SIMULATION MODELLING IN DECISON-MAKING PROCESS

Simulacije se često upotrebljavaju kao pomoć u procesu odlučivanja. Tema rada je uloga simulacija u procesu odlučivanja i razlozi zašto su simulacije pri tome tako značajna pomoć. Također su obrađeni i suvremeni pristupi simulacijski-baziranoj programskoj podršci.Simulation is one of the most widely used aids in decision-making-process, This article deals with the role of simulation in decision-making and reasons why the simulation is a powerful tool in that process. Also, the new approaches to simulation-based software as an aid in decision-making process is described

Is Scissoring a Metaphor for Disconnecting a Relationship?

A great deal of attention has surrounded the role of embodied cognition in human judgments; however, it has received very little research attention, especially in the marketing field. This research is based on the idea that the act of cutting can activate perceptions of severing relationships, as well as eliciting a sense of independence. Study 1 showed that consumers are less likely to adopt a close friend’s opinion when they engage in the act of cutting an object with scissors. Study 2 demonstrated that people are less likely to trust the reviews of online communities while cutting a piece of string with scissors. These lowered intentions to adopt others’ opinions appeared to be mediated by increased psychological distances between the self and the information provider. In other words, people who engage in the act of scissoring unconsciously weaken or disconnect themselves from the information providers, thereby choosing not to adopt others’ opinions. This research identifies the link between the physical activity of cutting and the mental disconnection concerning social relationships. The results provide implications in setting up an integrative framework of the consumer decision-making process involving embodied cognition.      

Neuroeconomics: How Neuroscience Can Inform Economics

Neuroeconomics uses knowledge about brain mechanisms to inform economic analysis, and roots economics in biology. It opens up the "black box" of the brain, much as organizational economics adds detail to the theory of the firm. Neuroscientists use many tools— including brain imaging, behavior of patients with localized brain lesions, animal behavior, and recording single neuron activity. The key insight for economics is that the brain is composed of multiple systems which interact. Controlled systems ("executive function") interrupt automatic ones. Emotions and cognition both guide decisions. Just as prices and allocations emerge from the interaction of two processes—supply and demand— individual decisions can be modeled as the result of two (or more) processes interacting. Indeed, "dual-process" models of this sort are better rooted in neuroscientific fact, and more empirically accurate, than single-process models (such as utility-maximization). We discuss how brain evidence complicates standard assumptions about basic preference, to include homeostasis and other kinds of state-dependence. We also discuss applications to intertemporal choice, risk and decision making, and game theory. Intertemporal choice appears to be domain-specific and heavily influenced by emotion. The simplified ß-d of quasi-hyperbolic discounting is supported by activation in distinct regions of limbic and cortical systems. In risky decision, imaging data tentatively support the idea that gains and losses are coded separately, and that ambiguity is distinct from risk, because it activates fear and discomfort regions. (Ironically, lesion patients who do not receive fear signals in prefrontal cortex are "rationally" neutral toward ambiguity.) Game theory studies show the effect of brain regions implicated in "theory of mind", correlates of strategic skill, and effects of hormones and other biological variables. Finally, economics can contribute to neuroscience because simple rational-choice models are useful for understanding highly-evolved behavior like motor actions that earn rewards, and Bayesian integration of sensorimotor information

What makes voters turn out: the effects of polls and beliefs

We use laboratory experiments to test for one of the foundations of the rational voter paradigm - that voters respond to probabilities of being pivotal. We exploit a setup that entails stark theoretical effects of information concerning the preference distribution (as revealed through polls) on costly participation decisions. We find that voting propensity increases systematically with subjects' predictions of their preferred alternative's advantage. Consequently, pre-election polls do not exhibit the detrimental welfare effects that extant theoretical work predicts. They lead to more participation by the expected majority and generate more landslide elections

Human vs. AI: Investigating Consumers’ Context-Dependent Purchase Intentions for Algorithm-Created Content

Increasingly digitalized media consumption is pressuring profitability in the content industry. Technological advancements in the realm of Artificial Intelligence (AI) render the potential to cut costs by applying algorithms to create content. Yet, before implementing algorithm-created content, content providers should be aware of the impact of algorithmic authorship on consumers’ intention to purchase said content. Accordingly, this study investigates user attitudes toward algorithmic content creation and their dependence on the underlying utilitarian or hedonic consumption context. In our online experiment (N=298), we find evidence for a positive effect of algorithmic authorship on consumers’ purchase intention. Even though the overall purchase intention is context dependent, this algorithm appreciation is independent of the content consumption context. Our study thus suggests that consumers appreciate algorithm-created content. Our results thus provide insights into the benefits of leveraging algorithms in order to maintain content providers’ profitability

Assessing the impact of climate change upon migration in Burkina Faso: an agent-based modelling approach

The notion of environmental migration, and the associated desire to predict the likely scale of the phenomenon in the future, has frequented academic debate since the 1980s. Despite this, current estimates of the numbers of people likely to be displaced by environmental change by 2050 range from 150 million to 1 billion. By developing an agent-based model this research attempts to provide a rigorous means of quantifying the influence of future changes in climate (using rainfall as a proxy) upon migration trends within the context of Burkina Faso. Located in dryland West Africa, the population and economy of Burkina Faso are highly dependent upon rain-fed agriculture, placing them in a position of considerable vulnerability to future changes in rainfall. The conceptual basis behind the Agent Migration Adaptation to Rainfall Change (AMARC) model presented by this thesis is developed using contributions from the fields of climate adaptation and social psychology to focus upon three Theory of Planned Behaviour components of the migration decision: behavioural attitude; subjective norm; and perceived behavioural control. Rules of behaviour defined within the model are developed and parameterised using information gained from both retrospective migration data analysis and the responses of interviewees in focus groups conducted across Burkina Faso. Following a process of stringent model validation and testing the AMARC model is used to investigate the role of changes in rainfall variability upon past and future modelled migration. Although a relatively clear hierarchical impact of (from highest to lowest modelled migration) average, dry and wet rainfall conditions upon total modelled migration is identified, the individual flows of migrants that make up the total show unique and varied relationships with changes in rainfall. Furthermore, modelled internal and international migration flows show both similarities and differences when compared with relationships identified between rainfall and migration within existing literature

Recreation, tourism and nature in a changing world : proceedings of the fifth international conference on monitoring and management of visitor flows in recreational and protected areas : Wageningen, the Netherlands, May 30-June 3, 2010

Proceedings of the fifth international conference on monitoring and management of visitor flows in recreational and protected areas : Wageningen, the Netherlands, May 30-June 3, 201

Agent-based computational modelling of social risk responses

A characteristic aspect of risks in a complex, modern society is the nature and degree of the public response – sometimes significantly at variance with objective assessments of risk. A large part of the risk management task involves anticipating, explaining and reacting to this response. One of the main approaches we have for analysing the emergent public response, the social amplification of risk framework, has been the subject of little modelling. The purpose of this paper is to explore how social risk amplification can be represented and simulated. The importance of heterogeneity among risk perceivers, and the role of their social networks in shaping risk perceptions, makes it natural to take an agent-based approach. We look in particular at how to model some central aspects of many risk events: the way actors come to observe other actors more than external events in forming their risk perceptions; the way in which behaviour both follows risk perception and shapes it; and the way risk communications are fashioned in the light of responses to previous communications. We show how such aspects can be represented by availability cascades, but also how this creates further problems of how to represent the contrasting effects of informational and reputational elements, and the differentiation of private and public risk beliefs. Simulation of the resulting model shows how certain qualitative aspects of risk response time series found empirically – such as endogenously-produced peaks in risk concern – can be explained by this model