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Behavioural economics : a very short introduction
Traditionally economists have based their economic predictions on the assumption that humans are super-rational creatures, using the information we are given efficiently and generally making selfish decisions that work well for us as individuals. Economists also assume that we're doing the very best we can possibly do - not only for today, but over our whole lifetimes too. But increasingly the study of behavioural economics is revealing that our lives are not that simple. Instead, our decisions are complicated by our own psychology. Each of us makes mistakes every day. We don't always know what's best for us and, even if we do, we might not have the self-control to deliver on our best intentions. We struggle to stay on diets, to get enough exercise and to manage our money. We misjudge risky situations. We are prone to herding: sometimes peer pressure leads us blindly to copy others around us; other times copying others helps us to learn quickly about new, unfamiliar situations. 00This Very Short Introduction explores the reasons why we make irrational decisions; how we decide quickly; why we make mistakes in risky situations; our tendency to procrastination; and how we are affected by social influences, personality, mood and emotions.
Book
Transformation Of Non-Commitment Decision Risk Of Three-Way Decision Based on Limited Time Observation
In order to avoid or reduce the loss of direct decision-making caused by insufficient information, on the basis of traditional two-way decision, the non-commitment decision is added in three-way decision. However, in most practical applications, the final decision needs to be made within a limited time, the risk of non-commitment decision will increase with time and even be equivalent to the risk of commitment decision. Therefore, from the perspective of multi-time decision points, the method of transformation of non-commitment decision risk of three-way decision based on limited time observation is proposed. First, the non-commitment decision risk is analyzed and the time risk coefficient is introduced to explain the law of non-commitment risk changing with time. Then, the subjective and objective factors in the decision process are analyzed so as to make the decision process more in line with human cognition and thinking logic. Finally, an example is given to verify the effectiveness and practicability of the method.
Journal Article
A platform approach to the organization of digital forest monitoring of the Baikal natural territory
This paper describes a platform approach to the organization of digital environmental monitoring of the forest resources of the Baikal natural territory (BNT), some characteristics of the current state of forests in the BNT and schemes of organization of state environmental monitoring in a traditional format. Some features and problems of forest resources monitoring of the BNT that complicate decision-making are formulated. Some basic requirements for digital forest monitoring and types of digital platforms of different levels are considered.
Journal Article
The Influence of User Generation Differences on Individual Performance in Using Information Technology
The effect of different user generation in an organization is one of the factors that cause the decline of information technology user, this is due to the aging and characteristic difference factors of each user generations, so they impact individual performance in using information technology. Organization have user generation with very diverse age range, then the user information technology must have compatibility, flexibility, and ease in assisting completing tasks. This research is quantitative with analytical methods using Partial Least Square Structural Equation Modeling (PLS-SEM) at Mulawarman University in the generation. This study aims to identify and prove the influence of each generation of different users (Generation Y, Generation X, and Generation of Baby Boomers) on the performance of individuals in using information technology. Generation Y it was proven to be superior because the task characteristics had a significantly stronger influence than generation X and the generation baby boomers which was at the 0.05 level of significance. This study is useful for organizations in identifying the influencing factors from the real problems faced by user generation and assisting strategic decision making in order to improve information technology performance.
Journal Article
Cellular quality control by the ubiquitin-proteasome system and autophagy
To achieve homeostasis, cells evolved dynamic and self-regulating quality control processes to adapt to new environmental conditions and to prevent prolonged damage. We discuss the importance of two major quality control systems responsible for degradation of proteins and organelles in eukaryotic cells: the ubiquitin-proteasome system (UPS) and autophagy. The UPS and autophagy form an interconnected quality control network where decision-making is self-organized on the basis of biophysical parameters (binding affinities, local concentrations, and avidity) and compartmentalization (through membranes, liquid-liquid phase separation, or the formation of aggregates). We highlight cellular quality control factors that delineate their differential deployment toward macromolecular complexes, liquid-liquid phase-separated subcellular structures, or membrane-bound organelles. Finally, we emphasize the need for continuous promotion of quantitative and mechanistic research into the roles of the UPS and autophagy in human pathophysiology.
Journal Article
TODIM method based on bipolar intuitionistic fuzzy soft set
This paper deals with TODIM(an acronym in Portuguese for iterative Multi-criteria decision making) method based on bipolar intuitionistic fuzzy soft set (BIFSS). Entropy measure on BIFSS is developed and it serves as a tool in computing the weight values. Further, a score function is defined and based on it a score matrix is constructed. A BIFS normalized euclidean distance is developed and by using this a dominance degree matrix is computed. An illustration is given to show the applicability of this method in solving the decision making problem.
Journal Article
Recommendation System for Department Selection at Vocational High School (VHS) Using the Yager Model Fuzzy Multi-Attribute Decision Making (FMADM) Method
The rapid growth of technology and knowledge requires efforts to improve human resources, one of which is improving the quality of vocational education. Vocational education is the implementation of formal education channels held in higher education one of which is the Vocational High School (VHS). VHS graduates with quality potential can increase superior human resources. The problems encountered are students who want to enter vocational schools, often have difficulty in choosing majors by their potential, mistakes in choosing majors cause students who have entered vocational schools to become graduates who are less superior. One of the solutions to this problem is to create a system that can recommend majors that are in sequence with student potential. One of the benefits if the students know the major recommendations according to student abilities, then when students carry out academic leraning will produce optimal achievement and be able to develop their abilities to the maximum and become superior vocational high school graduates. The method used in the calculation of this study is the Yager Model Fuzzy Multi-Attribute Decision Making (FMADM) method to provide the results of the major's recommendations by student potential. The attributes used in the selection of these majors are academic value, talent value, interest value, intelligence quotient (IQ), parental support levels, achievement motivation, student's attitude, student's independence, and student's health. Testing the recommendation system for the selection of VHS majors using the Yager Model FMADM method is obtained in the first scenario, the results of the recommendations at the top 10 results in an appropriate conformity value of 95.00% and not 5.00%. In the second scenario, the results of the recommendations at level 3 result in an appropriate suitability value of 82.50% and an unsuitable value of 17.50%. Based on this suitability, the FMADM Model Yager method can be implemented and produce recommendations according to student potential.
Journal Article
A Three-stage Multiple Criteria Decision Making Model Based on AHP-TOPSIS and AFS Concept Description
In this paper, we propose an integrated model to solve the multi-criteria decision making problem.Firstly, AHP method is applied to calculate the weight value of each attribute on all the alternatives; secondly, TOPSIS method is used to get the preference value based on the weights calculated in the first step; finally, AFS concept description algorithm is employed to give the semantic descriptions of performance characteristics for all the alternatives. Compared with other models, this model can not only consider the comprehensive preference value, but also consider the specific performance characteristic of the alternative, which makes the decision more scientific. The supplier selection problem is applied to explain the application ability of this model.
Journal Article
MADM based Optimal Nodes Deployment for WSN with Optimal Coverage and Connectivity
It is the digital era that provides importance for the research in Wireless Sensor Network (WSN). Different issues with different solutions are suggested by many authors. The realistic deployment having restrictions for cost, area coverage, Cluster Head (CH) coverage, and sink connectivity for WSN that demands an estimation of total count of sensors for deployment with the conditions for CH coverage and sink connectivity. Area coverage means how much portion of total area is sensed by deployed sensors nodes. CH coverage means the sensor node is able to transfer the sensed data to its CH without amplification and sink connectivity means that the CHs are connected with the sink and able to send the data directly without amplification. AHP is a Multi Attribute Decision Making (MADM) method that is used for the selection of best choice having less cost and efficient coverage and connectivity.
Journal Article
Collective incentives reduce over-exploitation of social information in unconstrained human groups
Collective dynamics emerge from countless individual decisions. Yet, we poorly understand the processes governing dynamically-interacting individuals in human collectives under realistic conditions. We present a naturalistic immersive-reality experiment where groups of participants searched for rewards in different environments, studying how individuals weigh personal and social information and how this shapes individual and collective outcomes. Capturing high-resolution visual-spatial data, behavioral analyses revealed individual-level gains—but group-level losses—of high social information use and spatial proximity in environments with concentrated (vs. distributed) resources. Incentivizing participants at the group (vs. individual) level facilitated adaptation to concentrated environments, buffering apparently excessive scrounging. To infer discrete choices from unconstrained interactions and uncover the underlying decision mechanisms, we developed an unsupervised Social Hidden Markov Decision model. Computational results showed that participants were more sensitive to social information in concentrated environments frequently switching to a social relocation state where they approach successful group members. Group-level incentives reduced participants’ overall responsiveness to social information and promoted higher selectivity over time. Finally, mapping group-level spatio-temporal dynamics through time-lagged regressions revealed a collective exploration-exploitation trade-off across different timescales. Our study unravels the processes linking individual-level strategies to emerging collective dynamics, and provides tools to investigate decision-making in freely-interacting collectives.
Individual decisions drive the dynamics of collective systems. Here, the authors use an immersive-reality experiment to show that group incentives reduce social information use and improve performance in naturalistic collectives.
Journal Article