Types Of Decision Support Research Articles

Supporting pension decisions with value clarification methods or testimonials: two studies showing mixed effects on activation and feeling of preparation

IntroductionPension participants need appropriate support when making (complex) pension decisions. Grounded in Fuzzy-Trace Theory, we argue that suitable decisions require participants to (accurately) understand meaningful differences between decision alternatives. Based on this, we investigated the effectiveness of different types of decision support for the decision when to retire.MethodsWe conducted two experiments among participants of four Dutch pension funds (Study 1: N = 2,328, Study 2: N = 500) on the effectiveness of three different types of decision support: (a) a traditional pros and cons text, (b) a Value Clarification Method (VCM), and (c) testimonials.ResultsThe studies showed mixed results. In the first study, we found an activating effect of the VCM and the testimonials: participants who received one of these two types of decision support were more likely to visit a web page with additional information. In the second study, we found no differences between the three types of decision support.ConclusionWe discuss possible explanations for the effects found, as well as implications for future (research on) pension decision support.

Architectures of analytics intelligent decision technologies systems (IDTS) for the COVID-19 pandemic

This article presents a selective literature review of Analytics Intelligent Decision Technologies Systems (Analytics IDTS) developed to support decision-making in business and public organizations, with a particular focus on the global COVID-19 pandemic. We select Analytics IDTS published in 2019–2020 and evaluate them with an Analytics IDTS Design and Evaluation Framework. We include the types of Analytics IDTS, their decisional services, architectural capabilities, and support for phases in the decision-making process. Results are shown for 33 articles in the general Analytics domain and 71 articles in the focused Public Health domain applied to COVID-19, including how these Analytics IDTS were architected and utilized for decision making. Research in descriptive and predictive models is evident in Public Health COVID-19 research reflecting the lak of knowledge about the disease, while predictive and prescriptive models are the primary focus of the general Analytics domain. IDTS in all disciplines rely on Algorithmic decision services and Heuristic Analysis services. Higher-level decisional Synthesis and Hybrid services such as design, explanations, discovery, and learning associated with human decision-making are missing in most types of decision support, indicating that research in Machine Learning and AI has many growth opportunities for future research.

Boosting the choice of energy-efficient home appliances: the effectiveness of two types of decision support

ABSTRACT Consumers’ limitations in assessing the lifetime cost of household appliances may sustain the much-cited energy efficiency gap. We analyse the impact of an individual’s energy and investment literacy and two different types of decision support on the ability to identify the appliance with the lower lifetime cost in an online randomized controlled trial among two independently chosen samples of the Swiss population. In a decision task, participants choose between appliances with different lifetime cost. One treatment offers a short education programme on how to calculate the lifetime cost of an appliance – via a set of information slides. The second treatment provides access to an online lifetime-cost calculator tool. We find that pre-treatment energy and investment literacy are positively associated with the probability of identifying the appliance with the lowest lifetime cost. Evidence in this paper suggest that both decision aids boost identification of energy-efficient appliances. We discuss strategies to scale up these boosters.

Electronic decision support and diarrhoeal disease guideline adherence (mHDM): a cluster randomised controlled trial

Acute diarrhoeal disease management often requires rehydration alone without antibiotics. However, non-indicated antibiotics are frequently ordered and this is an important driver of antimicrobial resistance. The mHealth Diarrhoea Management (mHDM) trial aimed to establish whether electronic decision support improves rehydration and antibiotic guideline adherence in resource-limited settings. A cluster randomised controlled trial was done at ten district hospitals in Bangladesh. Inclusion criteria were patients aged 2 months or older with uncomplicated acute diarrhoea. Admission orders were observed without intervention in the pre-intervention period, followed by randomisation to electronic (rehydration calculator) or paper formatted WHO guidelines for the intervention period. The primary outcome was rate of intravenous fluid ordered as a binary variable. Generalised linear mixed-effect models, accounting for hospital clustering, served as the analytical framework; the analysis was intention to treat. The trial is registered with ClinicalTrials.gov (NCT03154229) and is completed. From March 11 to Sept 10, 2018, 4975 patients (75·6%) of 6577 screened patients were enrolled. The intervention effect for the primary outcome showed no significant differences in rates of intravenous fluids ordered as a function of decision-support type. Intravenous fluid orders decreased by 0·9 percentage points for paper electronic decision support and 4·2 percentage points for electronic decision support, with a 4·2-point difference between decision-support types in the intervention period (paper 98·7% [95% CI 91·8-99·8] vs electronic 94·5% [72·2-99·1]; pinteraction=0·31). Adverse events such as complications and mortality events were uncommon and could not be statistically estimated. Although intravenous fluid orders did not change, electronic decision support was associated with increases in the volume of intravenous fluid ordered and decreases in antibiotics ordered, which are consistent with WHO guidelines. US National Institutes of Health.

Looking to the future: guidelines for decision support as adaptation practice matures

In this final paper, the guest editors identify and discuss ten guidelines emerging from the papers in this Special Issue on Decision-Support Tools for Climate Change Adaptation. The guidelines are arranged under three headings: foundational, design and construction, and supporting sustainability in the long term. Under foundational, we address the need for co-operation with end users of decision-support resources, the contribution these resources can make to the formation of thriving communities of practice, and the match between the different types of decision support and user needs. Under design and construction, we point to the risk that policy settings will change over the multiple years required to build and publish complex decision-support resources, reducing the relevance of the final product. We discuss the need for innovative approaches to ensure visibility, credibility and hence uptake. Developers should be mindful of the requirements, resources and capabilities of potential users at all points in the design and build. We also suggest that decision-support resources may be transferable between sectors and locations, but the motivation should be around achieving excellence, and not just cost savings. Under supporting sustainability in the long term, we stress the need for evaluation and comparative studies of performance, leading to carefully documented updating and improvement of decision-support resources. Finally, in the conclusions, we look to the future. Can decision-support resources evolve successfully to meet the information and guidance requirements of the increasingly sophisticated adaptation practitioner community?

Antisocial Online Behavior Detection Using Deep Learning

The shift of human communication to online platforms brings many benefits to society due to the ease of publication of opinions, sharing experience, getting immediate feedback and the opportunity to discuss the hottest topics. Besides that, it builds up a space for antisocial behavior such as harassment, insult and hate speech. This research is dedicated to detection of antisocial online behavior detection (AOB) - an umbrella term for cyber-bullying, hate speech, cyber-aggression and use of any hateful textual content. First, we provide a benchmark of deep learning models found in the literature on AOB detection. Deep learning has already proved to be efficient in different types of decision support: decision support from financial disclosures, predicting process behavior, text-based emoticon recognition. We compare methods of traditional machine learning with deep learning, while applying important advancements of natural language processing: we examine bidirectional encoding, compare attention mechanisms with simpler reduction techniques, and investigate whether the hierarchical representation of the data and application of attention on different layers might improve the predictive performance. As a partial contribution of the final hierarchical part, we introduce pseudo-sentence hierarchical attention network, an extension of hierarchical attention network – a recent advancement in document classification.

Public Transport Authorities’ use of Cost-Benefit Analysis in practice

Given the Swedish national goals for transport and infrastructure, economic efficiency is essential also in public transport. In 2003, Ljungberg (2007) sought to answer to which extent PTAs use Cost-Benefit analyses (CBA), a methodology to assess economic efficiency, in their planning of operations and infrastructure. It was found that CBA was seldom used. This paper tries to answer the same question, but for year 2016. The aim of this paper is to see to what extent PTAs are using CBA at the time of the survey, and investigate whether there are any changes with the previous study.A survey was sent to all Swedish PTAs with questions regarding current, previous, and projected future use of CBA. Questions about knowledge of reference materials and why the organization use (or do not use) CBA was asked. The main result is that most PTAs are not using CBA as decision support. For those that do, the method is used mostly for investments in payment systems and major line or traffic changes. The PTAs seem not regard a lack of economic resources a reason for not using CBA. Rather, lack of knowledge and more reliance on other types of decision support are the reasons.

MODEL PENDUKUNG KEPUTUSAN PEMASARAN MENGGUNAKAN FUZZY INFERENCE SYSTEM (STUDI KASUS: TOKO ONLINE)

<p>The growth of Internet users both in the world and Asia give a big opportunities to develop Ecommerce<br />in Indonesia, create more Online Shops. Through the early research in the form of questionaire and interview,<br />Online Shops have many challanges not only from competitors but also from the environment condition, Rupiah<br />to United States Dollar rates, and also the supply condition or supplier when supplying products. To support the<br />Online Shops in making decisions, designed a model using Fuzzy Inference System with Mamdani because, it is<br />intuitive and work well with human input, the model designed using MATLAB application, and for the inputs we<br />will be using Stock Condition, Demand Prediction from hystorical data, Ruiah to US Dollar rates, and Supply<br />condition, and for the outputs there will be Add stocks policy, promotional policy, contract with other supplier<br />policy and price adaptation policy, for the rules we will be using the if the rules. The Models will be verified and<br />validated with help from “Ikelashop” owner, the verification process will test if the rules given, give outputs as<br />designed, for the validation will be using Extreme Combination Test, or using extreme combination between<br />condition, face validity with help from expert to validate the outputs from Extreme Combination Test, and Turing<br />Test with comparing between model’s output and expert decision. The result are two types of Decision Support<br />Model for marketing, Critical Model and Non Critical Model that is not affected by Rupiah to Dollar Rates,<br />already verified and validated.</p>

Commentary: The Role of “Technovigilance” in Improving Care in Hospitals

Commentary: The Role of “Technovigilance” in Improving Care in Hospitals

Evaluating the use of a computerized clinical decision support system for asthma by pediatric pulmonologists

PurposeTo investigate use of a new guideline-based, computerized clinical decision support (CCDS) system for asthma in a pediatric pulmonology clinic of a large academic medical center. MethodsWe conducted a qualitative evaluation including review of electronic data, direct observation, and interviews with all nine pediatric pulmonologists in the clinic.Outcome measures included patterns of computer use in relation to patient care, and themes surrounding the relationship between asthma care and computer use. ResultsThe pediatric pulmonologists entered enough data to trigger the decision support system in 397/445 (89.2%) of all asthma visits from January 2009 to May 2009. However, interviews and direct observations revealed use of the decision support system was limited to documentation activities after clinic sessions ended. Reasons for delayed use reflected barriers common to general medical care and barriers specific to subspecialty care. Subspecialist-specific barriers included the perceived high complexity of patients, the impact of subject matter expertise on the types of decision support needed, and unique workflow concerns such as the need to create letters to referring physicians. ConclusionsPediatric pulmonologists demonstrated low use of a computerized decision support system for asthma care because of a combination of general and subspecialist-specific factors.Subspecialist-specific factors should not be underestimated when designing guideline-based, computerized decision support systems for the subspecialty setting.

Air Traffic Controllers' Performance in Advance Air Traffic Management System: Part I—Performance Results

The current air traffic management (ATM) system will soon reach its capacity limits, so new concepts for the future are being developed. Many proposed schemes include shifting the task of maintaining safe distances between aircraft to ground-based automation and assigning air traffic controllers a supervisory role. This research investigated air traffic controller performance using advanced ATM concepts for the task of conflict resolution. Performance using a medium fidelity air traffic control simulator was investigated across 2 proportions of free-flying traffic and 3 types of decision support. Conflict resolution performance was significantly degraded when free-flying aircraft failed to negotiate a conflict and controllers had to intervene. Conflict resolution performance varied across the aiding condition and was superior when negotiation information was provided. However we did not find any differences in performance across proportions of free-flying traffic. Implications of this research are in further exploration of ATM concepts, design of decision aids, and training needs assessment.

Situated Service-Oriented Modeling

The emergence of e-services benefited the stakeholders due to ease of access to data, information and knowledge sources. Service-based applications have evolved into flexible and adaptable systems capable of coping with changes in user requirements and business processes. The shift from monolithic application silos towards service-oriented approaches is evident in the literature today. The benefits of service-oriented approaches include cost effectiveness, improved inter-operability, reusability, and flexibility. The benefits are not enjoyed without the threat of cognitively overloading managers in their decision making activities. Tools for effective management of information are necessary. Effective and efficient service-oriented applications need to operate within their situational boundaries. As such, decision support type tools require tight integration with the service-based approach. This study proposes an integrated Situated Service-Oriented Model and demonstrates its value via a case study of an e-learning service-based application used over a period of 15 months. Two designs were used; component-based and service-oriented. The significance of this study is in the tangible value of the model proposed and demonstrated by the e-learning case study.

What Evidence Supports the Use of Computerized Alerts and Prompts to Improve Clinicians' Prescribing Behavior?

Alerts and prompts represent promising types of decision support in electronic prescribing to tackle inadequacies in prescribing. A systematic review was conducted to evaluate the efficacy of computerized drug alerts and prompts searching EMBASE, CINHAL, MEDLINE, and PsychINFO up to May 2007. Studies assessing the impact of electronic alerts and prompts on clinicians' prescribing behavior were selected and categorized by decision support type. Most alerts and prompts (23 out of 27) demonstrated benefit in improving prescribing behavior and/or reducing error rates. The impact appeared to vary based on the type of decision support. Some of these alerts (n = 5) reported a positive impact on clinical and health service management outcomes. For many categories of reminders, the number of studies was very small and few data were available from the outpatient setting. None of the studies evaluated features that might make alerts and prompts more effective. Details of an updated search run in Jan 2009 are included in the supplement section of this review.

Audit Support Systems and Decision Aids: Current Practice and Opportunities for Future Research

Technological changes and audit firm mergers over the last decade raise the question as to whether the decision aids reported in prior research are representative of the types of decision support currently employed in audit firms. To address this issue, a study was conducted of the audit support systems used at five international audit firms and the types of decision support embedded within their audit support systems. The concepts of system restrictiveness and audit structure were combined to develop a definition of audit support system restrictiveness, and the firms' systems were classified using this definition. Substantial differences in audit support system restrictiveness were found to be associated with the type of decision support embedded within these systems. In order to guide future research, existing audit decision aid studies were mapped to the types of embedded decision support and several future research opportunities were identified.

Fuzzy methods for case-based recommendation and decision support

The paper proposes two case-based methods for recommending decisions to users on the basis of information stored in a database. In both approaches, fuzzy sets and related (approximate) reasoning techniques are used for modeling user preferences and decision principles in a flexible manner. The first approach, case-based decision making, can principally be seen as a case-based counterpart to classical decision principles well-known from statistical decision theory. The second approach, called case-based elicitation, combines aspects from flexible querying of databases and case-based prediction. Roughly, imagine a user who aims at choosing an optimal alternative among a given set of options. The preferences with respect to these alternatives are formalized in terms of flexible constraints, the expression of which refers to cases stored in a database. As both types of decision support might provide useful tools for recommender systems, we also place the methods in a broader context and discuss the role of fuzzy set theory in some related fields.

Decision support for real-time, dynamic decision-making tasks

By definition, dynamic decision making dictates that multiple and interrelated decisions be made in a continuously changing environment. Such decision making is difficult and often taxes individuals’ cognitive resources. Here I investigated ways in which to support decision making in these environments. I evaluated three forms of decision support: outcome feedback, cognitive feedback, and feedforward that incorporated (to varying degrees) common features of learning theories associated with dynamic tasks. Participants in a laboratory experiment performed a real-time, dynamic decision-making task while receiving one of the different types of decision support. During the first 2 days, individuals received one type of decision support, but on the third day they performed the task without this support. Participants who received feedforward improved their performance considerably and continued to exhibit improved performance even after discontinuation of the decision support on the third day. Neither outcome feedback nor cognitive feedback resulted in improved performance. More research is necessary to conclusively identify the best forms of dynamic decision-making support and their durability when transferred to new tasks.

The impact of structuring information in a patient decision aid

Two computer based studies examined the correspondence between decision outcomes from two different types of decision support and the decision derived from a ‘reasoned choice’ model. In Study 1 (N = 72), the impact of presentation (alternative-tree or linear) on participants’ decision, satisfaction with decision and their expectancy-vale (EV) ratings was examined for a hypothetical scenario about a decision to have a heart operation or not. In the alternative-tree format, attributes associated with each alternative were set out either as ‘pros’ or ‘cons’ and participants could click on these headings to receive more information. In the ‘linear’ format participants read through the same information in a similar fashion to a leaflet. There was significantly greater correlation (p <0.05) between the decision and participants’ summed EV ratings in the alternative-tree condition (r = 0.63, p <0.01) than in the linear condition (r = 0.29, ns). Study 2 (N = 216) replicated these findings comparing the alternative-tree (r = 0.43, p <0.05) to an attribute-tree format (r = 0.19, ns) thus controlling for the interactive searching for information on a computer. Furthermore, process tracing measures reflected the use of more complex, systematic processing of information in the alternative-tree condition, consistent with an increased correspondence between participants’ decision and values. Health professionals need to consider more closely the structuring of information about treatment options to allow patients to process information and make decisions in line with their expectations and values.

Decision support methods and applications: The cross-sections of economics and engineering or environmental issues

After a short review of various types of decision support, the paper presents a survey reference point methodology and of applications of model-based decision support systems in engineering and environmental control. The main conclusion from this survey is that economics and economic modeling issues are usually present in such decision support, thus this support corresponds to a cross-section of economics, engineering and environmental issues. Such multi-disciplinary issues are best expressed by multi-objective optimization or, rather, multi-objective model analysis.

Decision Support Methods and Applications: The Cross-Sections of Economics and Engineering or Environmental Issues

After a short review of various types of decision support, the paper presents a survey reference point methodology and of applications of model-based decision support systems in engineering and environmental control. The main conclusion from this survey is that economics and economic modeling issues are usually present in such decision support, thus this support corresponds to a cross-section of economics, engineering and environmental issues. Such multi-disciplinary issues are best expressed by multi-objective optimization or, rather, multi-objective model analysis.

Delivering Flexible Decision Support for Environmental Management: A Case Study in Integrated Catchment Management

Natural resource managers face a significant challenge in making decisions in the light of the potential off-site impacts of human activities. Decision support systems can play a role in meeting this challenge. However, the development of decision support systems that address complex requirements effectively is exacting. This is further exacerbated where those requirements are evolving rapidly. These issues are addressed here in the context of natural resource management of a catchment scale. In order to provide flexibility in the delivery and use of decision support, a toolkit approach is proposed and its applicability evaluated. Three proof of concept decision support tools and their integration into a higher level tool are described. These examples illustrate both the types of decision support that were required by users and the toolkit approach. We contend that this approach significantly enhances the potential for operational use of decision support systems in environmental management.