regression; Principal components regression; Generalized least squares regression; Robust maximum likelihood regression; Return on capital employed; Stepwise directed search; Kaiser-Guttman criterion; Key determinants

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APA (6th Edition):

Burombo, E. C. (2014). Statistical modelling of return on capital employed of individual units . (Masters Thesis). University of South Africa. Retrieved from http://hdl.handle.net/10500/19627

Chicago Manual of Style (16th Edition):

Burombo, Emmanuel Chamunorwa. “Statistical modelling of return on capital employed of individual units .” 2014. Masters Thesis, University of South Africa. Accessed October 21, 2019. http://hdl.handle.net/10500/19627.

MLA Handbook (7th Edition):

Burombo, Emmanuel Chamunorwa. “Statistical modelling of return on capital employed of individual units .” 2014. Web. 21 Oct 2019.

Vancouver:

Burombo EC. Statistical modelling of return on capital employed of individual units . [Internet] [Masters thesis]. University of South Africa; 2014. [cited 2019 Oct 21]. Available from: http://hdl.handle.net/10500/19627.

Council of Science Editors:

Burombo EC. Statistical modelling of return on capital employed of individual units . [Masters Thesis]. University of South Africa; 2014. Available from: http://hdl.handle.net/10500/19627


University of South Africa

2. Marin, Mike A. Exploring complexity metrics for artifact-centric business process models.

Degree: 2017, University of South Africa

This study explores complexity metrics for business artifact process models described by Case Management Model and Notation (CMMN). Process models are usually described using Business Process Management (BPM), which is a relatively mature discipline with a large number of practitioners. Over the last few decades a new way of describing data intensive business processes has emerged in BPM literature, for which traditional BPM is no longer adequate. This emerging method, used to describe more flexible processes, is called business artifacts with Guard-Stage-Milestone (GSM). The work on GSM influenced CMMN, which was created to fill a market need for more flexible case management processes for knowledge workers. Complexity metrics have been developed for traditional BPM models, such as the Business Process Model and Notation (BPMN). However, traditional BPM is not suitable for describing GSM or CMMN process models. Therefore, complexity metrics developed for traditional process models may not be applicable to business artifact process models such as CMMN. This study addresses this gap by exploring complexity metrics for business artifact process models using CMMN. The findings of this study have practical implications for the CMMN standard and for the commercial products implementing CMMN. This research makes the following contributions: • The development of a formal description of CMMN using first-order logic. • An exploration of the relationship between CMMN and GSM and the development of transformation procedures between them. • A comparison between the method complexity of CMMN and other popular process methods, including BPMN, Unified Modeling Language (UML) Activity diagrams, and Event-driven Process Charts (EPC). • The creation of a systematic literature review of complexity metrics for process models, which was conducted in order to inform the creation of CMMN metrics. • The identification of a set of complexity metrics for the CMMN standard, which underwent theoretical and empirical validation. This research advances literature in the areas of method complexity, complexity metrics for process models, declarative processes, and research on CMMN by characterizing CMMN method complexity, identifying complexity metrics for CMMN, and exploring the relationship between CMMN and GSM. Advisors/Committee Members: Lotriet, H. H. (Hugo H.) (advisor), Van der Poll, John Andrew (advisor), Njuho, Peter M (advisor).

Subjects/Keywords: Business Artifacts; Business Process Management; BPM; Business Process Model; Case Management; Case Management Model and Notation; CMMN; Guard-Stage-Milestone; GSM; Complexity Metric; Process Model Complexity; Method Complexity

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Marin, M. A. (2017). Exploring complexity metrics for artifact-centric business process models. (Doctoral Dissertation). University of South Africa. Retrieved from http://hdl.handle.net/10500/23179

Chicago Manual of Style (16th Edition):

Marin, Mike A. “Exploring complexity metrics for artifact-centric business process models.” 2017. Doctoral Dissertation, University of South Africa. Accessed October 21, 2019. http://hdl.handle.net/10500/23179.

MLA Handbook (7th Edition):

Marin, Mike A. “Exploring complexity metrics for artifact-centric business process models.” 2017. Web. 21 Oct 2019.

Vancouver:

Marin MA. Exploring complexity metrics for artifact-centric business process models. [Internet] [Doctoral dissertation]. University of South Africa; 2017. [cited 2019 Oct 21]. Available from: http://hdl.handle.net/10500/23179.

Council of Science Editors:

Marin MA. Exploring complexity metrics for artifact-centric business process models. [Doctoral Dissertation]. University of South Africa; 2017. Available from: http://hdl.handle.net/10500/23179

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