An exploratory study of the value of pretraining end-user participation

Although software training is widely seen as an essential contributor to the productive use of computers in organizations, research has not focused on identifying the processes through which software trainers assess end users' training requirements. This research draws from self-regulation theories to examine the impacts of pretraining end-user participation on the outcomes of software training. Self-regulation theories aim to explain why individuals behave in a certain manner in an organizational context. Pretraining end-user participation consists of a pretraining interview designed to learn the needs of the trainee, and to gain insights into a training design that can make learning the target software more relevant to the trainee. The context of the study was a training programme for a database retrieval software package in a medium-sized manufacturing company. Approximately half the trainees were involved in the pretraining interview process. Trainees also received one of two training approaches, either applications-based (relevant problem focused) or construct-based (generic training approach) training. Data were gathered from questionnaires, quizzes and interviews. Although no clear differences were found, the data indicate that pretraining end-user participation should be considered a potentially effective tool in enhancing training effectiveness. Pretraining end-user participation is more likely to suggest who will or will not use a software application after formal training, provide a more realistic view of the content and usefulness of the training, and facilitate motivation planning and management. The paper discusses some potential critical success factors for making pretraining end-user participation more effective.     

A web-based screening model for climate risk to water supply systems in the northeastern United States

The aim of this study is to describe the development and application of a web-based decision support tool (ViRTUE) for performing climate risk evaluations of water supply systems. The tool is designed for small-scale water utilities in the northeastern United States that may lack the resources for detailed climate change risk investigations. Development of this tool demonstrates a relatively new approach to web application development using the Shiny framework for the R programming language to create an interactive environment for stakeholders and water managers to explore climate vulnerabilities. Using a decision-scaling framework, the tool allows the user to perform a climate stress test to evaluate the performance and vulnerability to water supply shortfalls of local reservoir systems over a wide range of potential climate change scenarios using a generic systems model. Probabilities of future climate conditions derived from climate projections then help inform utility operators of impending risk.     

基于仪表盘的税收决策支持平台的研究与实现

提出一种基于仪表盘的决策支持平台解决方案,设计面向税务行业的指标体系模型,用基于指标体系和联机分析处理的仪表盘技术实现了该税务决策平台.该平台具有良好的可扩展性、可定制性和可移植性等优点.     

A decision support system for the planning of the workload on a grain terminal

Ships, loaded with agricultural products, are handled by GEM at three different terminals in the port of Rotterdam. Each terminal consists of several berths and has both floating equipment and shore equipment. This paper describes the terminal system, the planning process and a menu driven computer planning model of the system. The planning model is split up into a first phase, in which berths are allocated, and a second phase, in which unloading equipment is assigned. The user of the model has the opportunity to manipulate several penalties and assign preferences to berths.     

决策支持系统理论与方法研究综述

针对经典决策支持系统理论与实际决策问题之间存在鸿沟,难以对复杂环境和复杂问题进行有效的决策支持和求解的缺陷,指出当前实际决策支持理论和方法存在的一些问题和需要考虑的各种因素,列举了主要的决策支持系统的方法和典型应用,并指出各种方法的优缺点．在与综合集成型决策支持系统进行比较后,提出只有构建综合集成型决策支持系统才能有效地解决复杂问题的决策支持．最后,总结了决策支持系统今后的研究方向和工作建议．     

New horizons at the core of information systems: decision support system advances

Here, we argue that decision support systems (DSSs) research is a core area of the information systems (IS) discipline, being one of six major expansions that have occurred in the IS field. Interestingly, DSS research is often blended with some other expansions experienced by the IS field: namely, organizational computing, electronic commerce/business, and pervasive computing. The DSS core of IS research continues to grow along ever-widening horizons. Diverse exemplars of such DSS advances are found in the papers of this special issue.     

食源性疾病预警与控制系统研究

食源性疾病的危害较大。基于信息技术的食源性疾病防范体系,利用先进的信息技术,构建良好的食品卫生安全体系,建立综合性的、可持续的系统,将积极有效地预防和及时高效地控制食源性疾病,从而降低食源性疾病对社会的危害。食源性疾病预警与控制系统主要由信息收集系统与信息处理决策系统组成,通过信息的快速传输、资料共享和信息相关处理,及时有效地预警控制食源性疾病。     

数据挖掘技术在HIS中的应用探讨

HIS作为先进的计算机管理模式正在逐渐取代了传统的医院管理模式,从与其相关的巨大信息资源中发现新的知识,将有助于为医院的管理和医疗研究提供决策支持。本文在实现了一个具体的HIS系统基础上,提出了将数据挖掘技术应用于HIS系统的设想,并对相关问题作了探讨。     

村庄布局优化DSS与GIS的系统集成

通过村庄布局优化决策支持系统案例着重讨论了ＧＩＳ与ＤＳＳ的系统集成。介绍了通过地理信息库与数据库和模型库的链接实现地图上村庄信息的显示和查询,以及村庄合并搬迁后在地图上的动态变化。使用户的决策活动更直观方便,具有较强的实用性和创新性。该系统不仅在实际应用中取得了良好的效果,而且具有一定的扩展前景。     

Decision support systems: An expert systems approach

This paper provides a conceptual framework for designing decision support systems (DSS) using an expert systems approach. Currently there is a significant trend towards the use of knowledge-based systems techniques in DSS design, but a comprehensive framework is yet to be proposed. Our paper addresses this problem and presents such a framework. Efforts are currently underway to design, implement and test a system based on this framework.     

数据建模工具及其在决策支持系统中的应用

随着数据建模工具的不断推新,开发决策支持系统所能选择的建模工具也越来越多。论文在介绍几种商品化系统建模工具的基础上,对它们的特点进行了较全面的比较,对它们基于应用的优缺点进行了分析。在选定数据建模工具ERWin后,详细论述了其在决策支持系统的具体应用。     

Frame-based argumentation for group decision task generation and identification

One of the most important stages of group decision-making is the generation and identification of decision tasks. In this paper, we define a decision task with five elements: decision makers, decision executors, decision objectives, decision problems and decision constrains. Based on this distinction, we present a conceptual model for generation and identification of group decision tasks in an organization. In addition, we describe a prototype of a group argumentation support system (GASS) that applies frame-based information structure in electronic brainstorming (EBS) and argumentation to support group decision task generation and identification. Using four group performance indicators, the prototype was evaluated in a lab experiment to determine its effectiveness and efficiency.     

Multiple criteria decision making and decision support systems — Guest editor's introduction

Integration of MCDM with DSS brings benefit to both fields. MCDM tools are useful in identifying and evaluating incompatible alternatives for DSS, while DSS can implement MCDM approaches and help maintain and retrieve MCDM models. Over the years, MCDM has made considerable contribution to the development of various DSS subspecialties. This special issue on Multiple Criteria Decision Making and Decision Support Systems consists of 9 selected papers from the 20th International Conference on Multiple Criteria Decision Making. The guest editors highlight the key ideas and contributions of the papers in the special issue.     

利用逆向模型生成法建立DSS模型链初探

模型库是决策支持系统的核心部分。本文介绍了决策支持系统中资源库的概念,提出模型链逆向生成的方法,这种方法能够有效地自动生成模型链,并给出了评估多个模型链优劣程度的一般模型。     

Searching for simplified farmers' crop choice models for integrated watershed management in Thailand: A data mining approach

This study used the C4.5 data mining algorithm to model farmers' crop choice in two watersheds in Thailand. Previous attempts in the Integrated Water Resource Assessment and Management Project to model farmers' crop choice produced large sets of decision rules. In order to produce simplified models of farmers' crop choice, data mining operations were applied for each soil series in the study areas. The resulting decision trees were much smaller in size. Land type, water availability, tenure, capital, labor availability as well as non-farm and livestock income were found to be important considerations in farmers' decision models. Profitability was also found important although it was represented in approximate ranges. Unlike the general wisdom on farmers' crop choice, these decision trees came with threshold values and sequential order of the important variables. The decision trees were validated using the remaining unused set of data, and their accuracy in predicting farmers' decisions was around 84%. Because of their simple structure, the decision trees produced in this study could be useful to analysts of water resource management as they can be integrated with biophysical models for sustainable watershed management.     

Contracting cleaning services in a European public underground transportation company with the aid of a DSS

This paper deals with the selection of a supplier for cleaning services in a European public underground transportation company as established in the European Community directives, where several conflicting criteria, such as improving service levels and reducing total service costs, must be taken into account simultaneously. The problem is analyzed in depth using the decision analysis methodology, and a decision support system, the Generic Multi-Attribute Analysis system, is used to allay the operational difficulties involved. This system can deal with incomplete information about decision-maker preferences, accounts for uncertainty about offer performance, and uses so-called decision-making with partial information to identify the best offer, taking advantage of imprecise inputs.     

一种基于Agent的决策支持系统生成器新框架

在已有ＤＳＳ框架的基础上,提出了一种基于Ａｇｅｎｔ决策支持系统生成器新框架,并讨论了该框架中各类Ａｇｅｎｔ的结构和实现方式。     

基于粗集理论的决策支持系统研究

粗集作为一种数据分析方法,能有效地从不精确的、不完整的数据中发现知识。决策支持系统涉及到对不确定因素和对不完备信息的处理。应用粗集理论可以在决策支持系统中对不完备数据进行分析、推理,提取有用特征,简化信息处理,得出肯定结论。