Behavior Decision Model Research Articles

Examining the Theory of Motivated Information Management (TMIM) in the COVID-19 Pandemic

In order to inform understanding of the public’s health information management during the COVID-19 pandemic, we applied a modification of TMIM from a serial mediation model to a conditional process model (moderated mediation). In doing so, the current study attempted to refine some of the relational propositions of the original TMIM with a focus on efficacy while addressing the distinction between a mediator and a moderator in a behavioral decision model. Findings from an online survey of U.S. adults (n = 488) demonstrated that anxiety can positively motivate evaluation of information seeking during the COVID-19 pandemic context, a unique context of application for TMIM. Efficacy was found to be qualified as an individual difference variable that moderates the relationships of uncertainty perception and health decision. Our newly proposed conditional process framework of the TMIM opens research directions in health information-seeking and encourages researchers to continuously incorporate updated methodological thought and approach in applying and building communication theory.

Impact of information processing on individuals’ intentions toward reducing PM2.5: evidence from Hefei City, China

Fine particulate matter (PM2.5) is the main pollutant particle of smog pollution. Public PM2.5-reduction behavior is beneficial and important to the reduction of smog emissions. The article aims to investigate the influencing factors of the intention for individuals’ PM2.5-reduction. A conceptual model was proposed from the perspective of the protection behavior decision model and the heuristic-systematic information processing model. A random questionnaire survey was conducted in Hefei City, China. Results suggest that risk perception is a positive determinant of PM2.5-reduction intention, information insufficiency, and information-seeking intention. Information insufficiency positively determines systematic processing and information-seeking intention but fails to influence heuristic processing. Information-seeking intention is positively correlated with systematic processing and heuristic processing. Systematic processing positively determines PM2.5-reduction intention. However, the results suggest that heuristic processing has no significant effect on PM2.5-reduction intention. The findings of this study provide practical implications for enhancing individuals’ PM2.5-reduction intention.

Study on Behavioral Decision Making by Power Generation Companies Regarding Energy Transitions under Uncertainty

With respect to decision making by companies, normative approaches such as the net present value (NPV) method are widely applied, even though it is known that investors may make non-normative decisions. This study aimed to obtain new information on the decision-making behavior of renewable energy (RE) companies under uncertainty in the energy market, which is not provided by the conventional normative approach. In this study, we designed a novel framework that expressed both normative and non-normative perspectives of decision making, and developed a behavioral decision-making model of a power generation company investing in large-scale RE (RE company). We also examined the decisions of the RE company under uncertainty in the energy market using the developed model, considering the Kansai region in Japan as an example study area. As a result, compared to the conventional NPV method, we obtained the following information: (i) heavy investments in either photovoltaics (PV) or wind resulted in decreased variable renewable energy (VRE) capacity, even though financial support was sufficient; (ii) balanced investments in both PV and wind yielded a larger VRE capacity in cases where financial support was sufficient; and (iii) co-worker’s suggestions that lowered the decision-makers’ reference point (RFP) encouraged VRE investments despite insufficient financial support.

Factors Affecting Compliance to Ethical Standards in Public Procurement in Kenya: A Behavioral Model of Ethical and Unethical Decision Making Perspective

The study sought to investigate the factors affecting compliance to ethical standards in public procurement in Kenya. The study adopted it is specific objectives from a behavioral model of ethical and unethical decision making that is; professionalism factors, social factors, personality factors, legal framework factors and work environment factors on how they affect compliance to ethical standards in public procurement in Kenya. The study adopted descriptive research design as the study design, the population of the study was 40 employees and since the population was small the researcher employed census research design where all employees took part in the research. Primary data collection method was used by administering structured questionnaires. Descriptive statistics, correlation and multiple regression analysis were used to analyze the data. The finding of the study revealed that professionalism factors, legal framework factors, and work environment factors had a positive and statistical significant influence on compliance to ethical standards in public procurement in Kenya. Personal factors and social factors were found not to have statistical significant influence on compliance to ethical standards in public procurement in Kenya. The study recommended that administrative bodies and judiciary should enforce sanction to people who contravenes rules and code of ethics in public procurement. Public organization to invest in training their employees in public procurement code of ethics and rules to avoid the ignorance’s currently observed. This study had implications on knowledge and practices since it did not only investigate factors affecting compliance to ethical standards in public procurement in Kenya but also informed that professionalism factors, legal framework factors and work environment factors were the major factors affecting compliance to ethical standards in public procurement in Kenya.

A fuzzy behavioral portfolio decision model with trapezoidal fuzzy return and aspiration

This paper deals with the stock portfolio selection problem involved with trapezoidal fuzzy number returns and multiple mental accounts. A fuzzy behavioral portfolio decision model is proposed to maximize the possibilistic mean value of portfolio return and ensure the portfolio return of each mental account exceeding the given minimum fuzzy aspiration level with a given probability. Then, some programming models are designed to solve the optimal portfolio strategy. Finally, one numerical example is given to illustrate the effectiveness of the proposed fuzzy behavioral portfolio decision approach.

Tank Behaviour Decision Based on Behaviour Tree and SA-QL

With the wide application of artificial intelligence technology in the military field, unmanned intelligent equipment will play an increasingly important role in the future equipment combat system, and autonomous decision-making ability will directly affect the combat performance of equipment. Therefore, the research on decision-making ability of unmanned intelligent equipment has important practical significance. This paper introduces the principle of behavior tree and SA-QL algorithm, proposes a modeling method of autonomous behavior decision based on behavior tree and SA-QL, and applies it to the construction of tank behavior decision model. By constructing the tank behavior tree model, the autonomous behavior decision is realized, and the tank model has the ability of continuous learning and evolution by using Q learning. Simulation results show that the built tank model can learn new decision instructions according to environmental changes and make behavioral decisions autonomously, which also proves the effectiveness of the proposed modeling method.

An adaptive behavior decision model of mobile robot based on the neuromodulation

How to effectively improve the behavior decision ability in unknown environment is a great challenge for mobile robots. Traditional methods suffer from the low efficiency and large computation load. Motivated by the regulation effect of serotonin and dopamine on human behavior, a novel adaptive behavior decision model for mobile robot is proposed in this work. This model integrates two kinds of adjustment factors that mimic the effects of two neuromodulators, serotonin and dopamine, to regulate the behavior decision of a mobile robot in unknown environment. Adjustment factor $$\mathbf {p}$$ is designed to simulate the function of the serotonin and make the robot avoid obstacles effectively, while the adjustment factor $$\mathbf {r}$$ is designed to simulate the function of the dopamine and make the robot approach the target quickly. Both of the adjustment functions can be adaptively regulated with the robot’s movement. Static and dynamic simulation results show that this neuromodulatory model has excellent collision avoidance capacity which can avoid the obstacles fluently, and the trajectory obtained tends to be optimal. Moreover, it is relatively simple, thus can effectively reduce the computation time and the load capacity, and greatly improve the running efficiency of the mobile robot in unknown environment.

Deterrents of tourism business crowdfunding: Aversion decision and aversion behavior

Crowdfunding has been recently suggested as an effective means for tourism business founders to gain financial support. Yet, few business founders in tourism have employed the method to fund their business creation and development. Using the behavioral decision model in complex and uncertain business situations, this qualitative study explored the deterrents to crowdfunding adoption and the factors that shape the perception of the deterrents in tourism business founders. The data collected by in-depth and face-to-face semi-structured interviews with 22 informants. Our findings revealed a combination of perceived personal, social and contextual deterrents that avert crowdfunding adoption decision and actual behavior. More specifically, our analysis explored attitude towards crowdfunding, perceived control over using crowdfunding, social norms and perceived contextual feasibility of crowdfunding as the determinants of crowdfunding aversion decision and aversion behavior. This study contributes deeper insights into tourism business financial management and crowdfunding policy, theory, practice and research development.

Urban Electric Vehicle Fast-Charging Demand Forecasting Model Based on Data-Driven Approach and Human Decision-Making Behavior

Electric vehicles (EVs) have attracted growing attention in recent years. However, most existing research has not utilized actual traffic data and has not considered real psychological decision-making of owners in analyzing the charging demand. On this basis, an urban EV fast-charging demand forecasting model based on a data-driven approach and human decision-making behavior is presented in this paper. In this methodology, Didi ride-hailing order trajectory data are firstly taken as the original dataset. Through data mining and fusion technology, the regenerated data and rules of traffic operation are obtained. Then, the single EV model with driving and charging behavior parameters is established. Furthermore, a human behavior decision-making model based on Regret Theory is introduced, which comprises the utility of time consumption and charging cost to plan driving paths and recommend fast-charging stations for vehicles. The rules obtained from data mining together with established models are combined to construct the ‘Electric Vehicles–Power Grid–Traffic Network’ fusion architecture. At last, the actual urban traffic network in Nanjing is selected as an example to design the fast-charging demand load experiments in different scenarios. The results demonstrate that this proposed model is able to effectively predict the spatio-temporal distribution characteristics of urban fast-charging demands, and it more realistically simulates the decision-making psychology of owners’ charging behavior.

A Behavioral Portfolio Decision Model with Triangular Fuzzy Number Return and Investor’s Sentiment

This paper deals with a behavioral portfolio decision problem with triangular fuzzy number return. A fuzzy sentimental mean model for behavioral portfolio decision is proposed by taking into account investor’s sentiment and multiple mental accounts. The presented behavioral portfolio decision model maximizes the fuzzy sentimental mean value of portfolio return and ensures the portfolio return of each mental account exceeding the given minimum triangular fuzzy number level with a given possibility degree. Then, multiple programming models are designed to solve the optimal behavioral portfolio strategy. Finally, a numerical example is given to illustrate the validity of the proposed approach.

I Am Innocent: Hourly Variations in Air Pollution and Crime Behavior

I posit that hourly changes in air pollution affect criminality through two distinct pathways, via physiological effects on the criminal and by changes in the tightness of the market for criminal activities. To disentangle individual from market effects, I develop a behavioral model of the individual decision to transgress and a model of search-and-matching frictions between criminals and crime opportunities. The study examines the impact on the four largest cities in North America. Causality emerges from instrumental variable panel-models. Results show that pollution increases violent and unpremeditated crimes while decreasing burglaries and sexual offenses through a reduction of crime opportunities.

UNDERSTANDING DOCTOR DECISION MAKING: THE CASE OF DEPRESSION TREATMENT.

Treatment for depression is complex, requiring decisions that may involve trade-offs between exploiting treatments with the highest expected value and experimenting with treatments with higher possible payoffs. Using patient claims data, we show that among skilled doctors, using a broader portfolio of drugs predicts better patient outcomes, except in cases where doctors' decisions violate loose professional guidelines. We introduce a behavioral model of decision making guided by our empirical observations. The model's novel feature is that the trade-off between exploitation and experimentation depends on the doctor's diagnostic skill. The model predicts that higher diagnostic skill leads to greater diversity in drug choice and better matching of drugs to patients even among doctors with the same initial beliefs regarding drug effectiveness. Consistent with the finding that guideline violations predict poorer patient outcomes, simulations of the model suggest that increasing the number of possible drug choices can lower performance.

A Behavioral Portfolio Model with Interval Return and Investor’s Sentiment

This paper proposes a behavioral portfolio decision model with interval returns and investor’s sentiment. A sentiment-adjusted mean model for behavioral portfolio selection is presented by taking into account investor’s sentiment return and multiple mental accounts. The proposed behavioral model maximizes the sentimental mean value of portfolio interval return and ensures the portfolio interval return of each mental account exceeding the given minimum return level with a given possibility degree. Then, multiple programming models are designed to solve the optimal behavioral portfolio strategy. Finally, a numerical example is given to illustrate the validity of the proposed approach.

Neurocognitive assessment in obsessive compulsive disorder patients: Adherence to behavioral decision models.

In economics, models of decision-making under risk are widely investigated. Since many empirical studies have shown patterns in choice behavior that classical models fail to predict, several descriptive theories have been developed. Due to an evident phenotypic heterogeneity, obsessive compulsive disorder (OCD) patients have shown a general deficit in decision making when compared to healthy control subjects (HCs). However, the direction for impairment in decision-making in OCD patients is still unclear. Hence, bridging decision-making models widely used in the economic literature with mental health research may improve the understanding of preference relations in severe patients, and may enhance intervention designs. We investigate the behavior of OCD patients with respect to HCs by means of decision making economic models within a typical neuropsychological setting, such as the Cambridge Gambling Task. In this task subjects have to decide the amount of their initial wealth to invest in each risky decision. To account for heterogenous preferences, we have analyzed the micro-level data for a more informative analysis of the choices made by the subjects. We consider two influential models in economics: the expected value (EV), which assumes risk neutrality, and a multiple reference points model, an alternative formulation of Disappointment theory. We find evidence that (medicated) OCD patients are more consistent with EV than HCs. The former appear to be more risk neutral, namely, less sensitive to risk than HCs. They also seem to base their decisions on disappointment avoidance less than HCs.

Strategic Corporate Social Responsibility, Sustainable Growth, and Energy Policy in China

China’s economy steps into the “new normal” phase, as it is growing in an innovation-driven instead of a factor-driven mode. In this paper, we constructed the corporate behavioral decision models in different scenarios of policy and analyzed the effect of energy policies on corporate behavior and societal welfare, in a duopoly market. The following conclusions were derived. (1) In a duopoly, the product pricing is irrelevant to the resource cost in their production process. (2) For the firm undertaking the social responsibility, the energy tax imposed by the government would increase either the production or the profit, but decrease the consumer surplus. In contrast, for the other firms, the energy tax rate is opposite to their profit. (3) Low-energy-consuming products will promote efficiency, which reduces either the price or the marginal cost, resulting in a more conspicuous cost advantage to the firm adopting the ecological innovation. (4) The marginal cost for a low-energy-consuming technology research and development steadily decreases, which turns their short-term financial disadvantages into the long-term competitive advantages. The marginal contribution of this paper was to build a simultaneously moving model, in duopoly market, and provide theoretical evidence to endogenize the firm strategy to undertake social responsibilities and to realize sustainable growth.

Does Desperation Breed Deceiver? A Behavioral Model of New Venture Opportunism

We develop a behavioral–decision model to highlight entrepreneurs’ decision making behind venture opportunism. We find that opportunism can present to entrepreneurs and their new ventures a risky yet beneficial choice to secure short–term gains at potential social costs. We posit that, motivated by loss aversion, entrepreneurs may accept the risk and engage in opportunism when their ventures confront economic losses. For instance, a high risk of venture failure may motivate entrepreneurs to act opportunistically in the hope that the failure can be averted. We further posit that such loss–averse decisions will be moderated by the entrepreneurs’ personal bonds to their new ventures. That is, the scale of entrepreneurs’ personal investment in their ventures will intensify their economic loss aversion posed by venture failure risk. In contrast, when entrepreneurs use their personal social capital to support their ventures, they will personally bear more of the down–side risks of opportunistic behavior and thus be less likely to act opportunistically to countervail a potential economic loss. Results based on the data collected from 244 NEEQ–listed new ventures in Beijing and Tianjin in China support our predictions.

Preference Based Subjective Beliefs

We test the empirical content of the assumption of preference dependent beliefs using a behavioral model of strategic decision making in which the rankings of individuals over final outcomes in simple games influence their beliefs over the opponent’s behavior. This approach— by analogy with Psychological Game Theory—allows for interdependence between preferences and beliefs but reverses the order of causality. We use existing evidence from a multi-stage experiment in which we first elicit distributional preferences in a Random Dictator Game, then estimate beliefs in a related 2×2 effort game conditional on these preferences. Our structural estimations confirm our working hypothesis on how social preferences shape beliefs: subjects with higher guilt (envy) expect others to put less (more) effort, which reduces the expected difference in payoffs.

Logistics supply chain management based on business ecology theory

In the same commercial ecosystem, although the different main bodies of logistics service such as transportation, suppliers and purchasers drive their interests differently, all the different stakeholders in the same business or consumers coexist mutually and share resources with each other. Based on this, this paper constructs a model of bonded logistics supply chain management based on the theory of commercial ecology, focusing on the logistics mode of transportation and multi-attribute behavior decision-making model based on the risk preference of the mode of transport of goods. After the weight is divided, this paper solves the model with ELECTRE-II algorithm and provides a scientific basis for decision-making of bonded logistics supply chain management through the decision model and ELECTRE-II algorithm.

Toward a Behavioral Model of Shared Decision Making

Recently, shared decision making (SDM) has come forward as a primary framework for decision making in healthcare. While current works on SDM are mostly grounded on normative and static decision models, this body of research has largely overlooked individuals’ dynamic preferences, emotions and bounded cognitive capacities, which are instead compelling behavioral aspects of any decision space involving two or more individuals, like patients and physicians. In this paper, we address this gap by synthetizing and systematizing the current literature on SDM into key thematic domains. Building on this evidence, we advance a theoretical apparatus of SDM which integrates extant research with insights from the behavioral sciences. The resulting effort offers a behavioral model of SDM. It accounts for a social dimension in the construction of preferences as well as the constraints imposed by bounded rationality and their effects on patient-centered care. Overall, this work locates topical and practical insights as t...

Behavior decision model for park-and-ride facilities utilization

With the accelerated process of urbanization and traffic development, especially the urban rail transit system’s great improvement, Park-and-Ride provides an effective mode for trips between suburbs and downtown. In this research, online and field survey is carried out on the use of Park-and-Ride facilities. Analyses are conducted on personal attributes containing gender, age, and income; the travel characteristics such as driving time during departing from origin to parking lot, parking duration, transfer mode, transfer walking time and waiting time, and transfer times; Park-and-Ride users’ intentions concerned walking time, waiting time, and time looking for parking space; and reasons for Park-and-Ride trip mode not be chosen. On the basis of decomposition for travel procedures, impedance models for different trip modes including public transport, private car, and Park-and-Ride are built and then the multinomial logit model for choice probability of trip modes and Park-and-Ride demand model is established. After further analysis on the survey data, calibrations and tests for the impedance models above are performed. Finally, a case is shown to demonstrate application of the proposed model.