The model of financial support for the sustainable development of agriculture

The article is devoted to the importance of implementing methodological approaches and methods of evaluating an economic system effectiveness in the field of finance to optimize operational decision-making based on modeling. Expert tools are considered, including: databases and knowledge, systems for modeling economic situations, intelligent decision-making systems. A simulation model has been built that covers the full range of relationships between blocks and indicators-factors that determine the essential characteristics of the economic development of the territory, which made it possible to find out the proportional dependence of the subsystems of financial support for agriculture development

Knowledge dependencies in fuzzy information systems evaluation

Experience and research within the field of Information Systems Evaluation (ISE), has traditionally centered on providing tools and techniques for investment justification and appraisal, based upon explicit knowledge which encodes financial and other direct situational factors (such as accounting, costing and risk metrics). However, such approaches tend not to include additional causal interdependencies that are based upon tacit knowledge and are inherent within such a decision-making task. The authors show the results of applying a cognitive mapping approach, in the guise of a Fuzzy Cognitive Mapping (FCM) simulation, i.e. Fuzzy Information Systems Evaluation (F-ISE), in order to highlight the usefulness of applying such a technique. The authors highlight those contingent and necessary knowledge dependencies, in an exploratory sense, which relate to the investment appraisal decision-making task, in terms of the interplay between tacit and explicit knowledge, in this regard

From Social Simulation to Integrative System Design

As the recent financial crisis showed, today there is a strong need to gain "ecological perspective" of all relevant interactions in socio-economic-techno-environmental systems. For this, we suggested to set-up a network of Centers for integrative systems design, which shall be able to run all potentially relevant scenarios, identify causality chains, explore feedback and cascading effects for a number of model variants, and determine the reliability of their implications (given the validity of the underlying models). They will be able to detect possible negative side effect of policy decisions, before they occur. The Centers belonging to this network of Integrative Systems Design Centers would be focused on a particular field, but they would be part of an attempt to eventually cover all relevant areas of society and economy and integrate them within a "Living Earth Simulator". The results of all research activities of such Centers would be turned into informative input for political Decision Arenas. For example, Crisis Observatories (for financial instabilities, shortages of resources, environmental change, conflict, spreading of diseases, etc.) would be connected with such Decision Arenas for the purpose of visualization, in order to make complex interdependencies understandable to scientists, decision-makers, and the general public.Comment: 34 pages, Visioneer White Paper, see http://www.visioneer.ethz.c

Workflow Patterns for Business Process Modeling

For its reuse advantages, workflow patterns (e.g., control flow patterns, data patterns, resource patterns) are increasingly attracting the interest of both researchers and vendors. Frequently, business process or workflow models can be assembeled out of a set of recurrent process fragments (or recurrent business functions), each of them having generic semantics that can be described as a pattern. To our best knowledge, so far, there has been no (empirical) work evidencing the existence of such recurrent patterns in real workflow applications. Thus, in this paper we elaborate the frequency with which certain patterns occur in practice. Furthermore, we investigate completeness of workflow patterns (based on recurrent functions) with respect to their ability to capture a large variety of business processes

Multi-agent knowledge integration mechanism using particle swarm optimization

This is the post-print version of the final paper published in Technological Forecasting and Social Change. The published article is available from the link below. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. Copyright @ 2011 Elsevier B.V.Unstructured group decision-making is burdened with several central difficulties: unifying the knowledge of multiple experts in an unbiased manner and computational inefficiencies. In addition, a proper means of storing such unified knowledge for later use has not yet been established. Storage difficulties stem from of the integration of the logic underlying multiple experts' decision-making processes and the structured quantification of the impact of each opinion on the final product. To address these difficulties, this paper proposes a novel approach called the multiple agent-based knowledge integration mechanism (MAKIM), in which a fuzzy cognitive map (FCM) is used as a knowledge representation and storage vehicle. In this approach, we use particle swarm optimization (PSO) to adjust causal relationships and causality coefficients from the perspective of global optimization. Once an optimized FCM is constructed an agent based model (ABM) is applied to the inference of the FCM to solve real world problem. The final aggregate knowledge is stored in FCM form and is used to produce proper inference results for other target problems. To test the validity of our approach, we applied MAKIM to a real-world group decision-making problem, an IT project risk assessment, and found MAKIM to be statistically robust.Ministry of Education, Science and Technology (Korea

Value-oriented process modeling - towards a financial perspective on business process redesign

To date, typical process modeling approaches put a strong emphasis on describing behavioral aspects of business operations. However, they often neglect value-related information. Yet, such information is of key importance to strategic decisionmaking, for instance in the context of process improvement or business engineering. In this paper we propose a valueoriented approach to business process modeling based on key concepts and metrics from operations and financial management. A simple case study suggests that our approach facilitates managerial decision-making in the context of process re-design