Selecting projects in a portfolio using risk and ranking

There are three dimensions in project management: time, cost and performance. Risk is a characteristic related to the previous dimensions and their relationships. A risk equation is proposed based on the nature of the uncertainty associated to each dimension as well as the relationship between the uncertainties. A ranking equation that is able to prioritise projects is proposed and discussed. The problem solved here is which projects to select in a given portfolio of projects. The model is implemented in a group decision support system (GDSS) which can guide decisionmakers in their decision process. However, the system is not intended as a substitution of the decisionmaker task, but merely as an aid. The methodology used is analysis of the equations proposed and trial and error based on examples. This paper’s main contribution is the risk equation and the ranking equation

ECONOMIC ANALYSIS AND EFFICIENCY IN PUBLIC EXPENDITURE

Benefit-Cost Analysis involves several steps: development of a program information structure (product categories), estimating the production function, pricing benefits and costs, adjusting for opportunity costs, choice of investment criteria, and incorporating uncertainty. Each step involves conflicts of interest that can only be resolved by political (collective) choice of property rights assigning opportunities to the various interest groups. The rules of benefit-cost analysis for public expenditure are equivalent of private property rights established by legislative and court decisions for the market economy. The traditional separation of technical analysis and political choice is not longer tenable. Theory and practice point to a more interactive, iterative relationship between analysts and politicians.Public Economics,

[[alternative]]Stochastic Time-Cost Tradeoff Model under Uncertainty of Project Financing

計畫編號：NSC93-2211-E032-019研究期間：200408~200507研究經費：316,000[[sponsorship]]行政院國家科學委員

Learning to Predict the Wisdom of Crowds

The problem of "approximating the crowd" is that of estimating the crowd's majority opinion by querying only a subset of it. Algorithms that approximate the crowd can intelligently stretch a limited budget for a crowdsourcing task. We present an algorithm, "CrowdSense," that works in an online fashion to dynamically sample subsets of labelers based on an exploration/exploitation criterion. The algorithm produces a weighted combination of a subset of the labelers' votes that approximates the crowd's opinion.Comment: Presented at Collective Intelligence conference, 2012 (arXiv:1204.2991

Web Note No. 18

In a recent analysis comparing the current oil production tax, More Alaska Production Act (MAPA, also known as SB 21) to the tax it replaced, Alaska’s Clear and Equitable Share (ACES), Scott Goldsmith, professor emeritus of economics at ISER, found that MAPA would produce higher revenues in the future, if changing to MAPA causes producers to make investments that lead to more production than would have occurred under ACES.2 Professor Goldsmith did not advocate for either tax, but projected effects of each under a range of different future oil prices, production rates, and costs. He noted that comparative revenues are highly sensitive to future costs and oil prices. Oil prices are notoriously difficult to forecast. Future North Slope oil production, as well as lease costs that can be deducted from producers’ tax liabilities under both ACES and MAPA, are also highly uncertain. Proponents of either MAPA or ACES appear to make assumptions about prices, production, and costs that support their arguments. Given the inherent uncertainty about oil prices, new production, and expenditures for capital and operating costs, what assumptions would be most reasonable to make for assessing outcomes of the tax regimes? This note critically examines the relevant assumptions for projecting tax outcomes, and explores how the different taxes compare under a set of assumptions that seem most reasonable, given our best current information. The comparisons address not only the amount of revenue the state would collect, but also how the taxes differently share risk between the industry and the state, and administrative issues affecting the nature of the relationship between the oil industry and state government. The analysis also places the debate about MAPA vs. ACES in the longer term context of Alaska oil production taxes, comparing MAPA and ACES to the original petroleum profits tax (PPT) that preceded ACES, and to the old severance tax PPT replaced.Northrim Bank

Risk-Based Decision Making Support for Construction Corporate Resource Management

Competitive bidding typically challenges contractors to stay in business by reducing contingency and limiting profit margin, which imposes more prudent resource utilization and allocation decisions during both planning and construction phases of projects. Many of these decisions must be made considering uncertainties that affect resource production and construction performance through several factors such as weather, managerial practices, job-type, and market conditions, etc. Construction decision makers will therefore have varied approaches to deal with these uncertainties based on their risk utility or perception. This research presents the development of a model for investigating the impact of risk-based approaches on construction network outcomes. The current study contributes to development of a model that enables corporate managers to understand the impact of different resource utilization and sharing policies on the overall outcome of their project and to select among optimum planning solutions that satisfy their profit margin and capital limitations. This research also enables corporate decision makers to have more realistic estimates for the profitability of their company, and understand consequences of their decisions in short and long term. Findings of this research provide decision makers with different solutions for profitability of their corporation based on non-dominated optimal time-cost trade-offs, and also broader perspective on how overall time and budget limitations, as well as risk perceptions, can affect the decision-making process. The model is verified and the results are validated through acquiring data from actual large scale construction projects in South Florida