Ideal Decisions Research Articles

A Pareto Dominance Principle for Data-Driven Optimization

Our paper proposes an effective way to make decisions based on data for uncertain situations. In simple terms, a data-driven decision is just a choice we make by looking at the available data. We express this choice as the best one according to a model we create from the data. The quality of this decision is judged by how well it performs in situations not seen during training. We also consider how often it disappoints in those situations. The challenge is that we do not know the exact probability of generating the data. An ideal data-driven decision should work well for any possible probability. However, such ideal decisions are usually not possible. Therefore, we look for decisions that work well on unseen data, considering the chances of disappointment. We prove that such effective decisions exist under certain conditions, allowing for practical applications. This approach holds regardless of whether the original problem is simple or complex, and it works even when the data are not uniformly collected. Our study also uncovers how the characteristics of the data-generating process influence the optimal decision-making model.

In Flight Emergency Decision-making Process: Does Intuition Matter?

Objective. This research aimed to describe the origins and contributions of pilot intuition in the decision-making process and gain knowledge on the urgency and importance of pilot intuition in decision-making.Method. The qualitative methodology used by the researcher is presented along with the phenomenology approach. Three pilots participated in the subject research. In-depth interviews, observation, and data documentation were used to collect the data. The researcher used the triangulation technique (other researchers, methods, theories, and data resources) to affirm data quality and results.Result. The research result showed that the pilot's intuitive decisions to take necessary action are based on ‘unconscious thought’ at the beginning of decision-making. However, it develops a more cognitive process where a pilot has time-critical analysis to rationalize his intuitive yet best decision. Such a decision-making process leads to prompt spontaneous and automatic action in the event of emergencies where data and information needed are lacking.
 Intuitive decisions and involuntary action are closely associated with the experience and knowledge of pilots in aviation. In an intuitive decision-making process, when time is limited and information/data is adequate, an analysis process can help a pilot identify the problem pattern and help them evaluate possible ideal decisions. An analysis process cannot replace intuition which plays a crucial role in the decision-making process during an emergency.Conclusion. A pilot’s intuition plays a strategic role in decision-making because aviation conditions are dynamic,situational, and constantly changing. Pilot’s intuition can be developed by sharpening their awareness of active and evolving aviation situations (situational and safety awareness). In addition, pilots must build longer flying hours, attend training, and expand their knowledge of aviation policies and procedures.
 
 

Evaluation of Production of Digital Twins Based on Blockchain Technology

A blockchain, as a form of distributed ledger technology, represents the unanimity of replication, synchronization, and sharing of data among various geographical sites. Blockchains have demonstrated impressive and effective applications throughout many aspects of the business. Blockchain technology can lead to the advent of the construction of Digital Twins (DTs). DTs involve the real representation of physical devices digitally as a virtual representation of both elements and dynamics prior to the building and deployment of actual devices. DT products can be built using blockchain-based technology in order to achieve sustainability. The technology of DT is one of the emerging novel technologies of Industry 4.0, along with artificial intelligence (AI) and the Internet of Things (IoT). Therefore, the present study adopts intelligent decision-making techniques to conduct a biased analysis of the drivers, barriers, and risks involved in applying blockchain technologies to the sustainable production of DTs. The proposed model illustrates the use of neutrosophic theory to handle the uncertain conditions of real-life situations and the indeterminate cases evolved in decision-makers’ judgments and perspectives. In addition, the model applies the analysis of Multi-criteria Decision Making (MCDM) methods through the use of ordered weighted averaging (OWA) and the Technique of Order Preference Similarity to the Ideal Solution (TOPSIS) to achieve optimal rankings for DT production providers based on consistent weighted decision-maker’s judgments in order to maintain and to assure sustainability. An empirical study is applied to the uncertain environment to aid decision-makers in achieving ideal decisions for DT providers with respect to various DT challenges, promoting sustainability and determining the best service providers. The Monte Carlo simulation method is used to illustrate, predict, and forecast the importance of the weights of decision-makers’ judgments as well as the direct impact on the sustainability of DT production.

INDECISION CAREER CHOICE PADA SISWA SMK

The career process that has been chosen by the individual appropriately is achieved through a good planning process and independent decision making with careful consideration based on an understanding of abilities and interests as well as an introduction to careers that exist in society as a meaningful self-realization. The problem in career decision making can be categorized as an indecision career choice, so that the individual's inability to choose, or make himself to take a certain form of action that will be realized in preparing for and entering a particular job. This research is a type of literature review research by looking for theoretical references that are relevant to the cases or problems found. The results of this study stated that based on the facts in the field, it was found that there were students who had difficulty in making ideal decisions. This condition is influenced by several factors including personality, self-esteem, social support, and career readiness.

Evolutionary Game Analysis of the Dissemination of False Information by Multiple Parties after Major Emergencies

False information is always produced after the outbreak of major emergencies. Taking this into consideration, this paper discusses the behavior of multiple parties in relation to false information dissemination after major emergencies. First, a game model is constructed, using relevant knowledge of evolutionary game theory, between three parties: regulatory institutions, opinion leaders, and ordinary Internet users. Second, the model equations are solved, and the evolutionary stability strategies of each game party under different circumstances are analyzed. Third, a numerical simulation is applied to the evolutionary trends under different strategy combinations with varying parameters. The results show that the probability of each game party making ideal decisions is positively correlated with the degree of punishment imposed by regulatory institutions on opinion leaders who release false information, the reward provided by regulatory institutions on opinion leaders who release positive information, the degree of participation and satisfaction gained by Internet users in adopting positive information, the richness of authentic content released by opinion leaders, and the psychological identification of Internet users with opinion leaders. Meanwhile, the probability of each game party making ideal decisions is negatively correlated with investigation and evidence collection costs borne by opinion leaders who release positive information, the additional income for opinion leaders who have false information adopted by Internet users, the costs of Internet users’ time and energy when they adopt information released by opinion leaders, and the costs of independently judging the accuracy of information by Internet users.

Distributed Intersection Conflict Resolution for Multiple Vehicles Considering Longitudinal-Lateral Dynamics

Multiple vehicles control at an intersection is one of the most challenging scenarios in the vehicle control field due to the high number of constraints. However, regarding the control strategies of an isolated intersection, few studies have considered the longitudinal-lateral dynamics comprehensively. In the approaches that treat the turning curve as a straight line, a longitudinal dynamic model is adopted, while the lateral execution ability is ignored. The ideal decisions that ignore vehicle dynamics are not accurately executed by actual vehicles, as doing so would be futile. In addition, due to the strong coupling and nonlinearity of the longitudinal-lateral dynamics model, the optimization problem is difficult to solve. Therefore, in this paper, a reasonable model, the simplified vehicle dynamics model coupled with longitudinal-lateral dynamics is used to describe longitudinal, lateral, and yaw motions comprehensively. Optimization of the longitudinal and lateral control of each vehicle is realized simultaneously. The multi-objective optimization problem is decomposed and solved by each vehicle utilizing model predictive control (MPC) in a distributed manner. A novel safety constraint interpretive method (SCIM) is proposed to reduce the number of constraints and facilitate the solution by converting the safety constraint. The asymptotic stability of a local closed-loop system is guaranteed by a terminal constraint, and the global feasibility is proven. Finally, a demanding intersection scenario, with comparison between the Proportional-Integral-Derivative (PID) method and Adaptive Cruise Control (ACC) method, is carried out in a Processor-in-the-Loop (PiL) test. The results demonstrate that intersection safety is guaranteed with smoother control inputs obtained by the designed distributed method. The control inputs are more suitable for vehicle execution, especially in turning maneuvers.

Strategic value realization framework from learning analytics: a practical approach

PurposeIn spite of the popularity of learning analytics (LA) in higher education institutions (HEIs), the success rate and value gained through LA projects is still little and unclear. The existing research on LA focusses more on tactical capabilities rather than its effect on organizational value. The key questions are what are the expected benefits for the institution? And how the investment in LA can bring tangible value? In this research, the authors proposed a value realization framework from LA extending the existing framework of information technology value.Design/methodology/approachThe study includes a detailed literature review focusing on the importance, existing frameworks and LA adoption challenges. Based on the identified research gap, a new framework is designed. The framework depicts the several constructs and their relationships focusing on strategic value realization. Furthermore, this study includes three case studies to validate the framework.FindingsThe framework suggests that leveraging LA for strategic value demands adequate investment not only in data infrastructure and analytics but also in staff skill training and development and strategic planning. Universities are required to measure the strategic role of LA and spend wisely in quality data, analytical tools, skilled staff who are aware of the latest technologies and data-driven opportunities for continuous improvement in learning.Originality/valueThe framework permits education leaders to design better strategies for attaining excellence in learning and teaching, and furnish learners with new data to settle on the most ideal decisions about learning. The authors believe that the appropriation of this framework and consistent efficient interest in learning analytics by the higher education area will prompt better results for learners, colleges and more extensive society. The research also proposes two approaches and eleven research agendas for future research based on the framework. The first is based on the constructs and their relationships in LA value creation, whereas the later one focusing on identifying problems associate with it.

The Establishing Paradigm of Dominus Litis Principle in Indonesian Administrative Justice

This study aimed to analyse a shifting paradigm of Dominus Litis (judge activeness) in the Indonesian state administrative justice. This principle emphasises that judges expand the paradigm that judges are not limited to being used in processes regulated in law. However, judges need to actively develop the paradigm to make legal discoveries oriented towards substantive justice and expand the paradigm from merely resolving disputes positivistically to resolving conflicts with paradigms. Legal realism and sociological jurisprudence to create substantive justice. This paper uses the normative research method, with a statutory approach and case approach by analysing two decisions of state administrative court judges. The result showed that Dominus Litis in the dispute's accomplishment is not limited to the implementation of juridical-legal positivism factors, but on how judges use their mindset to provide ideal decisions and conduct legal reasoning use socio-legal and socio-cultural paradigms. The development of demands for justice has also experienced a paradigm shift of justice. It requires the principle of an active judge who always follows developments in public policy, such as the principle of sustainable development related to environmental and natural resource issues, and finding the legal material truth.

Parking Site Selection for Light Rail Stations in Muaeng District, Khon Kaen, Thailand

Khon Kaen District is in the central, north-east part of Thailand and is being developed to handle the country’s growth. Khon Kaen District is undertaking the project of building a light rail as a facility for the people. Consequently, one of the problems is ensuring adequate parking for people using the light rail service. In general, the symmetry concept naturally used in decision making to finding an optimal solution for decision and optimization problems. In this paper, multi-criteria decision analysis (MCDA) and multi-objective decision making (MODM) were used to solve the parking site selection problem, which made the decision easier. This paper proposed an analytic hierarchy process (AHP) technique, combined with the geographical information system (GIS), to evaluate the weight of the criteria used in the analysis and find potential parking solutions. Furthermore, this paper proposed the application of a linguistic technique with fuzzy TOPSIS methods to analyze the appropriateness of parking site selections from potential candidates to support use of the light rail. The results of the MCDA show that the most suitable parking lot location is along the light rail and closest to the business area. The results of the fuzzy TOPSIS method, both positive and negative ideal decisions, can help inform decision makers in selecting which candidate site is optimal for parking.

How Do Physicians Approach Intravenous Alteplase Treatment in Patients with Acute Ischemic Stroke Who Are Eligible for Intravenous Alteplase and Endovascular Therapy? Insights from UNMASK-EVT.

With increasing use of endovascular therapy, physicians' attitudes toward intravenous alteplase in endovascular therapy-eligible patients may be changing. We explored current intravenous alteplase treatment practices of physicians in endovascular therapy- and alteplase-eligible patients with acute stroke using prespecified case scenarios and compared how their current local treatment practices differ compared with an assumed ideal environment. In an international multidisciplinary survey, 607 physicians involved in acute stroke care were randomly assigned 10 of 22 case scenarios, among them 14 with guideline-based alteplase recommendations (9 with level 1A and 5 with level 2B recommendation) and were asked how they would treat the patient: A) under their current local resources, and B) under assumed ideal conditions. Answer options were the following: 1) anticoagulation/antiplatelet therapy, 2) endovascular therapy, 3) endovascular therapy plus intravenous alteplase, and 4) intravenous alteplase. Decision rates were calculated, and multivariable regression analysis was performed to determine variables associated with the decision to abandon intravenous alteplase. In cases with guideline recommendations for alteplase, physicians favored alteplase in 82.0% under current local resources and in 79.3% under assumed ideal conditions (P < .001). Under assumed ideal conditions, interventional neuroradiologists would refrain from intravenous alteplase most often (6.28%, OR = 2.40; 95% CI, 1.01-5.71). When physicians' current and ideal decisions differed, most would like to add endovascular therapy to intravenous alteplase in an ideal setting (196/3861 responses, 5.1%). In patients eligible for endovascular therapy and intravenous alteplase, we observed a slightly lower decision rate in favor of intravenous alteplase under assumed ideal conditions compared with the decision rate under current local resources.

ECO-Case Based Reasoning Tool for Environmental Product Design

Case Based Reasoning (CBR) is one of the artificial intelligent methodologies that is widely used in problem solving by reusing the most similar previous experiences stored in the library. A framework of ECO-CBR for Life Cycle Assessment data collection has been used and the process was carried out using SolidWorks program. The practicality of the tool has been validated using case study, which then provides solution. The output enable researchers to determine forecast error and forecast accuracy, by valuing the calculation from Total Carbon Footprint, Energy Consumption, Air Acidification, and Water Eutrophication. ECO-CBR is able to assist designers in product design. Due to the limitation of environmental impact consideration in product sustainability, there is a demand to propose a tool that can assist designers to reduce environmental impact of product design at early stage. The model works as an essential guideline to lessen repeated mistakes in the product development process and help designers measure the risks before concluding ideal decisions. Minor errors that occur through the study showed that ECO-CBR is reliable to be implemented in order to find a better solution.

The Ethics behind Supervisors’ I-deal Secrecy versus I-deal Transparency Decisions

Idiosyncratic deals, or i-deals, are individualized work agreements, meaning that they create differences between co-workers. As the decision to grant an i-deal to one employee but not to another c...

A NOVEL HYBRID APPROACH FOR SIMPLIFIED NEUTROSOPHIC DECISION-MAKING WITH COMPLETELY UNKNOWN WEIGHT INFORMATION

The simplified neutrosophic set (SNS) is a useful model to describe the indeterminacy information which widely exists in the real world. In this paper, we develop a multicriteria decision-making (MCDM) method under simplified neutrosophic environment in which the information about weights of criteria is completely unknown, and the decision criterion values take the form of simplified neutrosophic numbers (SNNs). In order to determine the weighting vector of the criteria, we establish an optimization model based on the basic ideal of the traditional gray relational analysis (GRA) method. By solving this model, we get a simple and exact formula which can be used to determine the criterion weights. Moreover, we utilize the dice similarity measure to determine the similarity measures between each alternative decision and the related ideal decisions. Then, based on the traditional GRA method and the technique for order preference by similarity to ideal solution (TOPSIS), some calculation steps are presented for solving a simplified neutrosophic multicriteria decision-making problem with completely unknown weight information. To avoid information loss, this model does not use the aggregation process of decision information. Comparisons of the suggested methodology with other methods are also made. Finally, a numerical example and an experimental analysis are proposed to illustrate the application of the proposed model.

A direct projection-based group decision-making methodology with crisp values and interval data

This paper presents a methodology for group decision-making problems based on a new normalized projection measure, in which the attribute values are provided by decision makers in hybrid form with crisp values and interval data. According to the idea of the technique for order preference by similarity to ideal solution, the separations between each alternative decision and its ideal decisions are established based on the normalized projection measurement. There are no aggregation and transformation between crisp values and interval data in this model. The alternatives are ranked directly based on their relative closeness. An experimental analysis is given to illustrate the feasibility and practicability of introduced method.

A group decision making model with hybrid intuitionistic fuzzy information

Group decision making (GDM) is among the most important activities that usually occurs in our daily life. This paper extends the TOPSIS (technique for order performance by similarity to an ideal solution) approach to deal with hybrid intuitionistic fuzzy information. Using a projection measure instead of a distance measure, the separations between each alternative decision and its ideal decisions are established in a hybrid intuitionistic fuzzy environment. There are no transformations between intuitionistic fuzzy numbers and interval-valued intuitionistic fuzzy numbers. The alternatives are ranked directly based on original information. An experimental analysis is used to illustrate the feasibility and practicability of introduced method.

Bireyselden Ortak Bilgi Davranışına

Information behavior is an important field, which is increasingly studied by different disciplines. It is known that the first studies conducted related with information behavior were system focused, their aim was to resolve problems of the system and the subject was approached in terms of information centers. However after 1980, the topic was tackled in terms of user/ individual. During the last decade, the focus shifted from individual information behavior to collaborative information behavior. The collaborative information behavior assists in taking ideal decisions by generating common sense through collaboration within the teams/communities. Both theoretical as well as technical studies related with this subject are still in the pre-paradigm stage. Limited numbers of models are developed with the increase of theoretical and technical studies. Factors like common platform, context, awareness, triggers, trust and their impact on the behavior are investigated in the collaborative information behavior. The variety of the interaction scenarios between man-machine (for example man-man, man-machine, man-machine-man, etc.), requires that the subject is tackled from social and/or technical perspectives and this leads to challenges in the conceptualization. Why and how the studies on information behavior, which is relatively a new field, evolved from individual information behavior to collaborative information behavior, where we stand now in terms of the studies and the opportunities presented by this field are discussed in the present study.

A Tool for Training in Decision Making for Emergency General Surgery—Explicit Training is Possible Through Facilitation

Emergency general surgery is increasingly recognized as an area for improvement within the National Health Service in the United Kingdom. Our aim was to test the feasibility of a tool we developed in assessing and facilitating surgical decision making by trainees in the emergency setting. A decision-making tool based on common decisions in surgery was designed and incorporated prospectively into patient clerking. The 10 decisions available to surgeons were divided into 3 major headings: discharge decisions, observation decisions, and operative decisions. "Ideal decisions" were derived from the final diagnosis on discharge by 2 independent clinicians and compared with initial decisions made by surgeons. We analyzed the data with a view to validate the tool using 2 methods. Firstly, we looked at the percentage of correct decisions made by different grades of surgeon, and secondly, we analyzed the trends in deviations from ideal decisions. The decision-making tool was completed for 136 emergent surgical admissions over 2 months. Interns made less "ideal" decisions compared with residents (45% vs 56%, respectively; p = 0.10, Fisher exact test) and attending surgeons (45% vs 70%, respectively; p = 0.0001). Interns made more "admit and observe or investigate" decisions compared with residents (63% vs 55%, respectively; p = 0.27) and attending surgeons (63% vs 51%, respectively; p = 0.01), who were more likely to decide to operate on or discharge patients. A repeat study over the subsequent 2-month period has shown comparable findings in proportion of ideal decisions for each grade of surgeon. There are significant differences in the proportion of "ideal decisions" and types of decisions between interns and attending surgeons suggesting a learning curve and potential for using this tool in decision-making training. The tool inherently facilitates discussion over decisions made by making these explicit. Repeating the study revealed an internal consistency.

An intuitionistic fuzzy projection-based approach for partner selection

The partner selection is an important decision problem in the formation of a new virtual enterprise. Using the projection technique, this study introduces an approach to partner selection with linguistic values and intuitionistic fuzzy information under a group decision-making environment. To avoid information loss, there is no aggregations of decision information in this model except ideal decisions as auxiliary decision tools. Comparisons of the suggested methodology with other methods are also made. A numerical example and an experimental analysis are proposed to illustrate the application of the proposed model.

Group decision making with multi-attribute interval data

The aim of this paper is to present a group decision making methodology, in which the decision information, including the attribute values, attribute weights and weights of decision makers, is expressed in interval data. An extended TOPSIS technique is twice used in the proposed method, which is first used to determine the weights of decision makers, and second used to rank the preference order of alternatives. There is no aggregation of decision information in decision process, except that the ideal decisions as auxiliary decision tools are used in decision process. We give a comparison with another method for group decision making to show the technical advance of reported method. Additionally, we also give a real life application for supplier selection and a discussion to test the effectiveness and practical implications of the proposed method.

An application of soft computing technique in group decision making under interval-valued intuitionistic fuzzy environment

In this paper, we investigate the group decision making problem, in which the each decision maker (DM) provides his/her preferences over alternatives with respect to attributes in interval-valued intuitionistic fuzzy number. To determine the weights of DMs, inspired by the idea of TOPSIS technique, combining an optimistic coefficient, we first define a positive ideal decision as the average of all individual decisions and three negative ideal decisions, which have the maximum separations from the positive ideal decision. This method is suitable for cautious (avoiding risk) decision, since each negative ideal decision can effectively avoid a risk.By employing the derived weights of DMs, we aggregate all the individual decisions into a collective decision. After that, we aggregate all attribute values of each alternative of the collective decision into an overall evaluation of the alternative. Then rank all alternatives according to their score and accuracy degree and select the most desirable one.We compare this model with other methods and illustrate this method by a numerical example and a sensitivity analysis about the optimistic coefficient.