Behavior Decision Model Research Articles

How Behavioral Finance Patterns affect Investors’ Activity in Capital Markets?

Research by cognitive psychologists is challenging the rationality paradigm. It has started to penetrate economic modeling with a vast experimental documentation of cognitive limitations that has been accumulated so far raising the questions: Does behavioral decision models, which capture hope or expectation to risk in experimental settings, can help us comprehend investor behavior in financial markets. We try to portrait a whole picture on the attention hypothesis we have developed around pricing patterns within the innovative pharmaceuticals sector firms. We try to encompass it from several aspects: first, we lay a general psychological framework for Attention theory describing cognitive mechanisms such as the rule of selective attention in processing information in short-term. Second we explore financial aspects of selective attention, and last we explore real life investors` behavior around a major milestone within the drug development process – advisory committee milestone. Our findings based on 78 events dating for 2002-2014, a puzzling investors` behavior. We observe that higher trading is held around regulatory event in what seems like a speculative “micro bubbles”. In this paper, we try to portrait a whole picture on the attention hypothesis and merge it with these “micro bubbles” we assume to be in the drug development industry.

Simulating Human and Environmental Exposure from Hand-Held Knapsack Pesticide Application: Be-WetSpa-Pest, an Integrative, Spatially Explicit Modeling Approach.

This paper presents an integrative and spatially explicit modeling approach for analyzing human and environmental exposure from pesticide application of smallholders in the potato-producing Andean region in Colombia. The modeling approach fulfills the following criteria: (i) it includes environmental and human compartments; (ii) it contains a behavioral decision-making model for estimating the effect of policies on pesticide flows to humans and the environment; (iii) it is spatially explicit; and (iv) it is modular and easily expandable to include additional modules, crops, or technologies. The model was calibrated and validated for the Vereda La Hoya and was used to explore the effect of different policy measures in the region. The model has moderate data requirements and can be adapted relatively easily to other regions in developing countries with similar conditions.

Behavioral Modelling in a Decision Support System

Considering the variety of attitudes, objectives and behaviors characterizing forest owners is crucial for accurately assessing the impact of policy and market drivers on forest resources. A serious shortcoming of existing pan-European Decision Support Systems (DSS) is that they do not account for such heterogeneity, consequently disregarding the effects that this might have on timber supply and forest development. Linking a behavioral harvesting decision model—Expected Value Asymmetries (EVA)—to a forest resource dynamics model—European Forestry Dynamics Model (EFDM)—we provide an example of how forest owner specific characterization can be integrated in a DSS. The simulation results indicate that the approach holds promise as regards accounting for forest owner behavior in simulations of forest resources development. Hence, forest owner heterogeneity makes the distribution of forestland on owner types non-trivial, as it affects harvesting intensity and, subsequently, inter-temporal forest development.

English

The purpose of this study is to investigate the mechanisms of big data on consumer behavior on the models of C2C e-commerce. From the beginning of the following five aspects: recommendation system, information search, reputation system, virtual experience and security system, the paper discusses some factors that affect buying intention in C2C e-commerce under big data. It fully considers the characteristics of big data, and then constructs the behavioral decision-making model of C2C e-commerce consumers, especially the factors of perceived usefulness, perceived risk and trust are integrated into the model of this research. We conduct the survey method and collect 245 valid questionnaires on consumers in each area in Shanghai and online using the quota sampling method. The empirical data show that it has six hypotheses being rejected, and others are supported in 20 hypotheses. According to the results, the paper also discusses why these hypotheses are not supported and give some marketing countermeasures in order to help the e-commerce enterprises better respond to the challenges of big data. Key words: Big data, C2C e-commerce, behavioral decision-making model, mechanisms, countermeasures.

Drivers' decision-making when attempting to cross an intersection results from choice between affordances

In theory, a safe approach to an intersection implies that drivers can simultaneously manage two scenarios: they either choose to cross or to give way to an oncoming vehicle. In this article we formalize the critical time for safe crossing (CTcross) and the critical time for safe stopping (CTstop) to represent crossing and stopping possibilities, respectively. We describe these critical times in terms of affordances and empirically test their respective contribution to the driver's decision-making process. Using a driving simulator, three groups of participants drove cars with identical acceleration capabilities and different braking capabilities. They were asked to try to cross an intersection where there was an oncoming vehicle, if they deemed the maneuver to be safe. If not, they could decide to stop or, as a last resort, make an emergency exit. The intersections were identical among groups. Results showed that although the crossing possibilities (CTcross) were the same for all groups, there were between-group differences in crossing frequency. This suggests that stopping possibilities (CTstop) play a role in the driver's decision-making process, in addition to the crossing possibilities. These results can be accounted for by a behavioral model of decision making, and provide support for the hypothesis of choice between affordances.

Modeling and simulation of passenger mass violence event derived from irregular flights in the airport terminal

Purpose – The purpose of this paper is to analyze and access the extent that emotion contagion (EC) affects the passenger aggressive behavior, and then reveal key factors triggering the passenger mass violence event (MVE) under an irregular flight situation. Design/methodology/approach – This paper presents the group behaviors simulation framework based on multi-agent. The EC model is put forward to explore the EC effect among passengers, integrating the influence of intervention measures, power difference and intimacy. Moreover, the authors propose the aggressive behavior decision-making model tailed to the passenger MVE by combining the improved social force model and adaptive neuro-fuzzy inference system. Findings – The experiment results show that the method proposed in this paper can simulate the realistic evolution process of passenger MVE .The EC effect among passengers is the catalyst for the quick spreading of MVE. The intervention measures, such as providing food and endorsing service, can effectively prevent from the MVE situation deterioration. Originality/value – The research of this paper has important practical significance for the evolution analysis of passenger MVE and provides the basis for airport safety management.

Are We Still Giving Our Money to Beggars? Prosocial Intention in between of Religion, Emotion, Corruption, and Government Policy Advocacy

This research aimed to describe the dynamics of begging behavior in big cities in Indonesia, explain the psychological and social of the behavior, as well as examine the compatibility of the prosocial behavior decision-making model with the behavior of giving money to beggars by inhabitants of Jakarta, the capital of Indonesia. This research used a qualitative method namely interview with 20 participants (9 males, 11 females) age of 21-46 years old of various occupations (student, lecturer, trader, employee, etc.) and ethnicities (Chinese, Javanese, Betawinese, and Maduranese) who still give money or goods to beggars when this research was conducted. During the interview process, the authors provided intervention to participants in the form of fear communication and minimal counseling with the purpose to divert their intention of giving to beggars into giving of the donation through authorized disseminator of social assistance. This research found that factors such as religion, compassion, institutional corruption, and law enforcement play important roles in determining preferred target of prosocial behavior. Nevertheless, the cognitive-emotional intervention conducted by the authors was successful, which was indicated by the fact of 12 of the 20 participants agreeing to divert their target of prosocial behavior. DOI: 10.5901/mjss.2014.v5n23p1817

Abstract B67: Role of social support in Pap test decision making among Pacific Islander women

Abstract Background: Pacific Islanders (PIs) experience high cancer health disparities, including later stage of cervical cancer diagnosis due in large part to more than 10% lower Pap screening rates compared to non-Hispanic Whites. The aim of this community-based participatory research (CBPR) randomized control intervention is to increase rates of Pap testing among PI women residing in Southern California. Baseline data examined whether a Multi-Attribute Utility (MAU) model (a descriptive behavioral decision-making model) and women's perceived receipt of social support from their husband/partner significantly predicted Pap testing within the past three years. We also examined whether social support mediated the relationship between utility and Pap testing. Procedures: PI couples were recruited from Samoan, Tongan, and Chamorro churches and cultural social networks, and were randomly assigned to one of two educational interventions regarding cervical cancer screening. Participating women had to be between 21 and 65 years old and married or in a long-term relationship. A baseline questionnaire assessed women's MAU decision-making parameters (subjective value, subjective likelihood, and momentary salience) for eight anticipated consequences of getting a Pap test. Items also assessed female participants' perceived social support (appraisal, emotional, instrumental, and informational) from their husband/partner, and Pap testing behaviors. Results: Only half of the participants (49.9%) had received a Pap test within the past three years. A logistic regression model indicated that the total MAU score (which is the sum of the products of perceived subjective value, perceived subjective likelihood, and momentary salience across the eight parameters) was associated with higher rates of Pap testing (AOR= 1.10, p< 0.01). Four additional logistic regression models were run, one for each of the four different social support subscales. Appraisal support (AOR= 1.21, p= 0.000), emotional support (AOR= 1.25, p= 0.000), informational support (AOR= 1.13, p< 0.000), and instrumental support (AOR= 1.19, p= 0.000) were all associated with higher rates of Pap testing. Next, four mediational models were run, one for each of the four social support subscales, with instrumental support significantly mediating the relationship between MAU total scores and Pap testing. Specifically, the mediational model indicated MAU total scores had both a direct relationship with increased Pap testing, as well as an indirect relationship with increased Pap testing through its relationship with increased instrumental support. Conclusions: Results indicate that PI women's Pap testing follows a personal decision, with husband/partner's instrumental support enhancing the decision to receive a Pap test. Provision of such social support is the basis for the present intervention that educates men about the importance of expressing their concern for, and intention to assist with, regular Pap testing among PI women. Citation Format: Sora Park Tanjasiri, Jie Wu Weiss, Michele Mouttapa, Lola Sablan Santos, Jasmine Lacsamana DeGuzman, Vanessa Tuione May, Lourdes Quitugua, Dorothy Vaivao. Role of social support in Pap test decision making among Pacific Islander women. [abstract]. In: Proceedings of the Sixth AACR Conference: The Science of Cancer Health Disparities; Dec 6–9, 2013; Atlanta, GA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2014;23(11 Suppl):Abstract nr B67. doi:10.1158/1538-7755.DISP13-B67

Family ownership and R&D investment: The role of growth opportunities and business group membership

This study examines whether the influence of family ownership on R&D investment varies depending on growth opportunities and business group membership. Using data on Korean firms over ten years (1998-2007), the study shows that family ownership is negatively related to R&D investment, but the relationship becomes positive when growth opportunities are present. The moderating effect, however, differs between independent family firms and family business groups. The positive influence that growth opportunities have on promoting R&D investment is diminished for affiliates of family business groups. These findings imply that family owners invest more in R&D when their family control goals are threatened by the loss of growth potential. The empirical results of this study and its behavioral decision-making model help to bridge the gap between the predictions of the family control perspective and agency theory in explaining R&D investment by family firms in an emerging economy.

Why Do Strategic Alliances Persist? A Behavioral Decision Model

Strategic alliances are considered a flexible form of organizing, yet they are often long‐lived. Even when systematic benefit–cost analysis suggests that their organizational form should be changed or terminated, some alliances still persist. Drawing on behavioral decision theory, we propose a theoretical model that explains this phenomenon. Decision makers are subject to a variety of biases that can lead to the overvaluation of the net benefits of an alliance and, hence, inhibit the change or discontinuation of underperforming alliances. Our model illustrates how decision‐making biases at the individual, interpersonal, organizational, and interorganizational levels are moderated by the design of an alliance and the tools employed in the decision‐making process. This behavioral decision perspective advances our theoretical understanding of the longevity of strategic alliances and their embeddedness in complex decision‐making contexts. Copyright © 2014 John Wiley & Sons, Ltd.

Updating of Travel Behavior Model Parameters and Estimation of Vehicle Trip Chain Based on Plate Scanning

This article proposes a maximum-likelihood method to update travel behavior model parameters and estimate vehicle trip chain based on plate scanning. The information from plate scanning consists of the vehicle passing time and sequence of scanned vehicles along a series of plate scanning locations (sensor locations installed on road network). The article adopts the hierarchical travel behavior decision model, in which the upper tier is an activity pattern generation model, and the lower tier is a destination and route choice model. The activity pattern is an individual profile of daily performed activities. To obtain reliable estimation results, the sensor location schemes for predicting trip chaining are proposed. The maximum-likelihood estimation problem based on plate scanning is formulated to update model parameters. This problem is solved by the expectation-maximization (EM) algorithm. The model and algorithm are then tested with simulated plate scanning data in a modified Sioux Falls network. The results illustrate the efficiency of the model and its potential for an application to large and complex network cases.

Research on the Agent's Behavior Decision-making Based on Artificial Emotion

Emotional intelligence is an important branch of artificial intelligence, it is an important way to achieve the truly intelligent robot. This paper regards an Agent living in a virtual environment as the research object and proposes a fuzzy emotion model based on particle system, and combines the feedback signal of emotion with associative learning mechanism based on CMAC neural network. Finally, combined the environment, emotion model and CMAC network we propose a new Agent's behavior decision-making model based on artificial emotion, the results show that this model can improve the performance of the agent.

Relocation Remembered: Perspectives on Senior Transitions in the Living Environment

The experience of aging may necessitate transitions in living environments, either through adaptations to current residences or through relocations to more supportive environments. For over a half century, the study of these transitions has informed the work of researchers, health and mental health providers, policymakers, and municipal planners. In the 1970s and 80s, knowledge about these transitions advanced through Lawton and Nahemow's ecological theory of competence and environmental press, Wiseman's behavioral model of relocation decision making, and Litwak and Longino's developmental perspective on senior migrations. This article revisits influential theoretical frameworks that contribute to our understanding of senior transitions in living environments. These seminal works are shown to inform recent studies of relocation and gerontology. This article concludes with a call for a view on housing transitions that reflects the contemporary context.

Mental Account Barriers and Transaction Purpose: A Romanian Point of View

The present study encompasses the behavioral model of decision making. Using the models provided by scientific literature, the relationship between the basic structure of mental accounts, transaction utility and consumer decision, together with perceived comfortability. The procedure was carried out using undergraduate students of Lucian Blaga University of Sibiu, with similar proportions of sexes and with resembling ages. Results have shown that influence of mental accounting structuring and transaction utility on decision and perceived comfortability is insignificant, taken into account the differences between sexes. The presented results bring knowledge into the economic behavior of the individuals involved.

Transplantation at the Nexus of Behavioral Economics and Health Care Delivery

The transplant surgeon's decision to accept and utilize an organ typically is made within a constrained time window, explicitly cognizant of numerous health-related risks and under the potential influence of considerable regulatory and institutional pressures. This decision affects the health of two distinct populations, those patients receiving organ transplants and those waiting to receive a transplant; it also influences the physician's life and their institute's productivity. The numerous, at times nonaligned, incentives established by the complex clinical and regulatory environment, have been derived specifically to influence physicians' behaviors, and though well intended, may lead to responses that are nonoptimal when considering the myriad stakeholders being influenced. This may compromise the quality of care provided to the population at risk, and has potential to influence the physician-patient relationship. A synergistic collaboration between transplant physicians and economists that is focused on this decision environment may help to alleviate these strains. This viewpoint discusses behavioral economic principles and how they might be applied to transplantation. Specifically, the previous medical decision-making literature on transplantation will be reviewed and a discussion on how a behavioral model of physician decision making can be utilized will be explored. To date this approach has not been integrated into transplantation decision making.

Applying Theory of Planned Behavior in Predicting of Patient Safety Behaviors of Nurses

Background:Patient safety has become a major concern throughout the world. It is the absence of preventable harm to a patient during the process of health care, ensuring safer care is an enormous challenge, psychosocial variables influences behaviors of human. The theory of planned behavior (TPB) is a well-validated behavioral decision-making model that has been used to predict social and health behaviors. This study is aimed to investigate predictors of nurse’s patient safety intentions and behavior, using a TPB framework.Methods:Stratified sampling technique was used to choose 124 nurses who worked at the selected hospitals of Isfahan in 2011. Study tool was a questionnaire, designed by researchers team including 3 nurses a physician and a psychologist based on guideline of TPB model. Questionnaire Validity was confirmed by experts and its reliability was assessed by Cronbach’s alpha as 0.87. Binary logistic regression analysis was performed to evaluate how well each TPB variables predicted the variance in patient safety behavior. Analyzing was done by SPSS18.Results:Finding revealed that “normative beliefs” had the greatest influence on nurses intention to implement patient safety behaviors. Analyzing data by hospital types and workplace wards showed that both in public and private hospitals normative beliefs has affected safety behaviors of nurses more than other variables. Also in surgical wards, nurses behaviors have been affected by “control beliefs” and in medical wards by normative beliefs.Conclusion:Normative beliefs, and subjective norms were the most influential factor of safety behavior of nurses in this study. Considering the role of cultural context in these issues, it seemseducation of managers and top individuals about patient safety and its importance is a priority also control believes were another important predicting factor of behavior in surgical wards and intensive care units. Regarding the complexity of work in these spaces, applying medical guidelines and effective supervision must be seriously followed.

An empirical study of a behavioral decision model with moderated effects for long-range security initiatives

Organizations are squeezing their overhead budgets (where security initiatives fall) and are focusing more on revenue generation given current economic climates. Thus in both governmental sectors and in commercial settings, there are reasons to believe that strategic security initiatives are being sacrificed, and those that survive must be compelling to decision makers who may be biased toward one choice or another. To assist decision makers with difficult choices, it is critical to understand how biases affect long-range security initiative decisions. Although biases and behavioral decision theory (BDT) have been extensively researched in various contexts, we contribute to the body of security literature by filling a gap in relation to how biases defined in BDT influence security initiatives over the long-run. We conducted a longitudinal empirical investigation using a BDT model into how biases may affect long-range security initiative decision making, examining an important moderated interaction among the factors. Risk tolerance was shown to interact with overconfidence, anchoring adjustment, and utility such that these biases were amplified. This article represents a phase-3 in a four-phased study.

A behavioral decision model testing the association of marijuana use and sexual risk in young adult women.

We created a model conceptualizing sexual risk as a series of discrete event-specific behavioral decisions and tested the hypothesis that marijuana use was associated with increased sexual risk-taking. Three hundred eight marijuana-using women aged 18-24 completed a 90-day time-line-follow-back to assess sexual behaviors and marijuana use. A sequential logit model estimated the effect of marijuana use on the likelihood of being sexually active, partner type when sexually active, and condom nonuse conditional on partner type. Participants had a mean age of 20.4years, with 67% Caucasian. Marijuana use was associated with an increased likelihood of being sexually active (OR 1.6; 95% CI 1.33, 1.93) and with condom nonuse when sexually active with casual partners (OR 2.58; 95% CI 1.1, 6.09). This behavioral decision model identified where marijuana use affected sexual risk, and suggests where interventions designed to reduce risk may have an impact.

Automatic emotional expression of a face robot by using a reactive behavior decision model

This paper introduces a face robot named ‘Buddy’ which can perform facial expressions, such as eye-tracking and lip synchronization, via movements of its facial elements (i.e., eyeballs, eyebrows, eyelids, and lips). Buddy has 14 degrees of freedom. To produce the realistic motion of Buddy, we built a ‘Reactive Behavior Decision Model’ which decides not only how to control the rotation angles and speed of facial elements, but to exhibit as well particular emotions that could express the robot’s personality. Buddy’s personality is formed in the model by the accumulated external stimuli and internal status. The process to automatically achieve reactive behavior in the model is classified into three steps: (1) to analyze the external stimuli and identify variations in Buddy’s internal status; (2) to decide the type and degree of emotion based on the robot’s personality; and (3) to generate specific facial expressions and gestures by combining the appropriate primitive behaviors chosen from emotion databases. By using this model, we have proven that Buddy can display various facial expressions and behaviors, at times very reasonable but quite unexpected.

A Behavioral Decision Model Based on Fuzzy Targets in Decision Making Using Weather Information

Due to inevitable uncertainty in weather forecasts, many decision problems influenced by weather information have been formulated for decision making in uncertain situations. The fuzzy target-based decision making model we propose assumes that the decision maker assesses a fuzzy target expressing an aspiration, then selects the decision maximizing the possibility of attaining this target aspiration before making a decision. We then show that the decision maker's different behavior about the aspiration leads to different decisions depending on the decision maker's personal philosophy or experience. This behavioral analysis provides an interpretation for influencing psychological features of the decision maker in decision making and introduces an interesting link to attitudes towards risk by means of utility function.