The roles of user motivation to perform a task and decision support system (DSS) effectiveness and efficiency in DSS use

The purposes of this study are to: (1) obtain measures of actual decision support system (DSS) use that include the three elements of DSS use proposed by Burton-Jones and Straub (Burton-Jones, A., & Straub, D.W., Jr., (2006). Reconceptualizing system usage: An approach and empirical test. Information Systems Research, 17(3), 228–246), and (2) identify an important psychological construct – a user’s motivation to perform a task – and examine how it interacts with two DSS characteristics – effectiveness and efficiency – to affect actual DSS use. As predicted, the findings indicated that individuals who used a more effective DSS to work on a task that they were motivated in increased usage of the DSS, while DSS use did not differ between individuals who used either a more or less effective DSS to complete a task that they were less motivated in. The results also showed significant difference for two measures of DSS use (i.e., STEP and TIME) and no significant difference for one measure of DSS use (i.e., USE) between individuals who used either a more or less efficient DSS to perform a task that they were more motivated in. As expected, significant differences were found for individuals who used either a more or less efficient DSS to complete a task that they were less motivated in. Finally, the results showed that DSS use increased when perceived ease of use and perceived usefulness of the DSS were high; therefore, these results corroborate the findings of prior research in the context of actual DSS use.     

Representing modeling knowledge in an intelligent decision support system

Knowledge representation for data, models, and other decision support system (DSS) elements is a complex and ever-adapting task. The representation scheme for an intelligent DSS will need to provide general problem-solving model management activities as well as a mechanism for refining and testing the applicability of these models for each problem instance it encounters. We present traditional knowledge representation alternatives, and demonstrate why a multi-level scheme is superior for DSS use. We advance a two-level scheme, joining the advantages of connection graphs for the generalized analytical requirements and a frame component for problem-specific query resolution.     

Intermediating user-DSS interaction with autonomous agents

The use of advanced decision support system (DSS) capabilities is hampered by the inadequacy of a "toolbox" organization of DSS from the user's perspective. In such a setup, the user is assumed to have all the knowledge and skills necessary to appropriately use the tools provided by the system in the decision-making process. This paper proposes a model for the use of autonomous agents as intermediaries between the users and the system. The model is organized around the human problem-solving process. The paper elaborates on the types of intermediary agents and the architecture for a DSS. The approach is illustrated using the prototype for an investment DSS.     

Modelling Problem-solving for an Educational System

Abstract

When constructing a system that presents students with problem-solving, the essential problem to be considered is the definition of the system's conceptual model of the problem-solving expertise. We study two possible approaches of the definition of this model: refining generic problem-solving models and modelling by data-abstraction from an observed expertise. We emphasise that these two approaches have opposite advantages. The former facilitates the definition of rational systematic problem-solving models, the latter facilitates the respect of the problem-solving pedagogic specificities of a particular domain. In order to help in the refinement of the model constructed by either method we claim that a paper-based model is not sufficient and advocate the use of prototyping as a means to support modelling. To allow this prototyping we need a high-level language that (1) allows a quick operationalisation of the model while not enforcing predefined conceptual primitives, and (2) allows a control of what problem-solving material is used according to both problem-solving and pedagogical issues, these two aspects not being mixed. We present an example of such a language, the Zola language, and how it tackles these objectives, with examples from a system (under construction) that aims at training students to linear programming techniques.     

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。     

Gaze-augmented interaction improves problem-solving: new evidence from verbal protocols

When interacting with a problem on a computer screen, users need to select from a range of strategies that the user interface supports. Previous research shows that the problem-solving user interface plays a significant role in the strategy selection, such as by making recall unnecessary or by facilitating planning. What is not very well understood is how the interaction devices, themselves, affect problem-solving strategies. We conducted an experiment in which users interacted with a problem using either a computer mouse or gaze-augmented input. We analysed the qualitative differences in the problem-solving process by investigating the content of verbal protocols. We present a new evidence that shows that the gaze-based interaction is characterised by an increased cognitive processing of thecurrently attended information, leading to better plan development and improved problem-solving strategies. The findings have implications on the design of future gaze-aware problem-solving user interfaces.     

A decision support system for automotive product planning and competitive market analysis

A decision support system (DSS) for automotive product marketing, design and manufacturing in China is presented in this paper. The DSS is developed as a tool to support product planning, competitive market analysis, supply chain analysis and subsequent manufacturing systems planning and deployment. The system consists of a number of automotive related databases which provide information about manufacturers' performance in each market segment as well as production information of all existing market players in the Chinese auto industry. Product planning, one of the key modules of the DSS prototype, is highlighted in this paper. It supports decision makers in determining suitable strategies for market entry by analyzing existing competitors' status, growth estimation of each market segment, and competitive market analysis for new vehicle products. A case study for new market entry is included here to demonstrate the feasibility and effectiveness of the proposed methodology.     

Web-based undergraduate chemistry problem-solving: The interplay of task performance,domain knowledge and web-searching strategies

This study investigates the effect of Web-based Chemistry Problem-Solving, with the attributes of Web-searching and problem-solving scaffolds, on undergraduate students' problem-solving task performance. In addition, the nature and extent of Web-searching strategies students used and its correlation with task performance and domain knowledge also were examined. We recruited a total of 183 undergraduate students, all of whom are taking the freshman chemistry course, to participate in the study to solve three chemistry tasks across a semester. Mandated screen-capture software captured participants' on-screen Web-searching processes were recorded every five seconds. Results demonstrated that students' problem-solving performance was significantly improved from task 1 to 3, and students with more domain knowledge outperformed students with less domain knowledge. Students with higher problem-solving performance employed more existing knowledge and metacognitive Web-searching strategies; and students with lower problem-solving performance employed more cognitive Web-searching strategies. In addition, students' problem-solving performance was correlated with their domain knowledge, use of existing knowledge, and metacognitive Web-searching strategies. Moreover, students' use of existing knowledge was the major factor for predicting their problem-solving performance according to the regression model.     

Strategies for designing distributed systems: case studies in the design of an air traffic management system

The air traffic management system in the USA is an example of a distributed problem-solving system. It has elements of both cooperative and competitive problem-solving. It includes complex organizations such as Flight Operations Centers, the FAA Air Traffic Control Systems Command Center (ATCSCC), and traffic management units at en route centers that focus on daily strategic planning, as well as individuals concerned more with immediate tactical decisions (such as air traffic controllers and pilots). The design of this system has evolved over time to rely heavily on the distribution of tasks and control authority in order to keep cognitive complexity manageable for any one individual operator, and to provide redundancy (both human and technological) to serve as a safety net to catch the slips or mistakes that any one person or entity might make. Within this distributed architecture, a number of different conceptual approaches have been applied to deal with cognitive complexity and to provide redundancy. These approaches can be characterized in terms of the strategy for distributing: (1) control or responsibility, (2) knowledge or expertise, (3) access to data, (4) processing capacity, and (5) goals and priorities. This paper will provide an abstract characterization of these alternative strategies for distributing work in terms of these 5 dimensions, and will illustrate and evaluate their effectiveness in terms of concrete realizations found within the National Airspace System.     

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.     

Developing an effective support system for inquiry learning in a Web-based environment

Abstract Sixty-five teams of basic and secondary school students solved problem-solving tasks during a virtual hike in a Web-based inquiry-learning simulation 'Hiking Across Estonia'. This environment provided learners with all necessary background information for problem-solving and tools for carrying out experiments. There were 25 tasks in certain order about ecological and environmental issues. The teams were clustered according to the data about participants, the results of the pre- and post-test, and their achievement in problem-solving tasks of the virtual hike. Only two out of five clusters were regarded as effective in solving problems and analysing tables, graphs, figures, and photos. The others had difficulties in forming contextual or task and process awareness. A support system for increasing the effectiveness of inquiry learning and enhancing their development of analytical skills was developed on the basis of the strategies that the members of five clusters had used in solving the problems, their achievement in solving the tasks during the virtual hike and in the pre- and post-test, and the personal data about the teams. The support system contained different notes before solving the problems and changed sequence of the tasks on the virtual hike for some clusters. The usage of this system was evaluated in a second study with 60 teams. The comparison of two studies demonstrated significant effectiveness of the support system to both general problem-solving ability and analytical skills. The characteristics of each cluster and the influence of the support system are discussed in this paper.     

A decision support system for electric utilities: compliance with Clean Air Act

The Clean Air Act (CAA) Amendments established an absolute national limit for sulfur dioxide (SO₂) emissions by the year 2000. The Act is based on a market-oriented system under which power plants will be granted ‘emission allowances', each of which grants the right to emit a ton of SO₂ into the atmosphere. Utilities that reduce their emissions below their allocated allowances may sell the additional allowances in what will presumably be a developing market. Utilities are free to choose how to comply with the Act, but a few generally recognized options are likely to form the basis for compliance strategies. While the options are known, the costs of implementing the options are not known with certainty. Each utility will need to determine the lowest cost, most effective strategy given its current configuration and generation requirements. The compliance strategy decision must also be presented and defended to the appropriate Public Utility Commission (PUC). This paper outlines a prototype decision support system (DSS) using an optimization engine integrated with a database to help aid utilities in making decisions regarding their compliance strategy. This DSS was created specifically with a mid-western utility company in mind; however, it is generic enough to be useful to any utility. The results obtained using the DSS are very encouraging. The decisions supported by it are consistent with those offered by experts in the industry. The DSS promises to be a very useful tool for strategic planning related to CAA compliance.     

Mapcar: A framework to support the elaboration of the conceptual model of a knowledge-based system

Constructing a knowledge-based system requires the identification of the conceptual primitives and problem-solving strategy that will permit capturing the expertise in an adapted way. This article presents an approach to support the elaboration of such a conceptual model by data abstraction. Our work is motivated by the objective of constructing models that correspond to how experts solve problems, which is required for some applications, as, for example, presenting problem solving in an educational system. We argue that such an objective cannot be tackled by refining a predefined model. We propose to use a prototype reifying the model as a means for its study. We present methodological guides, and an operationalization language that allows the putting into practice of the approach we propose. Examples from different applications illustrate the presentation. © 1997 John Wiley & Sons, Inc.     

User characteristics—DSS effectiveness linkage: an empirical assessment

Despite extensive research on various factors affecting the acceptance and effectiveness of decision support systems (DSS), considerable ambiguity still exists regarding the role and influence of user characteristics. Although researchers have advocated DSS effectiveness as a multi-dimensional construct, specific guidelines regarding its dimensions or the approach to derive it is lacking. The study reported here attempts to contribute to the existing body of knowledge by proposing a multi-dimensional construct for DSS effectiveness and identifying a comprehensive set of user characteristics that influences DSS effectiveness. It critically examines the relationship between these two sets through canonical correlation analysis technique. Thirty seven students, taking a graduate level course in financial management, in a large university located in the north eastern part of the United States participated in the study acting as surrogates for real-world managers. The results of the study highlight that user's domain-related expertise, system experience, gender, intelligence, and cognitive style have important influence on one or more dimensions of DSS effectiveness. However, their relative importance vary with the outcome measure of choice.     

Impasse-driven learning in the context of video games

This study was designed to elucidate the problem-solving skills used by frequent and infrequent video game players to negotiate impasses encountered while playing a novel video game. All participants were instructed to think aloud while playing a video game for 20 consecutive minutes. Comments made were then used to make inferences about the problem-solving skills that participants used to resolve impasses encountered during the game. Findings showed that frequent players made significantly greater reference to insight and game strategies than infrequent players. After reaching an impasse, all players also were most likely to comment on their game progress and potential game strategies to use. Over the course of game play, all participants showed increasing emphasis on their problem-solving skills as evidenced through their greater mention of insight, game strategies, and goal comments.     

An examination of organizational strategies for supporting DSS

Decision support systems (DSS) are widely used by managers to provide problem solving assistance. Despite their widespread use, little is known about how organizations support DSS users. This paper discusses support practices that are thought to affect DSS groups' ability to provide support services, and reports on a field study that sought to identify the support characteristics of a sample of groups. This study also investigated differences among groups that were placed in different organizational locations. Managers of twenty-three DSS groups were interviewed to provide information on group organizational location, staff-to-user ratio, staff backgrounds, formalization, and other support characteristics. The results suggest that DSS groups generally follow some of the recommendations found in the literature with respect to their management while disregarding others. The support characteristics also tend to vary when comparing groups across organizational locations, suggesting that certain strengths and limitations may be associated with organizational support strategies.     

Plans, goals and selection rules in the comprehension of computer programs

The notion of the programming plan has been proposed as a mechanism through which one can explain the nature of expertise in programming. Soloway and Ehrlich (1984) suggest that such expertise is characterized by the existence and use of programming plans. However, studies in other complex problem-solving domains, notably text editing, suggest that expertise is characterized not only by the possession of plan-related structures but also by the development of appropriate selection rules which govern the implementation of plans in appropriate situations (Card et al. 1980, Kay and Black 1984, 1986). This paper presents an experimental study which examines the role of programming plans in the context of skill development in programming. The results of this study suggest that plan-based structures cannot be used in isolation to explain novice/expert differences. Indeed, such structures appear to prevail at intermediate levels of skill. The major characteristic of expertise in programming would appear to be strongly related to the development of appropriate selection rules and to so-called program discourse rules. This in turn suggests that current views on the role of plan-based structures in expert programming performance are too limited in their conception to provide an adequate basis for a thorough analysis of the problem-solving activity in the programming domain.     

Software engineering in the academy

Institutions that teach software are responsible for producing professionals who will build and maintain systems to the satisfaction of their beneficiaries. The article presents some ideas on how best to honor this responsibility. It presents five goals of a curriculum: principles: lasting concepts that underlie the whole field; practices: problem-solving techniques that good professionals apply consciously and regularly; applications: areas of expertise in which the principles and practices find their best expression; tools: state-of-the-art products that facilitate the application of these principles and practices; mathematics: the formal basis that makes it possible to understand everything else