Interface Evaluation for Open System Architectures

This research develops a deterministic interface evaluation framework (IEF) in support of the principles identified in the Modular Open Systems Approach (MOSA). Interface evaluation in weapon system development requires a Decision Analysis (DA) method capable of handling a continuously growing alternative set and functioning with limited availability of senior decision makers. Value Focused Thinking (VFT) is selected as the best method for addressing the parameters of the framework. Inputs from the Medium Altitude Unmanned Aircraft System program office are used. An initial value threshold is established to guide open interface decisions, based on assessments of 15 historical decision scenarios. Open interface recommendations for the 15 scenarios are compared to previous program decisions, where the model supports past decisions for 5 of 15 scenarios. A sensitivity analysis is then conducted to examine the robustness of the framework to changing weights for cost, schedule, and performance, and the threshold for an open implementation decision. This evaluation framework provides a repeatable method for key interface evaluation that reflects the values of DoD acquisition leadership and the Open System Joint Task Force (OSJTF)

Robustness of Multiple Objective Decision Analysis Preference Functions

This research investigated value and utility functions in multiobjective decision analysis to examine the relationship between them in a military decision making context. The impact of these differences was examined to improve implementation efficiency. The robustness of the decision model was examined with respect to the preference functions to reduce the time burden imposed on the decision maker. Data for decision making in a military context supports the distinction between value and utility functions. Relationships between value and utility functions and risk attitudes were found to be complex. Elicitation error was significantly smaller than the difference between value and utility functions. Risk attitudes were generally neither constant across the domain of the evaluation measure nor consistent between evaluation measures. An improved measure of differences between preference functions, the weighted root means square, is introduced and a goodness of fit criterion established. An improved measure of risk attitudes employing utility functions is developed. Response Surface Methodology was applied to improve the efficiency of decision analysis utility model applications through establishing the robustness of decision models to the preference functions. An algorithm was developed and employs this information to provide a hybrid value-utility model that offers increased elicitation efficiency

Integrating Multiple Criteria Decision-Making Models Into the Decision Support System Framework for Marketing Decisions

The paper focuses on integrating the multiple criteria decision making (MCDM) models within the decision support system (DSS) framework to encourage greater use of these models. A DSS framework and the criteria used for the choice of a model is discussed. Based on these criteria MCDM models generally used in the marketing field are evaluated. The possibility of using a mixture of MCDM models within the DSS framework is also explored. Following this, the role of the MCDM models in DSS is delineated. It is argued that, within the problem-solving process, the confluence of MCDM models and DSS plays a vital role in developing high-quality solutions

Integrating Multiple Criteria Decision-Making Models Into the Decision Support System Framework for Marketing Decisions

The paper focuses on integrating the multiple criteria decision making (MCDM) models within the decision support system (DSS) framework to encourage greater use of these models. A DSS framework and the criteria used for the choice of a model is discussed. Based on these criteria MCDM models generally used in the marketing field are evaluated. The possibility of using a mixture of MCDM models within the DSS framework is also explored. Following this, the role of the MCDM models in DSS is delineated. It is argued that, within the problem-solving process, the confluence of MCDM models and DSS plays a vital role in developing high-quality solutions

A fuzzy hierarchical decision model and its application in networking datacenters and in infrastructure acquisitions and design

According to several studies, an inordinate number of major business decisions to acquire, design, plan, and implement networking infrastructures fail. A networking infrastructure is a collaborative group of telecommunications systems providing services needed for a firm\u27s operations and business growth. The analytical hierarchy process (AHP) is a well established decision-making process used to analyze decisions related to networking infrastructures. AHP is concerned with decomposing complex decisions into a set of factors and solutions. However, AHP has difficulties in handling uncertainty in decision information. This study addressed the research question of solutions to AHP deficiencies. The solutions were accomplished through the development of a model capable of handling decisions with incomplete information and uncertain decision operating environment. This model is based on AHP framework and fuzzy sets theory. Fuzzy sets are sets whose memberships are gradual. A member of a fuzzy set may have a strong, weak, or a moderate membership. The methodology for this study was based primarily on the analytical research design method, which is neither quantitative nor qualitative, but based on mathematical concepts, proofs, and logic. The model\u27s constructs were verified by a simulated practical case study based on current literature and the input of networking experts. To further verify the research objectives, the investigator developed, tested, and validated a software platform. The results showed tangible improvements in analyzing complex networking infrastructure decisions. The ability of this model to analyze decisions with incomplete information and uncertain economic outlook can be employed in the socially important areas such as renewable energy, forest management, and environmental studies to achieve large savings

Does AHP help us make a choice? - An experimental evaluation

In this paper, we use experimental economics methods to test how well Analytic Hierarchy Process (AHP) fares as a choice support system in a real decision problem. AHP provides a ranking that we statistically compare with three additional rankings given by the subjects in the experiment: one at the beginning, one after providing AHP with the necessary pair-wise comparisons and one after learning the ranking provided by AHP. While the rankings vary widely across subjects, we observe that for each individual all four rankings are similar. Hence, subjects are consistent and AHP is, for the most part, able to replicate their rankings. Furthermore, while the rankings are similar, we do find that the AHP ranking helps the decision-makers reformulate their choices by taking into account suggestions made by AHP.Decision analysis, Multiple Criteria Decision Aid, Analytic Hierarchy Process (AHP)

Recruitment and selection processes through an effective GDSS

[[abstract]]This study proposes a group decision support system (GDSS), with multiple criteria to assist in recruitment and selection (R&S) processes of human resources. A two-phase decision-making procedure is first suggested; various techniques involving multiple criteria and group participation are then defined corresponding to each step in the procedure. A wide scope of personnel characteristics is evaluated, and the concept of consensus is enhanced. The procedure recommended herein is expected to be more effective than traditional approaches. In addition, the procedure is implemented on a network-based PC system with web interfaces to support the R&S activities. In the final stage, key personnel at a human resources department of a chemical company in southern Taiwan authenticated the feasibility of the illustrated example.[[notice]]補正完畢[[journaltype]]國內[[incitationindex]]SCI[[incitationindex]]E

First Mover Advantage: An Industrial Buyer Behavioral Perspective

Contemporary order-of-entry research has shifted from econometric investigations to research grounded in quasi-experimental and empirical consumer behavior studies. In the marketing literature, Carpenter and Nakamoto (1988), Kardes and Kalyanaram (1992), and particularly Alpert and Kamins (1992, 1994, 1995) have examined the role of consumer behavior as a potential explanation of first mover advantage. However, little or no research has been devoted to an understanding of pioneer advantage as it relates to industrial markets. This dissertation investigated the effect of order of entry on the attitudes of industrial purchasing managers. Six major hypotheses were proposed to examine the cognitive beliefs, attitudes, and purchasing intentions of industrial purchasing managers as they relate to order of entry. Specifically, this line of inquiry examined the global and multiattribute attitudes of industrial purchasing managers toward three categories of entry: pioneers, early followers, and late entrants. In addition, the research strategy of this study included a measure of global attitudinal preference under ceteris paribus conditions. The research setting for this study consisted of National Association of Purchasing Management members representing strategic business units from Standard Industrial Classifications 35, 36, 37, and 38. The results of this study were based upon a multivariate statistical analysis of the survey responses of 231 industrial purchasing managers. The findings of this study strongly suggest that industrial purchasing managers hold different attitudes toward potential suppliers based upon their entry order. In contrast to previous research in consumer goods settings, industrial purchasing managers were found to extend an attitudinal preference to early followers over pioneers. This attitudinal preference was substantial, statistically significant, and consistent. Survey respondents were also found to associate different subjective attributes with different order-of-entry categories, creating potential trade-offs in the purchasing decision. Pioneer suppliers were perceived to be more technologically sophisticated and more likely to enhance the competitive advantage of the purchasing firm\u27s products. However, survey respondents expressed concerns regarding pioneer quality, reliability, and expense—all factors associated with perceived risk. When these concerns were mitigated, industrial purchasing managers were found to prefer pioneer products

An application of multiattribute decision analysis to the Space Station Freedom program. Case study: Automation and robotics technology evaluation

The results are described of an application of multiattribute analysis to the evaluation of high leverage prototyping technologies in the automation and robotics (A and R) areas that might contribute to the Space Station (SS) Freedom baseline design. An implication is that high leverage prototyping is beneficial to the SS Freedom Program as a means for transferring technology from the advanced development program to the baseline program. The process also highlights the tradeoffs to be made between subsidizing high value, low risk technology development versus high value, high risk technology developments. Twenty one A and R Technology tasks spanning a diverse array of technical concepts were evaluated using multiattribute decision analysis. Because of large uncertainties associated with characterizing the technologies, the methodology was modified to incorporate uncertainty. Eight attributes affected the rankings: initial cost, operation cost, crew productivity, safety, resource requirements, growth potential, and spinoff potential. The four attributes of initial cost, operations cost, crew productivity, and safety affected the rankings the most