scholarly journals The Limitations of Decision-Making

Information ◽  
2020 ◽  
Vol 11 (12) ◽  
pp. 559
Author(s):  
Paul Walton
Keyword(s):  
Decision Making ◽  
Information Processing ◽  
Theoretical Basis ◽  
Quality Of Information ◽  
Collaborative Activity ◽  
Good Decision ◽  
Trade Offs ◽  
Evolution Characteristics ◽  
Required Quality

In a world faced with technological, health and environmental change and uncertainty, decision-making is challenging. In addition, decision-making itself is becoming a collaborative activity between people and artificial intelligence. This paper analyses decision-making as a form of information processing, using the ideas of information evolution. Information evolution studies the effect of selection pressures and change on information processing and the consequent limitations of that processing. The analysis identifies underlying information evolution factors that affect the quality of information used throughout decision-making and, hence, affect the quality of decisions. These factors imply a set of challenges in which the pressures that drive useful trade-offs in a static environment also hinder decision-making of the required quality in times of change. The analysis indicates the information evolution characteristics of a good decision-making approach and establishes the theoretical basis for tools to demonstrate the information evolution limitations of decision-making.

scholarly journals WEIGHTLESS PROCESSING OF QUANTIZED SIGNAL LOAD

T-Comm ◽  
2021 ◽  
Vol 15 (1) ◽  
pp. 48-51
Author(s):  
Vladimir I. Filatov ◽  
◽  
Alexander S. Nekrasov ◽  
Irina A. Rudzit ◽  
Daria A. Kondrashova ◽  
...  
Keyword(s):  
Signal Processing ◽  
Information Processing ◽  
Detection Problem ◽  
Quality Of Information ◽  
Input Information ◽  
Information Signal ◽  
Hardware Complications ◽  
Unit Density ◽  
Required Quality

Optimal methods for processing input information signals often involve operations, implementation of which is extremely difficult and significantly increases the requirements for automated information processing systems. However, the use of various approaches to solving this problem has led to the appearance of synthesized methods for processing a sequence of signals that allow solving the detection problem with the required quality without significant hardware complications. The article considers a method for weightless processing packets of input quantized signals, which allows us to evaluate the potential (limit) quality of information processing and quantify the amount of loss of this quality when excluding certain operations. The considered method is given with a reasonable structure of implemented devices in practice. A special feature of weightless signal processing is analysis of increasing unit density in a fixed interval of close positions, which gives information about the possible presence of an information signal. To identify this factor, two logical criteria are used, such as “m out of m” and “n out of m”, which will be described in this article.

Novel Application of Artificial Intelligence with Potential to Transform Well Planning Workflows on the Norwegian Continental Shelf

2021 ◽  
Author(s):  
Jon Gustav Vabø ◽  
Evan Thomas Delaney ◽  
Tom Savel ◽  
Norbert Dolle
Keyword(s):  
Artificial Intelligence ◽  
Decision Making ◽  
Continental Shelf ◽  
Data Science ◽  
Search Algorithm ◽  
Solution Space ◽  
Good Decision ◽  
Trade Offs ◽  
Well Trajectory ◽  
Norwegian Continental Shelf

Abstract This paper describes the transformational application of Artificial Intelligence (AI) in Equinor's annual well planning and maturation process. Well planning is a complex decision-making process, like many other processes in the industry. There are thousands of choices, conflicting business drivers, lots of uncertainty, and hidden bias. These complexities all add up, which makes good decision making very hard. In this application, AI has been used for automated and unbiased evaluation of the full solution space, with the objective to optimize the selection of drilling campaigns while taking into account complex issues such as anti-collision with existing wells, drilling hazards and trade-offs between cost, value and risk. Designing drillable well trajectories involves a sequence of decisions, which makes the process very suitable for AI algorithms. Different solver architectures, or algorithms, can be used to play this game. This is similar to how companies such as Google-owned DeepMind develop customized solvers for games such as Go and StarCraft. The chosen method is a Tree Search algorithm with an evolutionary layer on top, providing a good balance in terms of performance (i.e., speed) vs. exploration capability (i.e., it looks "wide" in the option space). The algorithm has been deployed in a full stack web-based application that allows users to follow an end-2-end workflow: from defining well trajectory design rules and constraints to running the AI engine and evaluating results to the optimization of multi-well drilling campaigns based on risk, value and cost objectives. The full-size paper describes different Norwegian Continental Shelf (NCS) use cases of this AI assisted well trajectory planning. Results to-date indicate significant CAPEX savings potential and step-change improvements in decision speed (months to days) compared to routine manual workflows. There are very limited real transformative examples of Artificial Intelligence in multi- disciplinary workflows. This paper therefore gives a unique insight how a combination of data science, domain expertise and end user feedback can lead to powerful and transformative AI solutions – implemented at scale within an existing organization.

scholarly journals The Effect of Perceived Factors of Decision Support Systems on Actual Usage: Behavioral Intention of Using Decision Support Systems as a Mediating Variable: “An Empirical Study of Jordanian Higher Education Institutions”

2016 ◽  
Vol 12 (1) ◽  
pp. 201
Author(s):  
Bilal Mohammed Salem Al-Momani
Keyword(s):  
Higher Education ◽  
Decision Making ◽  
Decision Support ◽  
Information Systems ◽  
Decision Support Systems ◽  
Behavioral Intention ◽  
Support Systems ◽  
Higher Education Institutions ◽  
Quality Of Information

Decision support systems (DSS) are interactive computer-based systems that provide information, modeling, and manipulation of data. DSS are clearly knowledge-based information systems to capture, Processing and analysis of information affecting or aims to influence the decision making process, performed by people in scope professional job appointed by a user. Hence, this study describes briefly the key concepts of decision support systems such as perceived factors with a focus on quality  of information systems and quality of information variables, behavioral intention of using DSS, and actual DSS use by adopting and extending the technology acceptance model (TAM) of Davis (1989); and Davis, Bagozzi and Warshaw (1989).There are two main goals, which stimulate the study. The first goal is to combine Perceived DSS factors and behavioral intention to use DSS from both the social perspective and a technology perspective with regard to actual DSS usage, and an experimental test of relations provide strategic locations to organizations and providing indicators that should help them manage their DSS effectiveness. Managers face the dilemma in choosing and focusing on most important factors which contributing to the positive behavioral intention of use DSS by the decision makers, which, in turn, could contribute positively in the actual DSS usage by them and other users to effectively solve organizational problems. Hence, this study presents a model which should provide the useful tool for top management in the higher education institutions- in particular-to understand the factors that determine using behaviors for designing proactive interventions and to motivate the acceptance of TAM in order to use the DSS in a way that contributes to the higher education decision-making plan and IT policy.To accomplish or attain the above mentioned objectives, the researcher developed a research instrument (questionnaire) and distributed it amongst the higher education institutions in Jordan to collect data in order to empirically study hypothesis testing (related to the objectives of study). 341 questionnaires were returned from the study respondents. Data were analyzed by utilizing both SPSS (conducted descriptive analysis) and AMOS (conducting structural equation modelling).Findings of the study indicate that some hypotheses were supported while the others were not. Contributions of the study were presented. In addition, the researcher presented some recommendations. Finally, this study has identified opportunities for further study which has progressed greatly advanced understanding constantly of DSS usage, that can help formulate powerful strategies Involving differentiation between DSS perceived factors.

scholarly journals A Model Proposed for the Prediction of Future Sustainable Residence Specifications Using Analytical Network Process

2019 ◽  
Vol 4 (3) ◽  
pp. 109
Author(s):  
Ayman M. Zakaria Eraqi ◽  
Walid Abdul-Hady Shoura
Keyword(s):  
Decision Making ◽  
Developing Countries ◽  
Demographic Characteristics ◽  
Relative Importance ◽  
Good Decision ◽  
Analytical Network Process ◽  
Network Process ◽  
Decision Structure ◽  
Occupant Satisfaction

In Egypt, people are unable to determine the qualities of appropriate residence that achieves quality and occupant satisfaction, and contributes to sustainability of residential conglomerations. In general, developing countries lack housing information which can be used to enhance quality of residence. Also, the methods of assessing and identifying the appropriate criteria for future residence quality remain traditional ones that cannot address the multiple, conflicting, overlapping aspects to reach a good decision. This calls for using the Analytical Network Process  (ANP), an effective tool for specifying the relative importance of all factors impacting a specific issue for making an appropriate residential decision. In addition, this method provides results for the decision element impacts network within the decision structure; thus contributing to more understanding of the mechanisms and requirements of residence selection. The proposed decision structure comprises a two-level network: main clusters, main elements, and sub-elements included in the demographic characteristics group, the residence criteria group, the demand parameters group, the supply parameters group, the residence specifications group, and the alternatives group which representing, in total, the decision and specifying the percentage needed for each housing level. Results of the model showed complete capacity in smoothly addressing complexities and overlapping in the decision structure. The decision structure showed that 52% chose luxury residence, 28% chose middle-class residence, and 19.5% chose the economic residence. Mechanisms of decision making were analyzed; particularly in terms of relationship to demographic characteristics and residence specifications. Also, the importance and impact of demand / supply parameters in reaching decision were analyzed.

scholarly journals Quality Assurance in Knowledge Data Warehouse

2017 ◽  
Author(s):  
Andysah Putera Utama Siahaan
Keyword(s):  
Decision Making ◽  
Knowledge Discovery ◽  
Data Warehouse ◽  
Noisy Data ◽  
Strategic Decision ◽  
Strategic Decision Making ◽  
Quality Of Information ◽  
External Data ◽  
Existing Data

Knowledge discovery is the process of adding knowledge from a large amount of data. The quality of knowledge generated from the process of knowledge discovery greatly affects the results of the decisions obtained. Existing data must be qualified and tested to ensure knowledge discovery processes can produce knowledge or information that is useful and feasible. It deals with strategic decision-making for an organization. Combining multiple operational databases and external data create the data warehouse. This treatment is very vulnerable to incomplete, inconsistent, and noisy data. Data mining provides a mechanism to clear this deficiency before finally stored in the data warehouse. This research tries to give technique to improve the quality of information in the data warehouse.

scholarly journals Evaluating COVID-19 Vaccination Website using DISCERN and QUality Evaluation Scoring (QUEST) Tools

2021 ◽  
Author(s):  
Akash Gajanan Prabhune ◽  
Aishwarya Mallavaram ◽  
Sachin Bhat ◽  
Samridhi Pandey ◽  
Ayesha Mehar Shagufta ◽  
...  
Keyword(s):  
Decision Making ◽  
United Arab Emirates ◽  
Ease Of Use ◽  
Average Score ◽  
Quality Of Information ◽  
Member States ◽  
Critical Information ◽  
Minor Elements ◽  
Selection Of

Abstract Background: The objective of this paper was to evaluate the COVID-19 vaccine registration website across UN-recognized member states for their portal quality, reliability, Ease Use and help to the general population in informed decision making.Methods: 12 UN member states (Countries) were selected based on the inclusion and exclusion criteria mentioned in the methodology section of this paper. PPS technique was used for sampling and selection of 12 countries from 193 UN member states. Post selection of UN member states the study used 2 step evaluation techniques, Step 1 The DISCERN checklist consists of 16 questions in three sections and is aimed to assess the reliability of information and quality of information; Step 2 The QUEST tool consists of 6 items with a subitem, Authorship, Attribution, Conflict of Interest, Complementarity, Currency, Tone. The authors developed a standard set of instructions for evaluating Vaccination Portals to bring uniformity in understanding and context setting.Results: DISCERN tool overall reliability score on the Likert scale of 0 to 5 was 4 (SD ± 1.28). On Quality of information regarding treatment choices, the average score was 3.4 (SD ± 1.67). The QUEST tool on ease of use, concision, and comprehensiveness demonstrated an average score of 18.1 (SD ± 8.3) out of 28.The vaccine registration portal of the Czech Republic was found to be most informative and was able to provide a piece of scientifically valid information on safety, efficacy, long-term short effects, choice of vaccine with attributable authors details. India, Bangladesh, Nigeria, South Africa scored relatively low to missing critical information on the website. The United Arab Emirates, Republic of South Korea, Indonesia, Australia, and Argentina had minor elements missing.Conclusions: COVID-19 vaccination portals vary in the quality of information and many were found unable to provide critical information for decision making on getting vaccinated

Knowledge-Intensive Entrepreneurship in the Economy of the European Union

2014 ◽  
pp. 43-52
Author(s):  
G. Olevsky
Keyword(s):  
Decision Making ◽  
Knowledge Production ◽  
The European Union ◽  
Quality Of Information ◽  
The Matrix ◽  
Knowledge Intensive ◽  
Knowledge Intensive Entrepreneurship ◽  
The Eu

The article studies role of knowledge in business and analyzes tendencies of the formation of knowledge-intensive entrepreneurship (business) in the EU. It is shown that for small and medium-sized enterprises prospects of expansion of knowledge production and sales of products and services are associated with the internationalization of business. The author proposes the matrix of decision-making entrepreneurs, depending on the completeness and quality of information at their disposal on the market.

scholarly journals Do multidisciplinary cancer care teams suffer decision-making fatigue: an observational, longitudinal team improvement study

BMJ Open ◽  
2019 ◽  
Vol 9 (5) ◽  
pp. e027303 ◽  
Author(s):  
Tayana Soukup ◽  
Tasha A K Gandamihardja ◽  
Sue McInerney ◽  
James S A Green ◽  
Nick Sevdalis
Keyword(s):  
Decision Making ◽  
Cancer Care ◽  
Information Quality ◽  
Primary Outcome ◽  
Audit And Feedback ◽  
Case Review ◽  
Quality Of Information ◽  
High Workload ◽  
Assess Quality

ObjectiveThe objective of this study was to examine effectiveness of codesigned quality-improving interventions with a multidisciplinary team (MDT) with high workload and prolonged meetings to ascertain: (1) presence and impact of decision-making (DM) fatigue on team performance in the weekly MDT meeting and (2) impact of a short meeting break as a countermeasure of DM fatigue.Design and interventionsThis is a longitudinal multiphase study with a codesigned intervention bundle assessed within team audit and feedback cycles. The interventions comprised short meeting breaks, as well as change of room layout and appointing a meeting chair.Setting and participantsA breast cancer MDT with 15 members was recruited between 2013 and 2015 from a teaching hospital of the London (UK) metropolitan area.MeasuresA validated observational tool (Metric for the Observation of Decision-making) was used by trained raters to assess quality of DM during 1335 patient reviews. The tool scores quality of information and team contributions to reviews by individual disciplines (Likert-based scores), which represent our two primary outcome measures.ResultsData were analysed using multivariate analysis of variance. DM fatigue was present in the MDT meetings: quality of information (M=16.36 to M=15.10) and contribution scores (M=27.67 to M=21.52) declined from first to second half of meetings at baseline. Of the improvement bundle, we found breaks reduced the effect of fatigue: following introduction of breaks (but not other interventions) information quality remained stable between first and second half of meetings (M=16.00 to M=15.94), and contributions to team DM improved overall (M=17.66 to M=19.85).ConclusionQuality of cancer team DM is affected by fatigue due to sequential case review over often prolonged periods of time. This detrimental effect can be reversed by introducing a break in the middle of the meeting. The study offers a methodology based on ‘team audit and feedback’ principle for codesigning interventions to improve teamwork in cancer care.

High Performance Work Systems and Organizational Outcomes: The Mediating Role of Information Quality

ILR Review ◽  
2003 ◽  
Vol 56 (4) ◽  
pp. 590-605 ◽  
Author(s):  
Gil A. Preuss
Keyword(s):  
Decision Making ◽  
High Performance ◽  
Information Quality ◽  
Knowledge Work ◽  
Care Hospital ◽  
Quality Of Information ◽  
Work Systems ◽  
High Performance Work Systems ◽  
Performance Quality

Using data on registered nurses and nursing assistants in 50 acute-care hospital units, the author explores the relationships among high performance work systems, information quality, and performance quality within a context shaped by equivocal information—information that can be interpreted in multiple and sometimes conflicting ways. He finds that the quality of information available for decision-making, which largely depends on the interpretative skills of the workers who are exposed to important equivocal information, partially mediates how employee knowledge, work design, and total quality management systems affect organizational performance (which is measured as the inverse of medication error incidence). Providing employees with extensive relevant knowledge and enabling them to use their skills during even seemingly routine tasks improves the effective quality of information they bring to decision-making, and thereby promotes high performance quality.

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