628 research outputs found

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

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    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)

    By force or by fraud: optimizing U.S. information strategy with deception

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    Military deception (MILDEC) operations have a long and illustrious place in America's battlefield history. To great effect, MILDEC has enabled countless victories in every U.S. conflict since the Revolutionary War. However, the United States has allowed its deception capability to atrophy. Possible explanations for our MILDEC divestiture range from structural insufficiencies to an ethical framework that emphasizes truth and transparency. Simultaneously, the onset of the Information Age has leveled the playing field between state and non-state actors (NSA) and proved that lasting victory cannot be achieved by force alone. Yet, due in part to the difficulty involved in quantifiably measuring information strategy, the contemporary military's acceptance and understanding of information warfare has been limited. This necessitates the re-examination of U.S. information strategy formulation to address more effectively the challenges and complexities encountered in the human domain. To overcome this impediment, this thesis examines the intangible aspects of information warfare and proposes a structured decision-making tool capable of generating precise computations of optimal information strategies. By Force or by Fraud is a quantitative assessment of MILDEC's utility on the modern battlefield that is qualitatively tested against historic cases of information warfare.http://archive.org/details/byforceorbyfraud1094549457Major, United States ArmyMajor, United States ArmyApproved for public release; distribution is unlimited

    A Hybrid MCDM Approach to Transshipment Port Selection

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    Port selection is an intrinsic supply-chain problem that has substantial impact on development of local economies. Shipping business environment developed into complex system where decision making is derived from uncertain and incomplete data. In this study we present a conceptual integrated Multi-Criteria Decision solution to transshipment port selection problem based on Best-Worst MCDM and Artificial Bee Colony Algorithm. Through literature review and expert analysis, 50 relevant criteria have been identified as relevant to the transshipment port selection problem. Decision makers within liner shipping companies evaluate transshipment port selection criteria and establish ranking that is used to determine crisp solution with lowest consistency ratio. ABC based algorithm is used to reduce computational complexity and deliver a single optimal solution by solving both objective and constraint violation functions

    Decision-making methods in engineering design: a designer-oriented approach

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    The use of decisional methods for the solution of engineering design problems has to be tackled on a "human" viewpoint. Hence, fundamental is the identification of design issues and needs that become a designer oriented viewpoint. Decision-based methods are systematically classified in MCDM methods, Structured Design methods and Problem Structuring methods. The results are organised in order to provide a first reference for the designer in a preliminary selection of decision-based methods. The paper shows the heterogeneous use of decision-based methods, traditionally expected to solve only some specific design problems, which have been used also in different design contexts. Moreover, several design issues, which emerged from the review process, have been pointed out and discussed accordingly. This review provided useful results for the enlargement of the state of the art on Decision Based Design methods in engineering design contexts

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

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    Author's pre-print version dated 2. August 2010 deposited in Munich Personal RePEc Archive. Final version published by Palgrave Macmillan; available online at http:// www.palgrave-journals.com/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

    The Analytic Hierarchy Process: A Tutorial for Use in Prioritizing Forest Road Investments to Minimize Environmental Effects

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    The prioritization of road maintenance projects is an important forest engineering task due to limited budgets and competing investment needs. Large investments are made each year to maintain and upgrade forest road networks to meet economic and environmental goals. Many models and guidelines are available for single-criteria analysis of forest roads, however we have found no method for multi-criteria analysis. Additionally, even single criteria approaches often rely on expert judgment to inform models of user preferences and priorities. These preferences are used to make tradeoffs between alternatives that contain data that are physical and biological, quantitative and qualitative, and measured on many different scales. The Analytic Hierarchy Process (AHP) has the potential to provide a consistent approach to the ranking of forest road investments based on multiple criteria. AHP was specifically developed to provide a consistent, quantifiable approach to problems involving multi-criteria analysis, but it has not been applied to road management. AHP is composed of four steps: the hierarchical decomposition of a problem into a goal, objectives, and sub-objectives; the use of a pairwise comparison technique to determine user preferences; the scaling of attribute values for each of the alternatives; and the ranking of alternatives. The road investment problem differs from traditional AHP applications in that potentially thousands of alternatives are compared at one time. We discuss the AHP methodology including the foundations, assumptions, and potential for use in prioritizing forest road investments to meet economic and environmental goals, drawing from an example from the Oregon State University College Forests

    Integrating Assessment Methods in the Development of ML-based Business Models for Manufacturing

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    The use of machine learning promises great potential along the entire value chain of manufacturing companies. Many companies have already recognized the resulting opportunities for increasing enterprise value and are developing their machine learning applications for the production environment. However, despite these efforts, many of the solutions developed fail in the market. Especially small- and medium-sized enterprises have difficulties developing suitable business models for their technical applications. These difficulties arise because companies do not evaluate their business projects sufficiently during the development phases. As a result, unpromising projects are not recognized until late in the development process and thus cause high sunk costs. This paper presents an approach for integrating assessment methods into developing machine learning- driven business models for production. Due to the diametric evolution of information availability and uncertainty during the business model development process, various methods and tools can be used for the assessment depending on the current phase. For this purpose, existing assessment methods are evaluated and contrasted regarding their suitability concerning machine learning-based business models for production. Afterwards, three approaches for the different planning phases of business model development (strategic, tactical, operational) are presented in this paper

    An AHP Framework to Evaluate Barriers and Potential Tensions to Green Supply Chain Management in the Food and Beverage Industry

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    With an increasing awareness of climate change and the need for sustainable processes, a growing number of studies have addressed green supply chain management (GSCM), its drivers, barriers, and implementation frameworks. However, despite the importance of environmental practices, industries are reluctant to implement GSCM activities, as many obstacles can arise while initiating GSCM in traditional supply chain management (TSCM). The previous literature review indicated substantial research on the barriers that hinder the adoption of green activities. To the best of our knowledge, no previous research has assessed the tensions and conflicts that may arise among collaborating actors, which can also hinder the adoption of environmental business practices. In particular, there is a notable gap in research that investigates the green- supply-chain issues in the Egyptian food and beverage manufacturing sector. In this paper, we went a step ahead to investigate these issues and to explore how GSCM barriers cause tensions among collaborating actors. Hence, the purpose of this paper is to investigate the barriers and tensions that impede the implementation of GSCM in the Egyptian food and beverage industry (FBI).  In our methodology, we targeted three large food and beverage multinational companies located in Egypt. Barriers and types of tensions were identified through the literature review. Data collection consisted of three phases. For the primary source of data, a qualitative method was utilized for semi-structured interviews, followed by a questionnaire survey. Furthermore, a decision group was formed to collect and validate the data. Using the analytic hierarchy process (AHP), this study categorised the identified barriers based on the relevant type of tension and explored how such barriers can create tension among various stakeholders. Thirty-nine barriers and 11 types of tension were identified through the literature review and discussion with experts. Of the total number of identified barriers, 18 were identified as common. Based on the AHP results, the category of economic tensions had the most importance. The barrier related to inflation and the currency exchange rate was the most significant among the 18 barriers and was the main driver of economic tensions. Our findings suggest that the economic instability of countries can affect the implementation of GSCM.  This is the first study that combines barriers and tensions among stakeholders as impediments toward adopting green environmental practices. This study provides a new approach to the literature, giving insight into the tensions that could delay or prevent the adoption of green business activities, an approach that could be a scientific breakthrough for upcoming studies. Finally, this study can help the Egyptian FBI to identify the main issues that could hinder the transition from TSCM to GSCM. Keywords: Green supply chain management; analytical hierarchy process; barrier analysis; tensions; food and beverage industry DOI: 10.7176/EJBM/13-6-01 Publication date:March 31st 202
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