The development of an optimised decision based methodology for the replacement timing of frontline equipment utilised within the quarrying industry
- Authors: Basson, Kenneth Mervyn
- Date: 2018
- Subjects: Decision making , Industrial equipment Industrial equipment -- Maintenance and repair
- Language: English
- Type: Thesis , Doctoral , DBA
- Identifier: http://hdl.handle.net/10948/23647 , vital:30592
- Description: At present, frontline equipment employed at B&E International, and operating within the quarrying sector is typically replaced as soon as the operating expenses are deemed to be excessive. From a capital budgeting perspective, the trigger for signalling the replacement of equipment occurs when prescribed operating cost performance metrics are violated. In some instances, a further consideration for motivating the replacement of equipment is when the perception arises that the nonavailability of the equipment employed, results in financial losses being incurred by a company. It can therefore be argued that the current equipment replacement timing methodological approach adopted at B&E International is suboptimal in nature. The situation is further aggravated by the fact that in many instances, escalation of commitment manifests itself whereby unnecessary capital is repeatedly invested in order to extend the life of an asset resulting in a situation occurring whereby the required level of investment return is not achieved. In the event of these situations arising, the decision to replace an asset is prolonged as a result of the suboptimal investment decisions being made. The primary focus of this study is to provide a methodological equipment replacement framework that is based upon sound capital budgeting fundamentals. A comprehensive literature review of capital budgeting approaches that specifically focus on the optimal replacement timing of frontline quarrying equipment, did not yield any relevant studies that have been undertaken in this regard. This study did however investigate contemporary equipment replacement approaches based upon a capital budgeting paradigm and highlighted their respective limitations. Convincing evidence obtained, indicated that the most widely accepted method of identifying the optimal replacement timing of equipment occurs when the economic life of the asset is attained. This in itself would therefore infer that a cost minimisation approach is the most pervasive methodological approach adopted in order to identify the optimal replacement timing of equipment. When considering capital investment based decisions, it was found that the discounted cash flow based methodologies are the most widely used and accepted approach applied in the mining industry. Notwithstanding this, one major caveat manifests itself in that when considering the optimal replacement timing of front line equipment within the quarrying industry, the inclusion of uncertainty, flexibility and the associated financial risks was not evident. In order to model these effects, a probabilistic Net Present Value (NPV) approach was adopted and the required Discounted Cash Flow (DCF) models were constructed. Given the uncertainty of the expected cumulative R&M profiles for the asset classes constituting this study, an extensive statistical analysis was carried out in order to establish the required predictive Repair and Maintenance (R&M) models required for the DCF analysis by means of regression analysis. Further regression analyses were conducted in order to model the overall availability and utilisation metrics for the respective asset classes included in this study. The consequence of incurring downtime was investigated and the resultant DCF analysis yielded a significant impact on the Free Cash Flow (FCF) generated by the respective assets. The magnitude of the incurred consequential financial losses incurred as a result of the respective downtime was found to be significant when considering frontline equipment. In order to model the effect of, and the extent to which, the respective independent variables influence the static NPV outcome, a sensitivity analysis was performed. From this, the influence of the independent variables constituting the NPV model employed in this study, were observed. A Real Options Analysis (ROA) approach was initially employed in order to model the effects of FCF uncertainty and the results of carrying out this analysis indicated a minimal influence on the static NPV model referred to earlier. It was therefore concluded that from an equipment replacement timing perspective, the ROA approach did not provide a robust and accurate representation of the probabilistic NPV outcomes anticipated. In order to address these perceived shortcomings, an Monte Carlo Simulation (MCS) model was constructed and the requisite probability distribution functions representing the most influential independent variables determined from the sensitivity analysis were identified and subsequently analysed. The results of the MCS analysis yielded the expected NPV outcomes that were found to be far more conservative compared to the static NPV outcomes referred to previously. Furthermore, the concluding findings of this study indicate that in order to estimate the optimal time to dispose of an asset, a static NPV analysis must first be modelled and thereafter a probabilistic NPV analysis. The respective uncertainty aspects over the lifespan of the assets should be identified to be incorporated into the MCS model. This methodological approach therefore opposes the use of a strictly deterministic based approach and rather predicates the use of a probabilistic NPV based framework. This study further concluded that traditional DCF approaches fail to consider management flexibility in terms of adapting to uncertainty and to also reduce the possibility of “escalation of commitment” occurring as a result of sub-optimal equipment replacement timing decisions by management. The use and acceptance of the traditional DCF approaches are acknowledged, but in order to develop an equipment replacement methodological approach that considers uncertainty and risk on the one hand and also allows for the incorporation of real data over the assets lifetime on the other, the use of an MCS probabilistic NPV based model was found to be the optimal approach to be adopted. The result of updating the static NPV model with updated data as soon as it is obtained enables one to generate accurate probabilistic distribution functions required for the subsequent MCS analysis. By adopting this approach the study has concluded that one can obtain realistic and accurate NPV forecasts from the anticipated FCF estimates. The principal conclusion obtained from this study is that the optimal time in which to replace front line assets employed at B&E International is when the probabilistic net earnings profile, viz., NPV of the equipment is maximized.
- Full Text:
- Date Issued: 2018
- Authors: Basson, Kenneth Mervyn
- Date: 2018
- Subjects: Decision making , Industrial equipment Industrial equipment -- Maintenance and repair
- Language: English
- Type: Thesis , Doctoral , DBA
- Identifier: http://hdl.handle.net/10948/23647 , vital:30592
- Description: At present, frontline equipment employed at B&E International, and operating within the quarrying sector is typically replaced as soon as the operating expenses are deemed to be excessive. From a capital budgeting perspective, the trigger for signalling the replacement of equipment occurs when prescribed operating cost performance metrics are violated. In some instances, a further consideration for motivating the replacement of equipment is when the perception arises that the nonavailability of the equipment employed, results in financial losses being incurred by a company. It can therefore be argued that the current equipment replacement timing methodological approach adopted at B&E International is suboptimal in nature. The situation is further aggravated by the fact that in many instances, escalation of commitment manifests itself whereby unnecessary capital is repeatedly invested in order to extend the life of an asset resulting in a situation occurring whereby the required level of investment return is not achieved. In the event of these situations arising, the decision to replace an asset is prolonged as a result of the suboptimal investment decisions being made. The primary focus of this study is to provide a methodological equipment replacement framework that is based upon sound capital budgeting fundamentals. A comprehensive literature review of capital budgeting approaches that specifically focus on the optimal replacement timing of frontline quarrying equipment, did not yield any relevant studies that have been undertaken in this regard. This study did however investigate contemporary equipment replacement approaches based upon a capital budgeting paradigm and highlighted their respective limitations. Convincing evidence obtained, indicated that the most widely accepted method of identifying the optimal replacement timing of equipment occurs when the economic life of the asset is attained. This in itself would therefore infer that a cost minimisation approach is the most pervasive methodological approach adopted in order to identify the optimal replacement timing of equipment. When considering capital investment based decisions, it was found that the discounted cash flow based methodologies are the most widely used and accepted approach applied in the mining industry. Notwithstanding this, one major caveat manifests itself in that when considering the optimal replacement timing of front line equipment within the quarrying industry, the inclusion of uncertainty, flexibility and the associated financial risks was not evident. In order to model these effects, a probabilistic Net Present Value (NPV) approach was adopted and the required Discounted Cash Flow (DCF) models were constructed. Given the uncertainty of the expected cumulative R&M profiles for the asset classes constituting this study, an extensive statistical analysis was carried out in order to establish the required predictive Repair and Maintenance (R&M) models required for the DCF analysis by means of regression analysis. Further regression analyses were conducted in order to model the overall availability and utilisation metrics for the respective asset classes included in this study. The consequence of incurring downtime was investigated and the resultant DCF analysis yielded a significant impact on the Free Cash Flow (FCF) generated by the respective assets. The magnitude of the incurred consequential financial losses incurred as a result of the respective downtime was found to be significant when considering frontline equipment. In order to model the effect of, and the extent to which, the respective independent variables influence the static NPV outcome, a sensitivity analysis was performed. From this, the influence of the independent variables constituting the NPV model employed in this study, were observed. A Real Options Analysis (ROA) approach was initially employed in order to model the effects of FCF uncertainty and the results of carrying out this analysis indicated a minimal influence on the static NPV model referred to earlier. It was therefore concluded that from an equipment replacement timing perspective, the ROA approach did not provide a robust and accurate representation of the probabilistic NPV outcomes anticipated. In order to address these perceived shortcomings, an Monte Carlo Simulation (MCS) model was constructed and the requisite probability distribution functions representing the most influential independent variables determined from the sensitivity analysis were identified and subsequently analysed. The results of the MCS analysis yielded the expected NPV outcomes that were found to be far more conservative compared to the static NPV outcomes referred to previously. Furthermore, the concluding findings of this study indicate that in order to estimate the optimal time to dispose of an asset, a static NPV analysis must first be modelled and thereafter a probabilistic NPV analysis. The respective uncertainty aspects over the lifespan of the assets should be identified to be incorporated into the MCS model. This methodological approach therefore opposes the use of a strictly deterministic based approach and rather predicates the use of a probabilistic NPV based framework. This study further concluded that traditional DCF approaches fail to consider management flexibility in terms of adapting to uncertainty and to also reduce the possibility of “escalation of commitment” occurring as a result of sub-optimal equipment replacement timing decisions by management. The use and acceptance of the traditional DCF approaches are acknowledged, but in order to develop an equipment replacement methodological approach that considers uncertainty and risk on the one hand and also allows for the incorporation of real data over the assets lifetime on the other, the use of an MCS probabilistic NPV based model was found to be the optimal approach to be adopted. The result of updating the static NPV model with updated data as soon as it is obtained enables one to generate accurate probabilistic distribution functions required for the subsequent MCS analysis. By adopting this approach the study has concluded that one can obtain realistic and accurate NPV forecasts from the anticipated FCF estimates. The principal conclusion obtained from this study is that the optimal time in which to replace front line assets employed at B&E International is when the probabilistic net earnings profile, viz., NPV of the equipment is maximized.
- Full Text:
- Date Issued: 2018
Business ethics in Ugandan small and medium-sized enterprises
- Authors: Mayanja, Jamiah
- Date: 2016
- Subjects: Business ethics -- Uganda , Small business -- Uganda
- Language: English
- Type: Thesis , Doctoral , DPhil
- Identifier: http://hdl.handle.net/10948/8521 , vital:26400
- Description: SMEs have been acknowledged by governments globally as a prime source of economic growth and development. In Africa there has been a noticeable increase in the number of SME establishments. In Uganda, SMEs are the most popular business choice and play a major role in the national economy. Although SMEs significant economic contributions are generally acknowledged, being ethical and successful has become a challenge, as many SMEs in Uganda have not fully adopted and integrated ethics into their business strategies. Understanding the reasons for the increased unethical behaviour in SMEs is central to their continued business success. The primary objective of the study was to investigate the factors that influence ethical business conduct in Ugandan SMEs. From a comprehensive literature review, three main independent variables (staff-, business- and external environment factors) were identified as variables influencing ethical business conduct (dependent variable) of SMEs. A hypothetical model was developed to determine whether the independent variables have an influence on the dependent variable. Twelve hypotheses were formulated to test the relationships between three staff factors, five business factors, four external environment factors and ethical business conduct. The study sought the perceptions of SME owners or managers in the Kampala District and utilised the quantitative research paradigm. A survey was conducted with the aid of a structured self-administered questionnaire distributed by three fieldworkers. A combination of convenience and snowball sampling was utilised. The final sample comprised 384 respondents. The validity of the measuring instrument was ascertained by using exploratory factor analysis. The Cronbach‟s alpha values for reliability were calculated for each of the factors identified during the exploratory factor analysis. A total of ten valid and reliable factors were retained. Pearson product-moment correlation and multiple regression analysis were used to test the correlation and statistical significance of the relationships hypothesised between the various independent and dependent variables. One statistically significant relationship was found between the staff factors (employee attitude) and ethical business conduct. Two statistically significant relationships were found between the business factors (knowledge acquisition and management practices) and ethical business conduct. Three statistically significant relationships were found between the external environment factors (legal requirements, industry norm and media power) and ethical business conduct. External environmental factors seem to have a greater influence on SME ethical business conduct in Uganda. Multivariate Analysis of Variance (MANOVA) was used to identify if significant relationships exist between the eight demographic variables and seven reliable and valid independent variables. Furthermore, post-hoc Scheffé tests identified where the significant differences occurred between the different categories. Cohen‟s d-values were calculated in order to assess the practical significance of the mean scores. A total of twelve practical significant relationships were identified. SME owners or managers should consider employing staff with the right attitude to uphold sound ethical business values. They should implement ethical management practices to promote ethical business conduct amongst employees and ensure that employees are made aware of what is regarded as acceptable ethical business behaviour. SME owners or managers should adhere to legal requirements and industry norms to be known as businesses exhibiting ethical behaviour and utilise media to instil and guide ethical values in employees. Lastly, they must pay attention to the role that demographical variables such as: gender, level of education, current employment status, number of years in business and number of employees, play in behaving ethically in business.
- Full Text:
- Date Issued: 2016
- Authors: Mayanja, Jamiah
- Date: 2016
- Subjects: Business ethics -- Uganda , Small business -- Uganda
- Language: English
- Type: Thesis , Doctoral , DPhil
- Identifier: http://hdl.handle.net/10948/8521 , vital:26400
- Description: SMEs have been acknowledged by governments globally as a prime source of economic growth and development. In Africa there has been a noticeable increase in the number of SME establishments. In Uganda, SMEs are the most popular business choice and play a major role in the national economy. Although SMEs significant economic contributions are generally acknowledged, being ethical and successful has become a challenge, as many SMEs in Uganda have not fully adopted and integrated ethics into their business strategies. Understanding the reasons for the increased unethical behaviour in SMEs is central to their continued business success. The primary objective of the study was to investigate the factors that influence ethical business conduct in Ugandan SMEs. From a comprehensive literature review, three main independent variables (staff-, business- and external environment factors) were identified as variables influencing ethical business conduct (dependent variable) of SMEs. A hypothetical model was developed to determine whether the independent variables have an influence on the dependent variable. Twelve hypotheses were formulated to test the relationships between three staff factors, five business factors, four external environment factors and ethical business conduct. The study sought the perceptions of SME owners or managers in the Kampala District and utilised the quantitative research paradigm. A survey was conducted with the aid of a structured self-administered questionnaire distributed by three fieldworkers. A combination of convenience and snowball sampling was utilised. The final sample comprised 384 respondents. The validity of the measuring instrument was ascertained by using exploratory factor analysis. The Cronbach‟s alpha values for reliability were calculated for each of the factors identified during the exploratory factor analysis. A total of ten valid and reliable factors were retained. Pearson product-moment correlation and multiple regression analysis were used to test the correlation and statistical significance of the relationships hypothesised between the various independent and dependent variables. One statistically significant relationship was found between the staff factors (employee attitude) and ethical business conduct. Two statistically significant relationships were found between the business factors (knowledge acquisition and management practices) and ethical business conduct. Three statistically significant relationships were found between the external environment factors (legal requirements, industry norm and media power) and ethical business conduct. External environmental factors seem to have a greater influence on SME ethical business conduct in Uganda. Multivariate Analysis of Variance (MANOVA) was used to identify if significant relationships exist between the eight demographic variables and seven reliable and valid independent variables. Furthermore, post-hoc Scheffé tests identified where the significant differences occurred between the different categories. Cohen‟s d-values were calculated in order to assess the practical significance of the mean scores. A total of twelve practical significant relationships were identified. SME owners or managers should consider employing staff with the right attitude to uphold sound ethical business values. They should implement ethical management practices to promote ethical business conduct amongst employees and ensure that employees are made aware of what is regarded as acceptable ethical business behaviour. SME owners or managers should adhere to legal requirements and industry norms to be known as businesses exhibiting ethical behaviour and utilise media to instil and guide ethical values in employees. Lastly, they must pay attention to the role that demographical variables such as: gender, level of education, current employment status, number of years in business and number of employees, play in behaving ethically in business.
- Full Text:
- Date Issued: 2016
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