The aim of this study was to investigate a productivity measurement at the South African Minting Company and evaluate the relationship between productivity and quality. Special emphasis was given to profit-linked total factor model as the tool for measurement. This was encouraged by their ability to separate productivity, profitability and price recovery. Three models were selected and evaluated. These models American Productivity Center (APC) Model, “Profitability = productivity + price recovery” (PPP) model and multi-factor productivity measurement model (MFPMM). APC model was selected as the suitable model because of its simplicity, easy to set up, its ability to produce both financial and non financial data, and allow for route cause analysis with expert system, and more insight for the manager with Microsoft Excels’ What if analysis “Goal seek”. APC model was set up for four periods, from 1 April 2004 to 30 September 2007. The overall profitability results of the circulation coins profit center show an overall positive contribution. There was a break-even of the price recovery for 2006 financial year (period 2). In 2007 financial year (period 3), there was a negative contribution, and this improved to almost break-even in the six month period during this 2008 financial year (period 4). This means there was much more inflation on input resources and the recovery was not fully realised in the price of goods sold. Individual input costs show that the negative price recovery is culminating from material, labour and energy costs contributions. There is a plausible explanation for material and labour, but not for energy. The metal volatility is the underlying cause of the price variation. Labour variation was a company strategy to adjust employee to higher percentiles. Productivity was always positive with the highest contribution in the current financial year (period 4). This means that the profitability at SA Mint has been driven by productivity in the past two financial years. iv Survey of the questionnaire shows average scores for productivity and quality. It is noteworthy, that the lowest mean score for productivity is for the statement “Products are produced in error-free process”. This is a productivity quality measure. In addition, the same variable shows r2 value of 0.42. A conclusion is that even though productivity and quality are highly correlated and show a highly positive relationship, there is a concern on quality in the company. A link can be made that low price recovery becomes more difficult when the quality is not always good. Defective product is a cost, because the product does not reach the customer and if the product is reworked it is still a cost, though low, but more importantly it decreases the available capacity. This study was successful in setting up APC model and producing data that is worthy to the company and academic world. Finally, this study was successful in its quest to establish the relationship between productivity and quality.

The aim of this study was to investigate a productivity measurement at the South African Minting Company and evaluate the relationship between productivity and quality. Special emphasis was given to profit-linked total factor model as the tool for measurement. This was encouraged by their ability to separate productivity, profitability and price recovery. Three models were selected and evaluated. These models American Productivity Center (APC) Model, “Profitability = productivity + price recovery” (PPP) model and multi-factor productivity measurement model (MFPMM). APC model was selected as the suitable model because of its simplicity, easy to set up, its ability to produce both financial and non financial data, and allow for route cause analysis with expert system, and more insight for the manager with Microsoft Excels’ What if analysis “Goal seek”. APC model was set up for four periods, from 1 April 2004 to 30 September 2007. The overall profitability results of the circulation coins profit center show an overall positive contribution. There was a break-even of the price recovery for 2006 financial year (period 2). In 2007 financial year (period 3), there was a negative contribution, and this improved to almost break-even in the six month period during this 2008 financial year (period 4). This means there was much more inflation on input resources and the recovery was not fully realised in the price of goods sold. Individual input costs show that the negative price recovery is culminating from material, labour and energy costs contributions. There is a plausible explanation for material and labour, but not for energy. The metal volatility is the underlying cause of the price variation. Labour variation was a company strategy to adjust employee to higher percentiles. Productivity was always positive with the highest contribution in the current financial year (period 4). This means that the profitability at SA Mint has been driven by productivity in the past two financial years. iv Survey of the questionnaire shows average scores for productivity and quality. It is noteworthy, that the lowest mean score for productivity is for the statement “Products are produced in error-free process”. This is a productivity quality measure. In addition, the same variable shows r2 value of 0.42. A conclusion is that even though productivity and quality are highly correlated and show a highly positive relationship, there is a concern on quality in the company. A link can be made that low price recovery becomes more difficult when the quality is not always good. Defective product is a cost, because the product does not reach the customer and if the product is reworked it is still a cost, though low, but more importantly it decreases the available capacity. This study was successful in setting up APC model and producing data that is worthy to the company and academic world. Finally, this study was successful in its quest to establish the relationship between productivity and quality.

台灣地區居民近年的死亡率下降速度加快，使得我國國民的平均壽命在公元2000年已超過美國，成為長壽的國家之一。其中我國國民死亡率的下降幅度因年齡而不同，且各個年代、世代也不相同，與APC（Age-Period-Cohort）模型採年齡、年代與世代三個因子分析死亡率頗為一致，因此本文計畫以APC模型研究台灣的死亡率。然而，由於「年代＝年齡＋世代」之線性相關，參數估計值有甄別問題（Identification Problem），使得參數估計值不唯一。 文獻中有不同方法解決APC模型的參數估計問題，近年又有Fu（2000）提出之本質估計量（Intrinsic Estimator），可直接解決參數估計及其變異數。因此本文首先以電腦模擬驗證本質估計量，以及過去其他估計方法，檢測這些方法是否可得出理論的結果。本文的第二部分則以西元1961至2005年的資料探討APC模型的實用性，分析APC與Lee-Carter模型的優劣；研究發現APC模型用於估計死亡率時，整體而言雖不如Lee-Carter模型，但可彌補Lee-Carter模型在高年齡有較大誤差的不足，唯在年輕族群則仍有改善空間，未來或可考慮APC與Lee-Carter模型的結合。 / The mortality rates in Taiwan area have been experiencing dramatic decreases in recent years. The life expectancy has surpassed that in the United States in 2000 and Taiwan has become one of the longevity countries. Besides, the falling of mortality rates varies in different age, period, and cohort groups, which corresponds to the APC (Age-Period-Cohort) model. Therefore, the goal of this paper is to study the mortality rates in Taiwan area with APC model. However, due to the linear dependency of age, period and cohort (Period = Age + Cohort), there is the identification problem, that is, the parameter estimates are not unique. A number of solutions to the identification problem in APC model have been provided in the literature. Fu (2000) introduce a new estimator, the Intrinsic Estimator (IE), which can solve parameter estimates and variance directly. In the first part of this research, computer simulation is conducted to examine the IE, compared with other methodologies. In the second part of this research, data from 1961 to 2005 are used for verifying the validity of APC model in fitting mortality rates, and we analyze the strengths and weaknesses between the APC and Lee-Carter model. The results from our study indicate that the APC model in estimating mortality rates does not show as well as the Lee-Carter model as a whole. However, the APC model performs better than the Lee-Carter model for the elderly mortality rates, but is still needed to be improved in young groups. In the future, it can be considered to combine the APC and Lee-Carter model.