Knowledge sharing and negotiation support in multiperson decision support systems

A number of DSS for supporting decisions by more than one person have been proposed. These can be categorized by spatial distance (local vs. remote), temporal distance (meeting vs. mailing), commonality of goals (cooperation vs. bargaining), and control (democratic vs. hierarchical). Existing frameworks for model management in single-user DSS seem insufficient for such systems. This paper views multiperson DSS as a loosely coupled system of model and data bases which may be human (the DSS builders and users) or computerized. The system's components have different knowledge bases and may have different interests. Their interaction is characterized by knowledge sharing for uncertainty reduction and cooperative problem-solving, and negotiation for view integration, consensus-seeking, and compromise. Requirements for the different types of multiperson DSS can be formalized as application-level communications protocols. Based on a literature review and recent experience with a number of multiperson DSS prototypes, artificial intelligence-based message-passing protocols are compared with database-centered approaches and model-based techniques, such as multicriteria decision making.     

A conceptual architecture for DSS generators

The development of DSS generators is a complicated task. No existing DSS generator has been reported as a generalised, powerful and “user friendly” system, which provides full-range of capabilities for easily building specific DSS in any application area. In order to integrate a variety of decision support and data management capabilities into a well-designed, orderly whole, a conceptual design model must be created as a foundation for developing such software systems. Sprague's DSS model provides a basis for the creation of a foundation for DSS generator development. This paper proposes a comprehensive conceptual design model which is an in-depth augmentation of Sprague's original model. This model not merely provides a basis for developing DSS generators; it also proposes a fundamental architecture of DSS generators which removes some of the responsibilities of DSS design from the user. Further, the conceptual model has been technically validated by implementing an experimental DSS generator REGIMES on a microcomputer. This implementation also demonstrates the feasibility of implementing a powerful DSS generator on cost-effective hardware.     

Decision support systems

Decision support system (DSS) has almost become a generic term for anything that helps a manager's decision making. This paper reviews developments that have taken place both in theory and practice and assesses the prospects for DSS over the next ten years.     

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.     

DSS implementation activities,problem domain characteristics and DSS success

This study examines the main and joint effects of DSS implementation activities (design, development, maintenance/use) and selected attributes (subjectivity, complexity, criticality) of the problem domain for which a DSS is being implemented. DSS success is assessed via four measures: relative use, perceived utility, output satisfaction and goal realisation (a new measure devised for this study). A sample of 155 DSS projects across 64 Finnish business organizations constituted the research database. The study's major findings are that (1) design activities have a positive influence on DSS success, (2) a negative relationship may exist between the development activities and DSS success and (3) interaction effects regarding problem domain complexity appear to exist.     

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.     

An AHP model of DSS effectiveness

Empirical studies have reported equivocal, or even dysfunctional, results from the use of decision support systems (DSS). Recent examples are the Davis, Kottemann, and Remus production planning experiments. According to the researchers, these experiments demonstrate that DSS what-if analysis creates an ‘illusion of control’ that causes users to overestimate its effectiveness. Such experimental findings are contrary to case-supported DSS theory. This paper examines the discrepancy. It first overviews the decision-making process, presents a generic DSS, identifies the theoretical role of the DSS in improving decision making, develops a multiple criteria model of DSS effectiveness, and gives a DSS for delivering the model to users. Illustrating with recent empirical investigations and the Davis, Kottemann, and Remus studies, the DSS-delivered model is used to reconcile the incongruity between the experimental findings and the case-supported theory. The paper concludes with a discussion of the article's implications for information systems research and practice.     

From auditor-centric to architecture-centric: SDLC for PCI DSS

This paper examines ways to improve security architecture by harnessing the executive attention that compliance activities like PCI DSS bring to security and focus that attention toward improving security architecture over the long term. Threat modeling fills a gap between the system's functional requirements and the auditor's checklist, and is used to catalyze this change of focus.     

Robust Threshold DSS Signatures

We present threshold DSS (digital signature standard) signatures where the power to sign is shared by n players such that for a given parameter t<n/2 any subset of 2t+1 signers can collaborate to produce a valid DSS signature on any given message, but no subset of t corrupted players can forge a signature (in particular, cannot learn the signature key). In addition, we present a robust threshold DSS scheme that can also tolerate n/3 payers who refuse to participate in the signature protocol. We can also endure n/4 maliciously faulty players that generate incorrect partial signatures at the time of signature computation. This results in a highly secure and resilient DSS signature system applicable to the protection of the secret signature key, the prevention of forgery, and increased system availability. Assuming that secret communication between the players is available, we prove the security of our protocols solely based on the hardness of forging a regular DSS signature.     

Benchmarking enhancements to a decision support system for global crop production assessments

The Office of Global Analysis/International Production Assessment Division (OGA/IPAD) of the United States Department of Agriculture – Foreign Agricultural Service (USDA-FAS) has been assimilating new data and information products from agencies such as the National Aeronautics and Space Administration (NASA) into its operational decision support system (DSS). The FAS mission is to improve monthly estimates of global production of major agricultural commodities and provide US Government senior decision makers and the public the most accurate, timely, and objective assessment of the global food supply situation possible. These estimates are ultimately captured as the US governments’ official assessments of world food supply for the commodity markets and policy makers. The goal of this research was to measure changes in the quality and accuracy of decision support information resulting from the assimilation of new NASA products in the DSS. We gathered both qualitative and quantitative information through questionnaires and interviews to benchmark these changes. We used an interactive project lifecycle risk management tool developed for NASA mission spaceflight design and quality assurance (DDP – Defect Detection and Prevention) to do this. In this case, we used it to (1) quantify the change in DSS Objectives attained after assimilation of new products, and (2) evaluate the effectiveness of various Mitigation options against potential Risks. The change in Objectives attainment was considered the most important benchmarking indicator for examining the effectiveness of the assimilation of NASA products into OGA/IPAD’s DSS. From this research emerged a novel model for benchmarking DSSs that (1) promotes continuity and synergy within and between government agencies, (2) accommodates scientific, operational and architectural dynamics, and (3) facilitates transfer of knowledge among research, management, and decision-making agencies.     

Automating Hypermedia for Decision Support

Many ‘first generation’ hypermedia systems were designed to support applications, which do not require the dynamic and general characteristics necessary for our domain --- decision support systems (DSS). The heart of our research is a dynamic model of hypermedia incorporating virtual structures and computation, which we call generalized hypermedia. Generalized hypermedia broadens and automates the ‘static’ or non-virtual notion of first generation hypermedia for a knowledge-based DSS shell. The shell provides a hypermedia-style interface for navigating among DSS application models, data and reports. Such a shell should support applications in a variety of fields, e.g., engineering, manufacturing, finance, and therefore must provide hypermedia support as general, system-level functionality Generalized hypermedia superimposes a hypermedia network on a DSS application, generating all hypermedia nodes, links and link markers dynamically from the application's standard, non-hypermedia knowledge base. In this paper we demonstrate how automating hypermedia can enhance decision making with a DSS. We describe generalized hypermedia and discuss the challenges presented to it by a dynamic, real-time environment.     

考虑仿冒商威胁的正品制造商销售模式选择策略

针对仿冒商进入市场引起的消费者权益难以保证,正品市场份额被抢占,正常的市场秩序受到破坏等问题,在考虑同时受欺骗型和非欺骗型仿冒商威胁的情形下,正品制造商通过零售商进行转售或自有渠道直销的两种销售模式,建立Stackelberg博弈对比研究正品制造商的两种销售模式的均衡结果,分析正品制造商的销售模式选择策略,探讨其销售模式选择策略对两类仿冒商的打击效果以及对消费者剩余和社会福利的影响.研究结果表明:正品制造商可能不会为了维护消费者利益而选择直销模式;正品制造商选择直销模式的意愿随消费者在转售模式下对正品和欺骗型仿冒品的感知质量及欺骗型仿冒品质量的提高而减小,随非欺骗型仿冒品质量的提高而增大;正品制造商选择直销模式总能有效打击非欺骗型仿冒商,然而,对欺骗型仿冒商而言,在一定条件下,正品制造商会选择转售模式并容忍欺骗型仿冒商的存在;正品制造商选择直销模式能够提高消费者剩余和社会福利.     

Empirical evaluation of a decision support model for adopting software product line engineering

ContextThe software product line engineering (SPLE) community has provided several different approaches for assessing the feasibility of SPLE adoption and selecting transition strategies. These approaches usually include many rules and guidelines which are very often implicit or scattered over different publications. Hence, for the practitioners it is not always easy to select and use these rules to support the decision making process. Even in case the rules are known, the lack of automated support for storing and executing the rules seriously impedes the decision making process.ObjectiveWe aim to evaluate the impact of a decision support system (DSS) on decision-making in SPLE adoption. In alignment with this goal, we provide a decision support model (DSM) and the corresponding DSS.MethodFirst, we apply a systematic literature review (SLR) on the existing primary studies that discuss and present approaches for analyzing the feasibility of SPLE adoption and transition strategies. Second, based on the data extraction and synthesis activities of the SLR, the required questions and rules are derived and implemented in the DSS. Third, for validation of the approach we conduct multiple case studies.ResultsIn the course of the SLR, 31 primary studies were identified from which we could construct 25 aspects, 39 questions and 312 rules. We have developed the DSS tool Transit-PL that embodies these elements.ConclusionsThe multiple case study validation showed that the adoption of the developed DSS tool is justified to support the decision making process in SPLE adoption.     

Decision support systems: Alternative perspectives and schools

This paper reviews and compares four distinct decision support system (DSS) perspectives or ‘schools’: Decision analysis, decision research, decision calculus, and implementation process. Each school represents a relatively coherent perspective for DSS development; all four address the development and use of computer-based tools that support and aid managers in their role as decision makers. They differ, however, in terms of the nature of the decision situation envisaged, the phase of the decision process considered, the primary aims for a DSS development effort, the nature of the learning to be achieved and the phase of the development process that is emphasized. The purpose of the review is an attempt to establish a more constructive approach to understanding the central tenets and challenges for DSS. At the same time, the unique concerns and distinct contributions of the different schools suggest that it is difficult to define a single approach that satisfies equally well all considerations and all demands.     

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.     

From what if to what's best in DSS

The author of IFPS/OPTIMUM presents some typical applications of optimization within decision support systems (DSS). They show that finding ‘what's best’ is gradually superseding the ‘what if’ and ‘goal seeking’ type of analysis that is prevalent now. IFPS/OPTIMUM is now used by over 130 companies, including many of the Fortune 500 ones. The main drawback of ‘what if’ and ‘goal seeking’ type of analysis is that one cannot impose restrictions on model variables and have the DSS generator solve for values of the ‘what if’ or ‘goal seek’ variables that satisfy those restrictions. Instead, one would have to muddle through many ‘what if's’ or ‘goal seeks’ at random and check if the restrictions are satisfied. It is a manual process that is very time consuming. ‘What's best’ analysis with optimization allows one to impose such restrictions easily and do the analysis quickly. This type of analysis is playing an increasingly significant role within decision support systems. Practicing management scientists and managers should note this phenomenon. New tools and new ways of addressing problems are emerging.     

Decision Support Systems: A summary,problems, and future trends

This paper critically examines issues confronting Decision Support Systems (DSS) in the business/management area. Due to the lack of acceptable definition of DSS, the characteristics and components of DSS are discussed in detail. It is pointed out that work activities that require decision making form a spectrum of problems ranging from structured problem to unstructured problem. It is further pointed out that personality and cognitive style can influence individuals' decision styles, and thus different decision aids will be sought. DSS development and applications are briefly described. Finally, the major problems facing current DSSs are outlined, and the future trends of DSS are described.     

Development of an environmental flows decision support system

The Murray–Darling Basin in Australia is severely environmentally degraded as a result of a range of anthropogenic changes, most notably the regulation and extraction of surface water resources for irrigated agriculture. Environmental problems include eutrophication of rivers and storages, elevated salinity levels, widespread blooms of toxic blue–green algae, decline of native fish and bird populations, and reduction of area of riverine wetlands. Both the community and the government are committed to improving the state of the environment in the Basin, both for it's intrinsic ecological values, and to ensure the sustainability of production in what is Australia's most economically important agricultural region. To facilitate the on-going trade-off process between competing users of this resource, a decision support system (DSS) is being developed which will enable explicit prediction of the likely response of key features of the riverine environment to proposed flow management scenarios. The DSS is being developed using the RAISON shell (Lam, D.C.L., Mayfield, C.I., Swayne, D.A., Hopkins, K., 1994. A prototype information system for watershed management and planning. Journal of Biological Systems 2 (4), 499–517), and will integrate a range of simple models of riverine ecology which are being developed. These models will include qualitative and quantitative models representing the response of different aspects of the instream and floodplain ecology dependent upon the river flow regime. The DSS will not include a detailed model of river hydrology or hydraulics, but rather, will use the output from the range of such models currently in use in the Basin as inputs to the ecological models. The DSS will also provide a range of tools to allow user-defined evaluation of scenario results, as well as explanations and supporting information to elucidate the ecological modelling.     

Conditional Preference Networks with User's Genuine Decisions

User's choices involve habitual behavior and genuine decision. Habitual behavior is often expressed using preferences. In a multiattribute case, the Conditional Preference Network (CP-net) is a graphical model to represent user's conditional ceteris paribus (all else being equal) preference statements. Indeed, the CP-net induces a strict partial order over the outcomes. By contrast, we argue that genuine decisions are environmentally influenced and introduce the notion of “comfort” to represent this type of choices. In this article, we propose an extension of the CP-net model that we call the CP-net with Comfort (CPC-net) to represent a user's comfort with preferences. Given that preference and comfort might be two conflicting objectives, we define the Pareto optimality of outcomes when achieving outcome optimization with respect to a given CPC-net. Then, we propose a backtrack search algorithm to find the Pareto optimal outcomes. On the other hand, two outcomes can stand in one of six possible relations with respect to a CPC-net. The exact relation can be obtained by performing dominance testing in the corresponding CP-net and comparing the numeric comforts.