This study develops and uses a scale to identify the innovativeness and positive attitudes of entrepreneurs towards entrepreneurship. The reliability of the scale is found to be high, and based on random sample of 78 entrepreneurs the most and the least innovative characteristics they have and the most and the least positive attitudes they have towards entrepreneurship are revealed. Furthermore, the effects of entrepreneurs' demographic characteristics on these measures are investigated based on hypothesis tests.
Contingency logistic supply chain design and performance are very important for rare events such as natural disasters, terrorist attacks, and other emergency conditions. Although there is ample work on the evaluation of supply chain systems in terms of their profitability and efficiency, there is little work on the effectiveness of the response time of the supply chain, as well as quantitative measures for the robustness of the design and the reliability of the supply chain. Depending on the contingency, the perceived risk may be different for different situations. The level of risk aversion is dependent on the decision maker and the uncertainties associated with the supply and demand for the contingency. In this study the risk associated with shortages due to the uncertainties in supply and demand in the supply chain are modelled using distortion. In addition, a numerical analysis is performed and the sensitivity of the parameters in a contingency logistic supply chain is analysed. Methods to improve the effectiveness of the contingency operation are examined by efficiently allocating available resources, supplies, and time, as well as modelling the decision maker's perception associated with the failure of a particular node. An array of optimization models are formulated and discussed. Each of these models enables a decision maker to examine a variety of trade-offs in a contingency logistics supply chain. For example, one model examines the acquisition of mitigation strategies and the reallocation of resources while taking into consideration the decision maker's risk aversion. The main contribution of this paper is the establishment of an analysis framework for modelling and analysing the risk and reliability of contingency logistic supply chains.
This paper provides an approach for assessing the uncertainty associated with the estimate of the availability of a two-state repairable system. During the design stage it is often necessary to allocate scarce testing resources among various components in an efficient manner. Although there are a variety of importance and uncertainty measures for the reliability of a system, there are limited measures for systems availability. This study attempts to fill the gaps on availability importance measures and provide insights for techniques to reduce the variance of a system-level availability estimate efficiently. The variance importance measure is constructed such that it provides a measure of the improvement in the variance of the system level availability estimate through the reduction of the variance of the various component availability estimates. In addition, a cost model is developed that trades-off cost and uncertainty. The measure is illustrated for five common system structures. Monte Carlo Simulation is used to illustrate the use of the assessment tools on a specific problem. Observations conclude that results are consistent with reliability importance measures.
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