"On Modelling Negotiations within a Dynamic Multi-objective Programming Framework: Analysis of Risk Measurement with an Application to Large BOT Projects"

The dynamic and multi-objective programming is used here to establish a risk measurement model. We develop an iterative algorithm and the convergence conditions for the model solution. The results obtained from the model developed here show that the sum of the interactive utility value (IUV) could determine whether or not the interactive relationship is characterized by independence among negotiators. In addition, the numerical example shows that this risk measurement model of the negotiation group can reflect risk assessment by the negotiation group for certain events and can analyze interaction characteristics among negotiators. We show the feasibility and applicability of the model and the exact solution algorithm, and their policy relevance for analyzing BOT projects.

Integrating multicriteria decision analysis and scenario planning : review and extension

Scenario planning and multiple criteria decision analysis (MCDA) are two key management science tools used in strategic planning. In this paper, we explore the integration of these two approaches in a coherent manner, recognizing that each adds value to the implementation of the other. Various approaches that have been adopted for such integration are reviewed, with a primary focus on the process of constructing preferences both within and between scenarios. Biases that may be introduced by inappropriate assumptions during such processes are identified, and used to motivate a framework for integrating MCDA and scenario thinking, based on applying MCDA concepts across a range of "metacriteria" (combinations of scenarios and primary criteria). Within this framework, preferences according to each primary criterion can be expressed in the context of different scenarios. The paper concludes with a hypothetical but non-trivial example of agricultural policy planning in a developing country

Consecutive Sequential Probability Ratio Tests of Multiple Statistical Hypotheses

In this paper, we develop a simple approach for testing multiple statistical hypotheses based on the observations of a number of probability ratios enumerated consecutively with respect to the index of hypotheses. Explicit and tight bounds for the probability of making wrong decisions are obtained for choosing appropriate parameters for the proposed tests. In the special case of testing two hypotheses, our tests reduce to Wald's sequential probability ratio tests.Comment: 29 pages, no figure; The main results of this paper have appeared in Proceedings of SPIE Conferences, Baltimore, Maryland, April 24-27, 201