Appropriate Models In Decision Support Systems For River Basin Management

In recent years, new ideas and techniques appear very quickly, like sustainability, adaptive management, Geographic Information System, Remote Sensing and participations of new stakeholders, which contribute a lot to the development of decision support systems in river basin management. However, the role of models still needs to be emphasized, especially for model-based decision support systems. This paper aims to find appropriate models for decision support systems. An appropriate system is defined as ‘the system can produce final outputs which enable the decision makers to distinguish different river engineering measures according to the current problem’. An appropriateness framework is proposed mainly based on uncertainty and sensitivity analysis. A flood risk model is used, as a part of the Dutch River Meuse DSS to investigate whether the appropriate framework works. The results showed that the proposed approach is applicable and helpful to find appropriate models

Solutions for decision support in university management

The paper proposes an overview of decision support systems in order to define the role of a system to assist decision in university management. The authors present new technologies and the basic concepts of multidimensional data analysis using models of business processes within the universities. Based on information provided by scientific literature and on the authors’ experience, the study aims to define selection criteria in choosing a development environment for designing a support system dedicated to university management. The contributions consist in designing a data warehouse model and models of OLAP analysis to assist decision in university management.university management, decision support, multidimensional analysis, data warehouse, OLAP

Decision-focussed resource modelling for design decision support

Resource management including resource allocation, levelling, configuration and monitoring has been recognised as critical to design decision making. It has received increasing research interests in recent years. Different definitions, models and systems have been developed and published in literature. One common issue with existing research is that the resource modelling has focussed on the information view of resources. A few acknowledged the importance of resource capability to design management, but none has addressed the evaluation analysis of resource fitness to effectively support design decisions. This paper proposes a decision-focused resource model framework that addresses the combination of resource evaluation with resource information from multiple perspectives. A resource management system constructed on the resource model framework can provide functions for design engineers to efficiently search and retrieve the best fit resources (based on the evaluation results) to meet decision requirements. Thus, the system has the potential to provide improved decision making performance compared with existing resource management systems

An Evolution of Corporate Software Support Systems

This paper is a brief literature survey on Software Support Systems (SSSs) and Knowledge Management (KM). This paper aims to evaluate strategic decision making perspective where enterprise information and knowledge management plays a vital role. For this evaluation, Software Support Systems (SSSs) and Knowledge Management (KM) which helps in selecting different types of support systems and human factors that affect adoption of such computer based systems in organizations are reviewed. This paper helps to analyze different types of the software support systems and system adoption concepts for the enterprises. This paper also includes concepts related to the Knowledge Management, which helps organizations to learn. Organizations knowledge and the support systems help the enterprises to take strategic decisions. Concerned literature describes Software Support Systems (SSSs) as Corporate Portals (CPs), Decision Support Systems (DSSs), Group Decision Support Systems (GDSSs), Computerized Decision Support Systems, and Adaptive Decision Support System (ADSSs). In addition, Technology Acceptance Model (TAM) that analyzes factors which would affect peoples in the enterprises is included. The factors, such as individual perception, ease of use and usefulness are analyzed. Keywords: Software Support Systems, Knowledge Management, Technology Acceptance Models

How Feedback Can Improve Managerial Evaluations of Model-based Marketing Decision Support Systems

Marketing managers often provide much poorer evaluations of model-based marketing decision support systems (MDSSs) than are warranted by the objective performance of those systems. We show that a reason for this discrepant evaluation may be that MDSSs are often not designed to help users understand and internalize the underlying factors driving the MDSS results and related recommendations. Thus, there is likely to be a gap between a marketing manager’s mental model and the decision model embedded in the MDSS. We suggest that this gap is an important reason for the poor subjective evaluations of MDSSs, even when the MDSSs are of high objective quality, ultimately resulting in unreasonably low levels of MDSS adoption and use. We propose that to have impact, an MDSS should not only be of high objective quality, but should also help reduce any mental model-MDSS model gap. We evaluate two design characteristics that together lead model-users to update their mental models and reduce the mental model-MDSS gap, resulting in better MDSS evaluations: providing feedback on the upside potential for performance improvement and providing specific suggestions for corrective actions to better align the user's mental model with the MDSS. We hypothesize that, in tandem, these two types of MDSS feedback induce marketing managers to update their mental models, a process we call deep learning, whereas individually, these two types of feedback will have much smaller effects on deep learning. We validate our framework in an experimental setting, using a realistic MDSS in the context of a direct marketing decision problem. We then discuss how our findings can lead to design improvements and better returns on investments in MDSSs such as CRM systems, Revenue Management systems, pricing decision support systems, and the like.Learning;Feedback;Marketing Decision Models;Marketing Decision Support Systems;Marketing Information Systems

Decision Support System for Managing and Determining International Class Program

Indonesian higher education today is faced with serious challenges that will threaten the existence of some universities. An increasing international competition will require that universities take a progressive approach to attract enough students to ensure their survival. One way the universities must improve is in the quality of their administration management. While universities in Indonesia do not compare well internationally, steps can be taken to improve the quality. There are potential lessons to be learned from corporate experience in quality control management. Decision-making in the field of academic resource planning involves extensive analysis of many data originating from multiple systems. Academic resource planning management is concerned with management resources in order to effectively support the university’s educational framework (such as offered degrees, enrolment and retention, resources teaching, course structure and curriculum). We propose a methodology for managing and determining the proposed International class based on many criteria of academic performance in university. The approach has been implemented as a decision support system allowing evaluation of various criteria and scenarios. The system combines two different methods in decision support system: Analytical hierarchy Process (AHP) and linear weightage model, the proposed model uses the AHP pairwise comparisons and the measure scale to generate the weights for the criteria which are much better and guarantee more fairly preference of criteria. Applying the system as decision-support facility for the management has resulted in significant acceleration of planning procedures and implementation, raised the overall effectiveness with respect to the underlying methodology and ultimately enabled more efficient academic administration

XWeB: the XML Warehouse Benchmark

With the emergence of XML as a standard for representing business data, new decision support applications are being developed. These XML data warehouses aim at supporting On-Line Analytical Processing (OLAP) operations that manipulate irregular XML data. To ensure feasibility of these new tools, important performance issues must be addressed. Performance is customarily assessed with the help of benchmarks. However, decision support benchmarks do not currently support XML features. In this paper, we introduce the XML Warehouse Benchmark (XWeB), which aims at filling this gap. XWeB derives from the relational decision support benchmark TPC-H. It is mainly composed of a test data warehouse that is based on a unified reference model for XML warehouses and that features XML-specific structures, and its associate XQuery decision support workload. XWeB's usage is illustrated by experiments on several XML database management systems

Dutch Experience in Irrigation Water Management Modelling

Modeling the soil-water-crop atmosphere system to improve agricultural water management in arid zones (SWATRE); Groundwater approach to drainage design in irrigated agriculture (SGMP); Computer Program for flume and weir design (FLUME 3.0); A hydrodynamic model in the design of operational controllers for water systems (MODIS/MATLAB); Decision support simulation model for water management at a regional and national scale (SIWARE); Management of water delivery systems (RIBASIM/OMIS); A water allocation, scheduling, and monitoring program (WASAM); and Irrigation agencies, farmers and computational decision support tools

HYPER MODEL MANAGEMENT SYSTEMS

In this paper we study the integration of Model Management and Hypertext systems to produce a Hyper Model Management System (HMMS). Model Management Systems constitute a class of software that is designed to support the construction, storage, retrieval, and use of models in the context of decision support systems (DSS). Hypertext systems allow users to split information into data fragments which the user cart browse to find information by taking non-linear paths in computer based texts. It has been suggested that DSSs should be conceived as environments which support decision making. We support the view that such environments can be readily provided for the subtask of model management by hypertext systems. The different kinds of model knowledge can be captured within different types of hypertext nodes and the relationships among these can be maintained by hypertext links. In this paper we describe some aspects of model management where hypertext will have a significant impact. However, plain hypertext is ineffective in dealing with the dynamic nature of information in model management tasks where data is revised, models executed, and reports are created on the fly. Dynamic domains require dynamic hypertexts. In this paper we also study the requirements for dynamic hypertexts. These can be satisfied within the class of generalized hypertext systems by using special hypertext nodes and links which we describe. We explore different architectures to integrate MMS and Hypertext systems to obtain HMMSs. This paper emphasizes the need for a shift to integrating Model Management and hypertext technologies.Information Systems Working Papers Serie