The network economy is a term for today’s global relationship among economic elements characterized by massive connectivity. The central act of the new era is to connect everything to everything in deep web networks at many levels of mutually interdependent relations, where resources and activities are shared, markets are enlarged and costs and risk are reduced. Network systems contain both positive and negative feedback. A variety of feedback processes create complex system behavior. For such a network the Analytic Network Process (ANP) approach seems to be very appropriate. The ANP method makes it possible to deal systematically with all kinds of dependence and feedback in the system. Dynamic models try to reflect changes in real or simulated time and take into account that the network model components are constantly evolving. Dynamic models use concepts of state variables, flows, and feedback processes. The Dynamic Network Process (DNP) is an extension of ANP that can deal with time dependent priorities in a networked economy.

Over the past few decades, innovations in Information and Communication Technologies (ICT) have led to a significant increase in the complexity of enterprise information systems. This has led to new challenges for enterprise architects, systems engineers, business managers and other decision makers who must cope with the complexity of business plans and processes (particularly automated engineering processes). In order to better manage this complexity, the Business Rule Group (BRG) has put forth the Business Motivation Model (BMM). The original BMM uses a SWOT (Strength, Weakness, Opportunity, and Threat) decision analysis approach. However, the SWOT framework contains significant limitations with respect to decision making and ICT risks, hampering the decision making ability of enterprise architects, business managers, engineers, and other decision makers. The AHP (Analytic Hierarchy Process) and ANP (Analytic Network Process) are among the most widely used decision making tools: they commonly implement a Benefit — Opportunity — Cost — Risk (BOCR) analysis to improve the effectiveness of business decision making. A new approach is put forth that replaces the original SWOT assessment with an ANP-based BOCR analysis. As well, the original BMM is modified and applied in a Component Architecture Framework (CAF).

Sand and gravel are important raw materials which are needed for many civil engineering projects. Due to economic reasons, sand and gravel pits are frequently located in the periphery of metropolitan areas which are often subject to competing land-use interests. As a contribution to land-use conflict solving, the Analytic Hierarchy Process (AHP) is applied within a Geographic Information System (GIS) environment. Two AHP preference matrix scenario constellations are evaluated and their results are used to create a land-use conflict map.

Municipal economy problems are of a complex nature. Existing requirements for sustainable development make us apply various criteria while solving these problems. These can, for example, include economic, financial, social and environmental criteria. To handle them effectively, multi-criteria analysis should be applied. Decisions about heat production and delivery systems belong to such multidisciplinary problems. They were usually resolved in the past using classical numerical methodology that took into account only the technical and economic merits of the various alternatives. By applying multi-criteria tools instead it is possible to obtain more realistic results and make more effective decisions. The Analytical Hierarchy Process (AHP) seems to be a good alternative to fill the existing gap between decision-making as it is actually practiced and the traditional methods when applied to selecting district heating (DH) systems. This paper presents such an application. Our application is to select the best heat energy source for a DH system for a medium sized city located in Poland. Our results led to an interesting conclusion with regard to the best heat energy source. Our results suggest that intensifying the effort to make widespread the use of more efficient, but financially more costly, energy sources is the best.

This paper reports an on-going application of the Analytic Network Process (ANP) in the context of a non-profit organization: The Latin American Studies Association (LASA). This institution organizes a large international conference every eighteen months and needs to estimate conference attendance in advance (for logistic purposes) as well as selecting a host city where the combination of hotel infrastructure, conference costs, and so on, makes it a sound financial choice. In this paper, ANP will be used to: first, create a model to predict the relative number of attendees to the forthcoming 2009 LASA conference; and second, to create a Benefit-Cost-Risk (BCR) model to select the most suitable Latin American city as the conference site. This paper shows how the combination of these two ANP models, one for prediction and one for selection, can be used together for effective decision-making.

The objective of this paper is to show that the Analytic Hierarchy Process (AHP) is a very powerful methodology for designing shiftwork schedules. Manufacturing, mining and other large industrial operations often run around the clock and their employees report for work in shifts. The huge number of variables and the amount of knowledge that needs to be structured, integrated and synthesized forces the need for a system analysis process that is able to deal with such complexity.

Work flexibility is a very important issue in Chile and in the rest of the world. One of the main problems of a flexible work process is handling shiftwork systems with their economic, health, social, family and environmental consequences.

Saudi Arabia every year receives more than two million Muslims from all over the world to perform the Hajj, the Muslim pilgrimage to Makkah. It must take place during a specific period of the year in a specific and limited space. In spite of the effort government agencies devote to this event, a variety of disasters usually take place each year. As the number of pilgrims is increasing every year the problem is becoming an alarming one. More and more resources are allocated to eliminate the occurrence of such disasters. More than one strategy has been proposed to make the Hajj as safe as possible. Knowing that the problem is very complex as it involves numerous actors, and many entangled criteria and elements, the question is which strategy is best. This paper presents the Analytic Network Process as a sound methodology for structuring the Hajj problem by designing an analytical model to find which strategy to focus on to make the pilgrimage as safe as possible.

Supplier selection is one of the most crucial activities performed by organizations because of its strategic importance. Supplier selection is a multi-objective problem involving both quantitative and qualitative criteria. Over the years a number of quantitative approaches have been tried. Although the Analytic Hierarchy Process (AHP) has previously been used in supplier selection problems, one major weakness of the application-oriented AHP literature is that it tends to focus on the mechanics of AHP instead of on the theoretical and practical implications associated with finding a solution. Though it is one of the most extensively used Multiple Criteria Decision Analysis methodologies, our literature search indicated that most studies found the best solution and stopped there, ignoring sensitivity analysis. Performing sensitivity analysis is very important for practical decision making, sometimes even as important as finding the best solution. In this paper for the first time a comprehensive application of AHP for a real-world case is presented along with sensitivity analysis in choosing the best suppliers for a Turkish construction company. As a result of this study the company decided to allocate the order quantities between the two top suppliers.

Infrastruture facilities in many countries have been repeatedly subjected to natural or human-induced disasters. International aid institutions, such as the United Nations Development Program (UNDP), United States Aid International Development (USAID), Japan International Cooperation Agency (JICA) and the World Bank International Aid Development (IDA), are endeavoring to assist in the reconstruction of devastated countries. Development institutions normally face the problem of selecting and implementing relevant priority infrastructure projects that are needed in various sectors. Usually there are also several key local players in the decision making process. In many cases, these main decision makers have contradictory objectives that lead to conflict and thereby hamper the reconstruction process. In response to this kind of problem, an effective approach has been developed within the field of Multiple Criteria Decision Analysis (MCDA), the Analytical Hierarchy Process (AHP), that can assist decision makers in prioritizing projects to meet specified goals and objectives. Using the AHP approach, the problem of selecting infrastructure projects is dealt with systematically when applying this flexible MCDA technique. This approach takes into account possible uncertainties and social discrepancies, and can use the judgments of the decision makers themselves when there is a lack of technical or historical data. Decision makers from international financial aid institutions, donor agencies, governmental and the local community can utilize this proposed approach.

Many countries with health insurance systems conduct periodic payment standards reform. How to reach consensus in setting payment standards among different specialties with different agendas has become a critical issue. The purpose of this study is to construct an analytic hierarchy process (AHP) model to obtain judgments from experts about the importance of “factors related to establishing payment standards in the national health insurance program”. Under this goal, the first tier contains four evaluation aspects, and the second tier contains sixteen evaluation criteria divided into four groups. The AHP model was then used to collect and combine the opinions of experts through an empirical study. The results can be directly used to formulate standard values as the basis for establishing payment standards. The results of our study strongly support that an AHP model is effective in forming a consensus among surgical specialists.