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Traditional definitions of decision support systems emphasise their support role in individual decision making and utilise notions of rational choice. By considering decisions as an organisational activity, the interpretation of decision support systems use in organisations can move beyond this technical rational understanding, to include potential political and legitimating roles for these systems. These three possible interpretations are discussed in relation to the implementation of a large decision support system in a local government context described by Dutton (1981). In its technical role, the system was used as part of a rational planning agenda. However, the system was clearly also used politically, to promote particular interests and as a lever in negotiations between various groups. Part of the appeal of the decision support system was the appearance of rationality and technical neutrality that it gave to the planning and decision making process, and the legitimation it provided with external constituents. The paper concludes that an unquestioning acceptance of the technical received view of decision support system use is limiting, and that a more reflective approach to their development, implementation and use is required.

Despite technological advancements to enhance patient health, the risks of not discovering the correct interactions and trends in digital health are high. Hence, a careful policy is required for health coverage tailored to needs and capacity. Therefore, this study aims to explore the adoption of a cognitive computing decision support system (CCDSS) in the assessment of health-care policymaking and validates it by extending the unified theory of acceptance and use of technology model.

A survey was conducted to collect data from different stakeholders, referred to as the 4Ps, namely, patients, providers, payors and policymakers. Structural equation modelling and one-way ANOVA were used to analyse the data.

The result reveals that the behavioural insight of policymakers towards the assessment of health-care policymaking is based on automatic and reflective systems. Investments in CCDSS for policymaking assessment have the potential to produce rational outcomes. CCDSS, built with quality procedures, can validate whether breastfeeding-supporting policies are mother-friendly.

Health-care policies are used by lawmakers to safeguard and improve public health, but it has always been a challenge. With the adoption of CCDSS, the overall goal of health-care policymaking can achieve better quality standards and improve the design of policymaking.

This study drew attention to how CCDSS as a technology enabler can drive health-care policymaking assessment for each stage and how the technology enabler can help the 4Ps of health-care gain insight into the benefits and potential value of CCDSS by demonstrating the breastfeeding supporting policy.

Using a decision support system (DSS) delays the decision‐making process and commits the user to the cost of invoking the system. The existing configurations of decision support systems do not guarantee the profitability of the DSS. If the DSS generates messages that the decision maker can anticipate, then the cost and waiting time as a result of invoking the DSS will not be justified. Proposes a decision support system equipped with a knowledge‐based model that tells the decision maker, prior to invoking the DSS, whether or not it is profitable to invoke the DSS; if invoking the DSS is not profitable, then the decision maker will have to base the decision on pure managerial subjective judgement. Uses a numerical example to illustrate the work of the proposed DSS.

A decision support system (DSS) is a flexible, interactive, computerized approach intended to support administrators in their decision making activities and which is capable of providing direct, personal support for complex, managerial decisions. This paper presents an overview of DSS's major characteristics which can integrate the intellectual resources of individuals with the capabilities of the computer to improve the quality of decisions. Following a discussion of its capabilities, the various components of a DSS (database, model base, hardware and user‐system interface) are examined as well as the development tools needed. Examples of the applications of DSSs in two universities provide insight into the benefits a DSS can bring to educational administration. Finally, the paper considers various development and implementation issues pertaining to a decision support system in academic administration.

IT support for marketing planning can aid in the use of marketing tools, facilitate group planning, and support moves towards continuous planning based on a live marketing model of the business. But, amongst other factors, achieving these benefits depends on the style of support provided by the system. After a review of relevant decision support system (DSS) literature, describes here the findings relating to support style from a qualitative evaluation of a system named EXMAR. The findings support Little’s classic rules of “decision calculus”, such as the importance of ensuring that managers understand and can control the system, rather than the objective influenced by management science of prescribing an optimal recommendation. Also emphasises the role of systems in enhancing mutual understanding in a cross‐functional planning team, and hence in building commitment to the resulting plan.

This paper proposes an integrated knowledge visualization and digital twin system for supporting strategic management decisions. The concepts and applications of strategic architecture have been illustrated with a concrete real-world case study and decision rules of using the strategic digital twin management decision system (SDMDS) as a more visualized, adaptive and effective model for decision-making.

This paper integrates the concepts of mental and computer models and examines a real case's business operations by applying system dynamics modelling and digital technologies. The enterprise digital twin system with displaying real-world data and simulations for future scenarios demonstrates an improved process of strategic decision-making in the digital age.

The findings reveal that data analytics and the visualized enterprise digital twin system offer better practices for strategic management decisions in the dynamic and constantly changing business world by providing a constant and frequent adjustment on every decision that affects how the business performs over both operational and strategic timescales.

In the digital age and dynamic business environment, the proposed strategic architecture and managerial digital twin system converts the existing conceptual models into an advanced operational model. It can facilitate the development of knowledge visualization and become a more adaptive and effective model for supporting real-time management decision-making by dealing with the complicated dependence of constant flow of data input, output and the feedback loop across business units and boundaries.

Decision making and the nature of decisions themselves are changing with the introduction of new information technology (IT)‐based systems in the construction industry. The use of IT systems relates to and can induce changes in business processes within firms as well as interorganizational project processes between firms. In the USA, some of the world's largest hardware and software producers are developing new generations of systems. The market for such systems is potentially large, and these vendors work in close proximity to powerful engineering and construction organizations as well as leading research establishments. It is likely that some of these systems will become de facto standards. For this and other reasons of industrial competitiveness, developments in US IT decision support systems are of interest to practitioners and researchers around the world. The present paper presents the findings of a UK Department of Trade and Industry Expert Mission to assess the development and use of IT systems in the US construction industry. The mission team included seven members, each with specialist knowledge of different aspects of IT development and implementation. The team visited 18 leading organizations where detailed interviews and seminars were conducted during a 2‐week period. The present paper highlights questions for researchers and systems developers. The main findings indicate fundamental changes to the timing, sequence and hierarchy of decision making.

Conceptualizes the impact of information technology on marketing decision making. Argues that developments in information technology affect the performance of marketing decision‐makers through different routes. Advances in information technology enhance the possibilities of collecting data and of generating information for supporting marketing decision making. Potentially, this will have a positive impact on decision‐making performance. Managerial expertise will favor the transformation of data into market insights. However, as the cognitive capabilities of marketing managers are limited, increasing amounts of data may also increase the complexity of the decision‐making context. In turn, increased complexity enhances the probability of biased decision processes, thereby negatively affecting decision‐making performance. Marketing management support systems, also being the result of advances in information technology, are tools that can help marketers to benefit from the data explosion. The analysis leads to the expectation that the combination of marketing data, managerial judgment, and marketing management support systems will be a powerful factor for improving marketing management.

Presents a foundation for the development of marketing decision support systems (MDSS). Argues that traditional management information systems typically follow a sequential flow through analysis, design, and implementation; MDSS involves a developmental approach emphasizing iteration and evaluation through the various stages. Surmises that MDSS offers marketing managers the advantages of an interactive system to supply them with useful information to help improve decision making.

Data quality metadata (DQM) is a set of quality measurements associated with the data. Prior research in data quality has shown that DQM improves decision performance. The same research has also shown that DQM overloads the cognitive capacity of decision-makers. Visualization is a proven technique to reduce cognitive overload in decision-making. This paper aims to describe a prototype decision support system with a visual interface and examine its efficacy in reducing cognitive overload in the context of decision-making with DQM.

The authors describe the salient features of the prototype and following the design science paradigm, this paper evaluates its usefulness using an experimental setting.

The authors find that the interface not only reduced perceived mental demand but also improved decision performance despite added task complexity due to the presence of DQM.

A drawback of this study is the sample size. With a sample size of 51, the power of the model to draw conclusions is weakened.

In today’s decision environments, decision-makers deal with extraordinary volumes of data the quality of which is unknown or not determinable with any certainty. The interface and its evaluation offer insights into the design of decision support systems that reduce the complexity of the data and facilitate the integration of DQM into the decision tasks.

To the best of my knowledge, this is the only research to build and evaluate a decision-support prototype for structured decision-making with DQM.