Multiple criteria decision support in organizational and management chosen problems solving

This article presents an introduction to multicriteria decision making using two decision tools: the Analytic Hierarchy Process (AHP) and its generalization to dependence and feedback – the Analytic Network Process (ANP). The discussion involves theoretical aspects of these methods and some examples of their applications, (e.g. the first application of the ANP, in improving of food quality products, in Poland), in organizational and management problems solving. AHP and ANP introduced by Thomas L. Saaty from the University in Pittsburgh, USA. The Analytic Hierarchy Process has been one of the fastest developing mathematical methods over the recent years used for solving multi-criteria decision problems. The AHP is a general theory of measurement based on some mathematical and psychological principles. In that method a hierarchic decision scheme is constructed, by the breaking the problem into decision elements: goal, criteria, subcriteria, sub-subcriteria (…) and decision alternatives. The goal is on the top of hierarchy, whereas alternatives create the lowest level of hierarchy. The importance of every decision element is established, through the pair-wise comparison of elements on each level of the hierarchic structure, with regard to elements on the level above. To do the comparisons it is using the Saaty’s fundamental scale for paired comparisons for the analysis of both quantitative and qualitative variables. The Analytic Network Process (ANP) is a new theory that extends the Analytic Hierarchy Process (AHP). The basic structures are networks, which allow interactions and feedback within the clusters and between the clusters. So, it can be applied for solving more sophisticated decision problems. Authors’ intention was to showing utility of these methods, which can be successfully applied in the solution of any multicriteria enterprise.multiple criteria decision making methods, Analytic Hierarchy Process (AHP), Analytic Network Process (ANP)

Influence of aggregation and measurement scale on ranking a compromise alternative in AHP

Analytic Hierarchy Process (AHP) is one of the most popular multi-attribute decision aid methods. However, within AHP, there are several competing preference measurement scales and aggregation techniques. In this paper, we compare these possibilities using a decision problem with an inherent trade-off between two criteria. A decision-maker has to choose among three alternatives: two extremes and one compromise. Six different measurement scales described previously in the literature and the new proposed logarithmic scale are considered for applying the additive and the multiplicative aggregation techniques. The results are compared with the standard consumer choice theory. We find that with the geometric and power scales a compromise is never selected when aggregation is additive and rarely when aggregation is multiplicative, while the logarithmic scale used with the multiplicative aggregation most often selects the compromise that is desirable by consumer choice theory.AHP, Multi-criteria Decision analysis

A Study of the Digital Divide Evaluation Model for Government Agencies - A Taiwanese Local Government\u27s Perspective

This paper examines the Taiwanese government’s ways of constructing a measurement model and an empirical study of digital divide among government agencies. On the basis of Gowin\u27s Vee structure, this paper first refers to the Grounded Theory in the establishment of the draft list for the measurement of the digital divide in local governments. Furthermore, it constructs five dimensions and 42 measurement factors with an expert questionnaire and the Analytic Hierarchy Process (AHP) for the digital divide evaluation model of government agencies. Finally, this paper measures the actual levels of digital divide in local governments, with the digital divide evaluation model in examining the degrees of digitalization, pros, and cons in association with digital divide. It is hoped that the results would serve as a reference for government agencies of all levels in formulating their digitalization strategies

The Analytic Hierarchy Process: A Mathematical Model for Decision Making Problems

The ability to make the right decision is an asset in many areas and lines of profession including social work, business, national economics, and international security. However, decision makers often have difficulty choosing the best option since they might not have a full understanding of their preferences, or lack a systematic approach to solve the decision making problems at hand. The Analytic Hierarchy Process (AHP) provides a mathematical model that helps the decision makers arrive at the most logical choice, based on their preferences. We investigate the theory of positive, reciprocal matrices, which provides the theoretical justification of the method of the AHP. At its heart, the AHP relies on three principles: Decomposition, Measurement of preferences, and Synthesis. Throughout the first five chapters of this thesis, we use a simple example to illustrate these principles. The last chapter presents a more sophisticated application of the AHP, which in turn illustrates the Analytic Network Process, a generalization of the AHP to systems with dependence and feedback

Influence of aggregation and measurement scale on ranking a compromise alternative in AHP

Analytic Hierarchy Process (AHP) is one of the most popular multi-attribute decision aid methods. However, results depend on the preference measurement sacle and the aggregation technique used. In this paper, we describe a decision problem with an inherent trade-off between two criteria. A decision-maker has to choose among three alternatives: two extremes and one "compromise". Six different measurement scales described previously in the literature and the new proposed logarithmic scale are considered for applying the additive and the multiplicative AHP. The results are compared with the standard consumer choice theory. The geometric and power scales offer no chance (for the additive AHP) and very few chances (for the multiplicative AHP) for a compromise to be selected. The logarithmic scale used with the multiplicative AHP is the most in agreement with the consumer choice theory.: Decision Analysis, Multiple criteria analysis, Utility theory, Additive AHP, Multiplicative AHP, Logarithmic scale

Calculating Weights of Social Capital Index Using Analytic Hierarchy Process

This study aims at identifying and ranking social capital indicators in the measurement model for Vietnam context. The analytic hierarchy process is adopted to explore the relative importance of each dimension in the integrated social capital index. The opinions from the in- depth interviews with experts, scholars and practitioners in social capital theory in Vietnam are employed to calculate the indicators' weights in the model. The empirical findings indicate the superior impact of trust to network in the integrated index. Moreover, bridging and bridging-link are found to be more important than bonding and bonding-link. The result implies the potential of leveraging this resource for the development of individuals and community. Keywords: Economics, Social capital index, Decision making, Analytic Hierarchy Process (AHP), JEL Classifications: A1, C0, K

Risk Assessment of Urban Gas Pipeline Based on Different Unknown Measure Functions

Several risk factors threaten the safety of urban gas pipeline. How to effectively identify various risk factors affecting urban gas pipeline and put forward scientific risk assessment method is the focus in the field of urban safety research. To explore the uncertain factors in the process of gas pipeline risk assessment, and propose a practical assessment method, a three-layer index system for the risk assessment of urban gas pipeline was established using unascertained measure theory, which included 5 first-class evaluation factors and 34 second-class evaluation indexes. Four unascertained measure models (linear, parabolic, exponential and sinusoidal) were constructed, and the unascertained measure values of each evaluation index under four unknown measure function models were calculated. The weight of evaluation factors was determined by Analytic Hierarchy Process (AHP), and the confidence criterion was used for discriminant evaluation. Results demonstrate that the risk assessment models constructed with different measurement functions can effectively reduce the uncertainty of urban gas pipeline risk assessment, but for the same object, the risk level of the linear measurement model in 4# pipeline is lower than other measurement functions, and the risk level of sinusoidal measurement model in 8# pipeline is higher than other measurement functions. Therefore, considering the evaluation results under different measure functions and focusing on monitoring objects with different results is necessary when using unascertained measure theory for risk assessment. The conclusions obtained from this study clarify the application conditions of unascertained measure theory in urban gas pipeline risk assessment, which helps to reduce the uncertainty in the assessment process and improve the accuracy of the assessment results

Influence of aggregation and measurement scale on ranking a compromise alternative in AHP

Author's pre-print version dated 20. December 2009 deposited in Munich Personal RePEc Archive. Final version published by Palgrave Macmillan; available online at http:// www.palgrave-journals.com/Analytic Hierarchy Process (AHP) is one of the most popular multi-attribute decision aid methods. However, within AHP, there are several competing preference measurement scales and aggregation techniques. In this paper, we compare these possibilities using a decision problem with an inherent trade-off between two criteria. A decision-maker has to choose among three alternatives: two extremes and one compromise. Six different measurement scales described previously in the literature and the new proposed logarithmic scale are considered for applying the additive and the multiplicative aggregation techniques. The results are compared with the standard consumer choice theory. We find that with the geometric and power scales a compromise is never selected when aggregation is additive and rarely when aggregation is multiplicative, while the logarithmic scale used with the multiplicative aggregation most often selects the compromise that is desirable by consumer choice theory

A Fuzzy Analytic Hierarchical Method to Reduce Imprecision and Uncertainty in Drilling Operation’s Factor Selection Process for Unidirectional Carbon Fibre Reinforced Plastic Composite Plates

Parametric selection in machining processes is recently understood as a route to reducing waste generation in drilling activities and achieving a robust resource distribution in drilling activities. However, the selection methods dominant in the literature lack competence in reducing uncertainties and imprecision associated with the drilling process. The purpose of this research is to reduce the uncertainty and imprecision in previously analyzed data that used the analytic hierarchy process (AHP) method. This paper adjusts the uncertainty and imprecision by introducing a geometric mean-based fuzzy analytic hierarchy process. The selection method influences the drilling expert's preferences by imposing the fuzzy theory in a triangular member function that converts the crisp numerical values into fuzzy members and adequately suppresses the imprecision and uncertainty in the elements. The thrust force was positioned first in ranking with a FAHP method's weight of 0.415, which matched the literature value of 0.413 for the AHP method. It was found that the use of the FAHP method has corrected the imprecision and uncertainty introduced by the AHP method. It was found that the thrust force and torque were overestimated by or 0.48% and 3.95%, respectively and was accordingly corrected. Besides, no errors were found with the measurement of eccentricity response. Furthermore, the entry delamination, exit delamination and surface roughness were underestimated by -8.11%, -3.33% and -6.96%, respectively, and therefore corrected by the FAHP method. The usefulness of this effort is to enhance cost-effective decisions and the effectiveness in the distribution of scarce drilling resources