scholarly journals Assessing Blockchain Investments through the Learning Option: An Application to the Automotive and Aerospace Industry

Mathematics ◽  
2020 ◽  
Vol 8 (12) ◽  
pp. 2213
Author(s):  
Ana María Sánchez Pérez ◽  
Jorge Tarifa Fernández ◽  
Salvador Cruz Rambaud

Blockchain technology has demonstrated huge potential in providing simplicity and efficiency for different industries. However, its implementation in the automotive and aerospace industry is quite slow because of its difficulty to show value creation. Real option methodology, specifically the learning option, is an assessment tool which fits the conditions under which investment in blockchain technology is carried out. Thus, its application can help managers to wisely invest in this technology despite the complexity of this industry. This study offers a suitable tool to assess the strategic value of an investment in blockchain technology from a conservative position by using the real option approach, particularly the learning option. Specifically, this paper provides the mathematical expression to obtain the value of a project which includes the learning option for n periods. Likewise, it tries to raise awareness among managers of the importance to gather relevant information before making irreversible decisions. The results show that, despite the high profitability of the analyzed sector and the strategic value added by the learning option to the investment, the value of this option remains constant over the project lifespan. This indicates that the blockchain investment has to be implemented as soon as possible given that it is a highly profitable project whose value increases very slowly by waiting to get more new information. In this way, the immediate investment in blockchain technology in the automotive and aerospace industry is recommended to reap the competitive advantages offered by digital technologies.

2021 ◽  
Vol 11 (6) ◽  
pp. 721
Author(s):  
Russell J. Boag ◽  
Niek Stevenson ◽  
Roel van Dooren ◽  
Anne C. Trutti ◽  
Zsuzsika Sjoerds ◽  
...  

Working memory (WM)-based decision making depends on a number of cognitive control processes that control the flow of information into and out of WM and ensure that only relevant information is held active in WM’s limited-capacity store. Although necessary for successful decision making, recent work has shown that these control processes impose performance costs on both the speed and accuracy of WM-based decisions. Using the reference-back task as a benchmark measure of WM control, we conducted evidence accumulation modeling to test several competing explanations for six benchmark empirical performance costs. Costs were driven by a combination of processes, running outside of the decision stage (longer non-decision time) and showing the inhibition of the prepotent response (lower drift rates) in trials requiring WM control. Individuals also set more cautious response thresholds when expecting to update WM with new information versus maintain existing information. We discuss the promise of this approach for understanding cognitive control in WM-based decision making.


2021 ◽  
Vol 12 (1) ◽  
Author(s):  
◽  
Elmar Kotter ◽  
Luis Marti-Bonmati ◽  
Adrian P. Brady ◽  
Nandita M. Desouza

AbstractBlockchain can be thought of as a distributed database allowing tracing of the origin of data, and who has manipulated a given data set in the past. Medical applications of blockchain technology are emerging. Blockchain has many potential applications in medical imaging, typically making use of the tracking of radiological or clinical data. Clinical applications of blockchain technology include the documentation of the contribution of different “authors” including AI algorithms to multipart reports, the documentation of the use of AI algorithms towards the diagnosis, the possibility to enhance the accessibility of relevant information in electronic medical records, and a better control of users over their personal health records. Applications of blockchain in research include a better traceability of image data within clinical trials, a better traceability of the contributions of image and annotation data for the training of AI algorithms, thus enhancing privacy and fairness, and potentially make imaging data for AI available in larger quantities. Blockchain also allows for dynamic consenting and has the potential to empower patients and giving them a better control who has accessed their health data. There are also many potential applications of blockchain technology for administrative purposes, like keeping track of learning achievements or the surveillance of medical devices. This article gives a brief introduction in the basic technology and terminology of blockchain technology and concentrates on the potential applications of blockchain in medical imaging.


2021 ◽  
Author(s):  
Russell Golman ◽  
George Loewenstein ◽  
Andras Molnar ◽  
Silvia Saccardo

Management scientists recognize that decision making depends on the information people have but lack a unified behavioral theory of the demand for (and avoidance of) information. Drawing on an existing theoretical framework in which utility depends on beliefs and the attention paid to them, we develop and test a theory of the demand for information encompassing instrumental considerations, curiosity, and desire to direct attention to beliefs one feels good about. We decompose an individual’s demand for information into the desire to refine beliefs, holding attention constant, and the desire to focus attention on anticipated beliefs, holding these beliefs constant. Because the utility of resolving uncertainty (i.e., refining beliefs) depends on the attention paid to it and more important or salient questions capture more attention, demand for information depends on the importance and salience of the question(s) it addresses. In addition, because getting new information focuses attention on one’s beliefs and people want to savor good news and ignore bad news, the desire to obtain or avoid information depends on the valence (i.e., goodness or badness) of anticipated beliefs. Five experiments (n = 2,361) test and find support for these hypotheses, looking at neutrally valenced as well as ego-relevant information. People are indeed more inclined to acquire information (a) when it feels more important, even if it cannot aid decision making (Experiments 1A and 2A); (b) when a question is more salient, manipulated through time lag (Experiments 1B and 2B); and (c) when anticipated beliefs have higher valence (Experiment 2C). This paper was accepted by Yan Chen, behavioral economics and decision analysis.


2021 ◽  
pp. 026638212110549
Author(s):  
CA(Dr.) Gaurav Bhambri

In this paper I analytically review the literature on the information overload problem, with special reference to the business organizations and entrepreneurship and the study mainly reveals that the problem of the information overload has been existed for many years, whereas in current years the problem has become more clearly recognized and experienced. A concern stressed in the literature is the paradoxical situation that most probably there is an abundance of information available and it is often difficult to obtain useful, and relevant information when it may be needed. Both perceptions and the actual effects of information overload have exacerbated by rapid advances made in the information and communication technology, whereas it is not clear cut as to whether Internet has worsened/improved the situation. Some solutions have put forward to reduce the information overload are a reduction in duplication of the information found in professional literature; the adoption of the personal information management strategies, along with the integration of software solutions such as push technology and intelligent agents; and the provision of value-added information. Main emphasis is placed on the technology as a tool and not driver, while increased in information literacy may provide key to reducing the information overload in organisations.


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