An examination of decision-makers' utilization of decision support system output

A study was conducted of 18 decision support systems in major U.S. corporations in order to examine their methods of operation and the ways in which the DSS contribute to the decision making process. These DSS were studied with respect to organizational level of the decision maker, phases of the decision making process, interaction among decision makers using the DSS, requirement for and regularity of DSS use, impact on job tasks and performance, and perceived value of the DSS. Study results provide substantial support for generalized conceptualizations in the literature. Decision support is primarily for upper and/or middle management working in interaction. Use of the DSS is at the discretion of the decision maker and the majority of DSS users are highly satisfied with their systems.     

Utility and accuracy of smell-driven performance analysis for end-user programmers

This paper proposes a technique, called smell-driven performance analysis (SDPA), which automatically provides situated explanations within a visual dataflow language IDE to help end-user programmers to overcome performance problems without leaving the visual dataflow paradigm. An experiment showed SDPA increased end-user programmers’ success rates at finding performance problems and decreased the time required for finding solutions. Another study, based on using SDPA to analyze a corpus of example end-user programs, revealed that it is usually accurate at identifying performance problems. Based on these results, we conclude that SDPA provides a reliable basis for helping end-user programmers to troubleshoot performance problems, as well as a potential foundation for future work aimed at training users and at aiding code reuse.     

Reciprocal Recommender Systems: Analysis of state-of-art literature,challenges and opportunities towards social recommendation

There exist situations of decision-making under information overload in the Internet, where people have an overwhelming number of available options to choose from, e.g. products to buy in an e-commerce site, or restaurants to visit in a large city. Recommender systems arose as a data-driven personalized decision support tool to assist users in these situations: they are able to process user-related data, filtering and recommending items based on the user’s preferences, needs and/or behavior. Unlike most conventional recommender approaches where items are inanimate entities recommended to the users and success is solely determined upon the end user’s reaction to the recommendation(s) received, in a Reciprocal Recommender System (RRS) users become the item being recommended to other users. Hence, both the end user and the user being recommended should accept the “matching” recommendation to yield a successful RRS performance. The operation of an RRS entails not only predicting accurate preference estimates upon user interaction data as classical recommenders do, but also calculating mutual compatibility between (pairs of) users, typically by applying fusion processes on unilateral user-to-user preference information. This paper presents a snapshot-style analysis of the extant literature that summarizes the state-of-the-art RRS research to date, focusing on the algorithms, fusion processes and fundamental characteristics of RRS, both inherited from conventional user-to-item recommendation models and those inherent to this emerging family of approaches. Representative RRS models are likewise highlighted. Following this, we discuss the challenges and opportunities for future research on RRSs, with special focus on (i) fusion strategies to account for reciprocity and (ii) emerging application domains related to social recommendation.     

The effect of decision support system expertise on system use behavior and performance

We performed an empirical investigation into the effect of users’ decision support system (DSS) expertise on their problem-solving strategies. The results indicated that individuals who had only recently learned to use the DSS were confused or restricted by the set of functions provided by the system and did not plan well for their use of the DSS. Those who had previous knowledge of the system exhibited more focused and efficient problem-solving behavior. Our findings suggested that problem-solving strategies depended significantly on the user's level of system expertise.     

A decision support system for the technical sustainability assessment of water distribution systems

The purpose of this study is to develop a decision support system (DSS) for the technical sustainability assessment of water distribution systems (WDSs). The technical sustainability is assessed based on the sustainability index methodology using reliability, resiliency, and vulnerability as performance criteria. These performance criteria are visualized by the DSS combining several visualization techniques to improve the raw data readability and the effectiveness of the decision-making process. The technical sustainability of the existing WDS is assessed using the sustainability index methodology and two alternative scenarios are proposed to improve the sustainability. The “new pump” scenario is based on adding network components. The second scenario is based on using reclaimed water for non-potable water demand and fire flow. The results show that the DSS is effective to illustrate time-dependent variables in the WDS and that the sustainability index methodology is a credible approach to compare scenarios and to identify problematic locations.     

基于网格和Agent技术的开放式DSS模型*

综合利用网格技术、Agent技术、数据仓库和数据挖掘技术,构建了一种基于网格的开放式DSS模型。该模型面向决策问题,以电子市场的形式组织决策资源,提供了决策资源共享和重用的新思路,提高了DSS的动态性、开放性、智能性和处理分布式问题的能力。详细分析了该模型的结构,给出了模型的运行流程,讨论了该模型区别于传统DSS的优越性。     

Problem-solving strategies for DSS design

For a successful design and implementation of DSS, competent understanding of decision-making processes in organizational settings and sensitivity to the interpersonal and organizational dimensions of the relationship between decision-makers and DSS designers are essential. Towards this end, a three-faceted strategy is broadly outlined and proposed. The strategy encompasses (a) a diagnostic attitude to the empirical tasks and contextual properties of decision-making, (b) emphasis on decision-makers rather than on decisions, and (c) the concept of DSS design as a joint undertaking for organizational problem-solving.     

An empirical study of users as application developers

A study was conducted in ten organizations of 272 non-DP professionals (“users”) who develop their own administrative computer-based applications. The data are used to create taxonomies of such users and of the applications they develop. Findings concerning the distribution of work time, application development time, relative advantages and disadvantages of user developed applications, and other factors are summarized. Evaluations of user developed applications activity by both users and DP managers are reported, and users' perceptions of importance and satisfaction with 18 different factors related to this activity are analyzed.     

Investigating the buying process for the introduction of data processing in small and medium-sized firms

Analysing the buying process and the post-purchase experiences may be of interest to both the supplier and potential buyers. The buying behaviour during the introduction of data processing and computer-assisted information processing in 69 small and medium-sized firms were investigated using a standardized questionnaire. For all firms, the decision to buy involved a decision to obtain a system, with unity of hardware, system software, and application software — thus software support had the major influence on the decision. The assumption that in producer markets buyers decide more rationally and with greater market transparency only holds true for so called “intensive decision-makers”. This subset is the result of a cluster analysis that groups the firms according to their decision-making behaviour. A comparison of the “intensive decision-makers” with all others on their post-purchase development of computer-assisted information processing presents the following finding: Over an equal time span, the “intensive decision-makers” achieved a higher level of information processing (as measured by the number of DP-applications installed, the possibility of on-line operation of the firms' departments, and the creation of integrated solutions) than the rest of the sample.     

一种基于Intranet和多Agent系统的决策支持系统框架

基于Intranet的决策支持系统的研究不仅具有重大的理论价值,而且具有很高的应用价值。该文通过对多A-gent系统与传统决策支持系统的比较和结合,把Agent方法引入到基于Intranet的决策支持系统的研究中,提出了一种新型的决策支持系统实现框架。该框架充分利用了Agent自主运行、主动性、持续性和问题求解能力以及多Agent系统的分布式和合作性等特点,对基于Intranet决策支持系统结构的研究产生了深刻的影响。该文给出了一个基于该框架的原型系统实现,通过仿真可以看出该实现框架非常适合于企业Intranet分布式开放环境。     

Providing effective decision support: Modeling users and their requirements

The major premise of this paper is that in order for a DSS to be effective in a given problem domain, it is important to model the decision-making behavior of the user over and above traditional problem solving concerns. This is achieved by extending the traditional planning framework based on first-order logic to include modal logic. This extended framework is then used to represent beliefs and desires of the user, communicative actions performed by the user and the system, as well as the usual goals, task-related actions etc. The essence of this approach, then, is to view natural language utterances of the user of a DSS as speech acts which can be modeled using the extended framework; this view can, in turn, be used to interpret natural language utterances of the user.     

Do men and women use feedback provided by their Decision Support Systems (DSS) differently

This study investigates the effect gender has on the use of computer-based feedback and the impact that this feedback has on mood. The decision making process of men and women are investigated via a laboratory experiment using a previously validated Decision Support System (DSS) and a commonly used and negatively framed feedback. Grounded in human-computer interaction theories highlighting the strong social component of computers and social feedback theories showing that men and women react to negative feedback differently, we argue that the commonly used outcome feedback in DSS studies will influence both the decision accuracy of male and female users and their moods differently. The results, which support our basic theoretical argument, indicate that outcome feedback (in particular the more negative outcome feedback) improved the decision accuracy of the female users compared to their male counterparts. The results also indicate that the outcome feedback affect the overall mood of men and women differently as well. The overall moods of the female subjects were significantly less positive before and after completing the task (receiving this commonly used negative form of feedback), the moods of the male subjects before and after completing the task (receiving the same negative feedback) did not change. These results not only extend prior DSS feedback studies but also highlight the need and provide support for examining gender differences in such investigations.     

Change, attitude to change, and decision support system success

It is generally recognized that user attitudes are important determinants of success in the implementation of information systems. Among these, users' attitudes towards the changes introduced by a system are thought to be especially important in the implementation of MIS and OR/MS applications. Based on the results of a survey of 32 decision support systems (DSS), this study investigates the relationships between the extent of changes caused by the systems to users' work environments, the users' attitudes towards work related changes, and four measures of DSS success. The results indicate that DSS users are more satisfied with, and use more extensively, those DSS that bring change than DSS that do not result in substantial changes to their work environment. Implications for the measurement of DSS success are also discussed.     

A decision support system for updating and incorporating climate change impacts into rainfall intensity-duration-frequency curves: Review of the stakeholder involvement process

Stakeholder involvement can serve to increase the quality of decision support systems (DSSs) and increase the perceived legitimacy of DSS outputs. Involving those who are ultimately affected by the outputs of DSSs in system design and development also reflects democratic principles. Importantly, stakeholder involvement can help ensure that the outputs of DSSs are used in decision-making processes. However, DSSs often fail due to poor engagement of stakeholder and end-user communities in the development and design of systems. The stakeholder engagement process applied in the development of the Computerized Tool for the Development of Intensity Duration Frequency Curves under Climate Change described here followed many of the tenants of best practices identified in the literature. While the engagement strategy was generally considered successful, over- and under-representation of some stakeholder groups and long term funding issues were weaknesses in the engagement process.     

The impact of DSS on organizational communication

There is some controversy in the MIS literature concerning the potential impact of computer systems on interpersonal communication in organizations. Generally, MIS researchers have found that effective communication between users and designers is an important factor in determining user satisfaction and MIS success.Recently, however, Naylor [8] has argued that decision support systems (DSS) may isolate managers from interaction with others. This is in marked contrast to the contentions of Wagner [16] and Huber [6] that DSS may lead to more effective managerial communication.We would argue that DSS encourage communication for several reasons: adaptive DSS development requires continued manager-analyst interaction; DSS-based decisions often require groups of managers; and there is a greater need for human information processing in a DSS environment.This paper reports the results of a study of the relationships between DSS usage and organizational communications. It was found that users in three different categories (managers, financial or planning analysts (FPAs), and “others”) felt that DSS usage encouraged communication. Also, significant positive relationships were found between increased communication and overall satisfaction with the DSS for all three groups. Finally, for managers and FPAs, significant positive relationships were found between increased communication and satisfaction with the DSS in decision-making activities.     

一种基于多目标决策的指挥决策方案优选算法

指挥决策是作战指挥活动的核心,决策方案优选是指挥决策的重要阶段之一.首先,给出了多目标决策的基本概念,提出了指挥决策问题的基本假设;其次,结合多目标决策理论,根据指挥决策问题基本假设,把威胁度、目标重要性、武器防护能力等作为指挥决策方案的优选指标.提出了一种基于多目标决策理论的指挥决策方案优选算法;最后,通过仿真实例,对该算法进行了验证.得出.结合威胁度、目标重要性以及武器防护能力等指标,通过计算武器攻击效度的方法,进行方案优选是切实可行的,对提高指挥决策效率有重要的意义.     

Research issues of Internet-integrated cognitive style

Cognitive style was once a popular research topic in the field of decision support systems (DSS), but because of the lack of usable results, it has not received much attention from the research community in recent years. This paper argues that it can be both promising and worthwhile to revive research efforts into cognitive style in the modern decision-making environment. Several reasons are offered to support this argument: First, the decision-making environment is now more integrated with technology, particularly the Internet, making it more uniform and easier to define. Second, the potential benefit of such studies is greater because more people are using Internet-based technology to make decisions. Third, data on the cognitive behavior of decision makers are captured and available for analysis because of the close integration between technology and the decision-making process. Research questions are raised and potential variables are proposed and discussed.     

广义模型服务器的设计与实现

模型的管理与运行一直是决策支持系统的核心,为了有效地实现广义模型的管理,组合和运行,文章设计和实现了一个广义模型服务器。它基于TCP／IP协议,采用三层客户／服务器机制,对模型的表示和运行进行了规范化,通过命令语言在客户端进行模型的管理和运行。该服务器可以对模型、算法、实例、工具等决策支持资源进行有效地管理,它既可广泛地应用于各领域的决策支持系统的开发,也可单独作为决策支持工具进行各种领域问题的辅助决策,文中系统地介绍了该服务器的设计和实现的理论和技术问题。