Cognitive Decision-making Processes Research Articles

Development of a Qualitative Assessment Instrument for Cognitive Processes in Gaming Decision

Indonesia ranks 6th with the highest number of online gamers in Asia and 12th in the world gaming market. When online gamers become addicted, they lose the ability to halt or control their gaming behavior, leading to problematic behavior. Decision-making processes at the cognitive level are considered relevant in various addictive behaviors, including inappropriate gaming behavior. Exploratory research can be conducted using a qualitative technique, with data collected through in-depth interviews, to acquire an in-depth understanding of the comparison of the interaction process of each cognitive component in decision-making to play online games. This research was conducted in Bandung from December 2021 to December 2022. Steps are needed to develop guidelines that explore the functioning of affective and cognitive responses (coping, cognitive and affective bias, and craving and urge) and executive and inhibitory control. The guideline used a cognitive theoretical framework in addictive behavior, namely the I-PACE model, with a multidimensional theoretical basis. Through theoretical deepening, it was derived as a guideline divided into three main aspects, four sub-aspects, 32 main questions, and 36 probing questions.

Deciphering Decision Making: The Interplay of Mood States and Decision Styles

Recent theories of Decision- Making have advocated the role of emotions in the cognitive processes of decisions. One such approach is the EIC model (Lerner et al., 2015) which posits – mood to indirectly affect decision making by impacting current emotions, indicating individual’s overall emotional states to indirectly influence cognitive decision processes. The study aimed to understand the role of emotions on decision making and the nuances that underlie it. The 6 main hypothesis of the paper focused on evaluating whether incidental emotions via current emotions affect decision making significantly or do decision styles have a stronger significant effect on decision making. The paper used a mixed method design where the qualitative data was collected via interviews and thematic analysis and labels were attuned via open coding that helped in triangulation and pattern generation. Tools used were the YDMC, Mood induction videos of OPENLAV Database, Decision Style questionnaire (DSQ), Ryff’s well-being scale and an Interview schedule. A purposive sampling was done to obtain the sample (N=29) for the pre-test post-test design. Results for the quantitative data concluded that sad and angry incidental mood had significant effects on FR1 and FR2 (Resistance to Framing and Sunken costs) of YDMC and, that happy mood had no significant effect on risk perception. The decision styles that have been seen to dominate were Vigilant followed by Dependent and Spontaneous style. For qualitative data, based on the dominant responses for the entire sample an Interactive Hexagonal map was constructed. STB (Self -thoughts & Beliefs), FP (Futuristic perspective), CE (Current experiences), EE (Environmental ‌effects), and PEx (Past experiences) were the dominant pattern connections found for the current sample. Thus, Incidental Mood had a significant effect on Resistance to Framing and Sunken costs whereas had no significant effect on Consistency with Risk Perception. Future work on the nuances of mood on decision-making can help determine the affective, cognitive, and neuropsychological models of decision-making where neural correlates could help delve deeper in these higher cognitive and emotional processes.

CONSUMER DEBT MANAGEMENT AMONG GOVERNMENT EMPLOYEES: COGNITIVE, EMOTIONAL AND BEHAVIOURAL

Many people claim that they feel burdened with their debt such as personal loans, hire purchases, housing loans, credit cards, and education loans. The burden that they carry has affected their life such as being unable to pay their debts. They want to live in luxury without thinking about the effect that will drag them to bankruptcy because of many factors that occur while managing their consumer debt. Thus, this study aims to examine the relationship between cognitive, emotional, and behavioural, and consumer debt management among government employees. This study is a descriptive study that distributed a questionnaire to collect the data and used SPSS to analyse the data. The target population is individuals who are employees from government organizations who have experienced using credit for their daily spending, purchasing assets, financing, and investing activities. The questionnaires were equally distributed to 100 employees from 10 government organizations from different positions. It found that there is a significant relationship between behavioural and consumer debt management. However, there is no significant relationship between cognitive and emotional consumer debt management. Good debt management improves the behaviour of government employees to pay their debts every month and understand the relationship between solvency and credit history. In contrast, government employees do not seriously think of their debt and are not emotional when making a decision to do financing. Future research is necessary to investigate how culture and socioeconomic status affect cognitive processes in relation to managing debt. Research should also examine how FinTech applications, including budgeting apps and AI-powered financial guidance, impact individuals' cognitive decision-making processes and their debt management results.

Enhancing Autonomous Operations in Smart Objects and Devices through the Internet of Robotic Things

This study investigates the field of the Internet of Robotic Things (IoRT) and its capacity to transform the functioning of mobile context and robots’ awareness systems. IoRT facilitates autonomous operations in smart objects and devices via the use of data analytics technologies, intelligent data processing tools, deep reinforcement learning, and edge computing techniques. This article examines the use of sensor networks, cloud robotics, machine learning algorithms, and collaborative context-aware robotic networks for the purpose of enhancing job performance, decision-making skills, and operational efficiency in diverse industrial and collaborative settings. The research also investigates the incorporation of route planning tools and motion, cognitive decision-making processes, and sensor data to improve the efficiency of robotic systems in tasks involving object handling. Furthermore, this study investigates the impact of cloud computing, wireless sensor networks, and cognitive approaches on enhancing inventory allocation procedures and company performance. The main purpose of this article is to provide a scholarly contribution to the field of IoRT by exploring its technological advancements and examining its potential applications across many sectors.

Decision-making processes in image guided radiotherapy: A think aloud study

Introduction3D Image Guided Radiotherapy (IGRT) using Cone Beam Computer Tomography (CBCT) has been implemented for a range of treatment sites across the UK in the last decade. A paucity of evidence exists to understand how radiation therapists (RTTs) make clinical decisions during image interpretation as part of the IGRT process. The aim of this study was to investigate the decision-making processes used by RTTs during image interpretation of IGRT. MethodCase study methodology was adopted utilising a think aloud observational method with follow-up interviews. 12 RTTs were observed and interviewed across three UK radiotherapy centres. Participants were observed reviewing and making clinical decisions in a simulated environment using clinical scenarios developed in partnership with each centres’ Clinical Imaging Lead. Protocol analysis was used to analyse the observational data and thematic analysis was used to analyse the interview data. ResultsA range of approaches to decision-making was observed which varied in length from nine phrases to 57 (mean 24) per case. Six themes emerged from the data: Set Sequence, Site Specific Clinical Priorities, Initial Gross Review, Decision to treat, Compromise and experience. In addition, three cognitive decision-making processes were identified: Simple linear, Linear repeating and Intuitive decision-making process. The findings of the study align with general principles of expert performance, whereby experience in a specific scope of practice is more beneficial in developing expertise than overall experience. ConclusionThis study has provided new and original insight in the decision-making processes of RTTs. The study has highlighted three process models to explain how RTTs make decisions during IGRT: Simple linear, Linear repeating and Intuitive decision-making process. Intuitive processes are widely accepted to be error prone and linked to bias. When using this process, some RTTs followed this with a confirmation phase. This second phase of the process should be encouraged when teaching IGRT. The results of the study support the concept of expert performance, where performance and expertise are only improved by exposing individuals to specific types of experiences. RTTs, managers and Higher Education Institutions are encouraged to review these models and implement them into IGRT training. It is clear from the evidence base that understanding how we make decisions, enables us to develop expertise and reduce errors during the decision-making process.

A Large-Scale Group Decision-Making Approach to Assess Water Resource Sustainability with Double-Level Linguistic Preference Relation

With the rapid development of science and technology and the continuous progress of society, water resource sustainability has attracted much attention. The assessment process of water resource sustainability has become a hot topic. Because professional models cannot ensure the accuracy of evaluation results, expert judgment techniques are used to perform the assessment process. Meanwhile, to eliminate the biases and consider people’s cognitive processes in complex decision making, this study utilizes a large group of experts to evaluate the sustainability of water resources, which is called a large-scale group water resource sustainability assessment (LGWRSA). This study proposes the double-level linguistic preference relation (DLLPR) to enable experts to present more reasonable and intuitive linguistic opinions. Based on the DLLPR, this study presents a clustering method, a weighting method, and a comprehensive adjustment factor determination method. To prevent minority opinions and non-cooperative behaviors from interfering with the decision-making process and to make the decision-making process develop in an accurate and objective direction, a consensus model is developed to modify minority opinions and suggestions and manage non-cooperative behaviors. After a sufficient number of experts reach a consensus through the method proposed in this article, a more accurate evaluation result can be obtained. Finally, an actual LGWRSA problem is established to derive water resource sustainability expectations for four provinces, which validates the effectiveness of the proposed method. A comparative analysis is performed to illustrate the benefits of these methods and present their shortcomings.

Layout-Aware Dreamer for Embodied Visual Referring Expression Grounding

In this work, we study the problem of Embodied Referring Expression Grounding, where an agent needs to navigate in a previously unseen environment and localize a remote object described by a concise high-level natural language instruction. When facing such a situation, a human tends to imagine what the destination may look like and to explore the environment based on prior knowledge of the environmental layout, such as the fact that a bathroom is more likely to be found near a bedroom than a kitchen. We have designed an autonomous agent called Layout-aware Dreamer (LAD), including two novel modules, that is, the Layout Learner and the Goal Dreamer to mimic this cognitive decision process. The Layout Learner learns to infer the room category distribution of neighboring unexplored areas along the path for coarse layout estimation, which effectively introduces layout common sense of room-to-room transitions to our agent. To learn an effective exploration of the environment, the Goal Dreamer imagines the destination beforehand. Our agent achieves new state-of-the-art performance on the public leaderboard of REVERIE dataset in challenging unseen test environments with improvement on navigation success rate (SR) by 4.02% and remote grounding success (RGS) by 3.43% comparing to previous previous state of the art. The code is released at https://github.com/zehao-wang/LAD.

The impact of evolved psychological mechanisms on innovation and adoption: A systematic literature review

Studies of the impact of psychological factors and cognitive decision processes, which are often regarded as micro-foundations of innovation and adoption, are a dominant theme in the recent innovation literature. Across a range of disciplines, analysis of the role of evolved psychological mechanisms (EPM) in decision-making has led to dramatic changes in our understanding of motivation and the mechanisms of decision-making. However, the emerging literature applying these findings to innovation and technology management has not been thoroughly assessed. Given the substantial advances in psychology and economics generated by the application of an EPM lens, we undertake a systematic review of innovation, adoption, and resistance literature in which EPMs are applied or considered. This paper synthesizes the existing literature, describes the influence of EPMs on decisions involving new ideas or technologies, proposes Evolutionary Choice Theory (ECT) as a parsimonious and consilient theory of decision-making, and offers pragmatic insights for practitioners to support consistent and effective managerial interventions.

Attentional modulation as a mechanism for enhanced facial emotion discrimination: The case of action video game players

Action video game players (AVGPs) outperform nonvideo game players (NVGPs) on a wide variety of attentional tasks, mediating benefits to perceptual and cognitive decision processes. A key issue in the literature is the extent to which such benefits transfer beyond cognition. Using steady-state visual evoked potentials (SSVEP) as a neural measure of attentional resource allocation, we investigated whether the attentional benefit of AVGPs generalizes to the processing of rapidly presented facial emotions. AVGPs (n = 36) and NVGPs (n = 32) performed a novel, attention-demanding emotion discrimination task, requiring the identification of a target emotion in one of two laterally presented streams of emotional faces. The emotional faces flickered at either 2.0 Hz or 2.5 Hz. AVGPs outperformed NVGPs at detecting the target emotions regardless of the type of emotion. Correspondingly, attentional modulation of the SSVEP at parieto-occipital recording sites was larger in AVGPs compared with NVGPs. This difference appeared to be driven by a larger response to attended information, as opposed to a reduced response to irrelevant distractor information. Exploratory analyses confirmed that this novel paradigm elicited the expected pattern of event-related potentials associated with target detection and error processing. These components did not, however, differ between groups. Overall, the results indicate enhanced discrimination of facial emotions in AVGPs arising from enhanced attentional processing of emotional information. This presents evidence for the attentional advantage of AVGPs to extend beyond perceptual and cognitive processes.

Ethical-deontological problems of therapy of mental disorders

In recent decades, psychiatric ethics has been an area of intensive research and reconsideration of established regulations. Basic principles of medical deontology do not cover ethical issues of modern psychiatric science and practice. The fundamental principle of ethical relationship between a physician and a patient in psychiatric practice is a voluntary informed consent that is based on three main criteria: voluntarism, decision-making capacity and information disclosure about proposed medical procedure. The principle of voluntary informed consent implies a dialogue between a psychiatrist and a patient that rely on the principles of patient's autonomy and does not allow the priority of the paternalistic approach. The physician is obliged to provide all available information on the proposed intervention in a comprehensive way and assess the degree of patient's awareness of this information. The main objective is to determine patient's ability to make decisions as accurately as possible. Many mental disorders affect cognitive processes of decision making and may impact patient's autonomy. It is unacceptable to consider psychiatric patients as incapable of making decisions in advance.

How about choosing environmentally friendly beef? Exploring purchase intentions among Italian consumers

Abstract The increasing global demand for livestock products and its large environmental impact ask for urgent policy and managerial strategies. With regard to meat consumption, feasible actions relate to its reduction and orienting consumers toward more sustainable meat choices. The aim of the study is to investigate the determinants affecting meat consumers in their intention to buy beef whose label clearly expresses environmentally friendly characteristics. To do so, we hypothesized to apply an institutional system of ecological labeling on beef products. An extended framework based on the Theory of Planned Behavior was applied to understand the factors affecting the consumer decision-making process toward eco-labeled beef. A survey was conducted with 1139 consumers in Italy. Data were analyzed by means of confirmatory factor analysis and structural equation models. Results highlight that beef consumers are likely to change their habits, in favor of more sustainable beef choices. The analysis highlights that, together with consumer attitudes, social norms and perceived behavioral control, institutional trust and food shopping habits play an important role in activating the consumer's cognitive decision-making process toward more sustainable beef. Results add to the literature on the determinants of green food-choices and introduce new insights on the role of institutional trust in the intention to buy beef labeled with a public standard. Findings highlight that particular attention should be devoted to build trust for public institutions in order to promote sustainable food consumption behavior. Moreover, results validate previous studies on the effectiveness of information-based policies in fostering more sustainable consumption choices.

Continuous Real-Time Circuit Reconfiguration to Maximize Average Output Power in Cognitive Radar Transmitters

A spectrum sharing radar can be guided by a cognitive decision process to determine the optimal radar operating frequency as the spectral environment changes. This decision process utilizes spectrum sensing or spectral prediction to determine the optimal radar transmission for a given situation. The radar transmitter power amplifier performance varies with frequency and bandwidth of the applied waveform, thus adaptive impedance tuners are useful in maximizing the transmitted power and radar range as the transmission frequency range is varied. Since high power handling is required in radar transmissions, and mechanically actuated impedance tuners presently demonstrate the best power handling, the time required to tune is often orders of magnitude greater than the pulse repetition interval. As such, the relatively lengthy impedance tuning operations should be guided to maximize the average output power as the system transitions between different center frequencies, bandwidths, and waveforms over time. This article presents an algorithm that performs impedance tuning with an evanescent-mode cavity tuner based on an average performance gradient computed for multiple transmit pulses. Comparison of test results with traditionally measured amplifier load-pull data shows that the transmitter is effectively optimized for maximum average output power.

On the Interplay of Data and Cognitive Bias in Crisis Information Management

Humanitarian crises, such as the 2014 West Africa Ebola epidemic, challenge information management and thereby threaten the digital resilience of the responding organizations. Crisis information management (CIM) is characterised by the urgency to respond despite the uncertainty of the situation. Coupled with high stakes, limited resources and a high cognitive load, crises are prone to induce biases in the data and the cognitive processes of analysts and decision-makers. When biases remain undetected and untreated in CIM, they may lead to decisions based on biased information, increasing the risk of an inefficient response. Literature suggests that crisis response needs to address the initial uncertainty and possible biases by adapting to new and better information as it becomes available. However, we know little about whether adaptive approaches mitigate the interplay of data and cognitive biases. We investigated this question in an exploratory, three-stage experiment on epidemic response. Our participants were experienced practitioners in the fields of crisis decision-making and information analysis. We found that analysts fail to successfully debias data, even when biases are detected, and that this failure can be attributed to undervaluing debiasing efforts in favor of rapid results. This failure leads to the development of biased information products that are conveyed to decision-makers, who consequently make decisions based on biased information. Confirmation bias reinforces the reliance on conclusions reached with biased data, leading to a vicious cycle, in which biased assumptions remain uncorrected. We suggest mindful debiasing as a possible counter-strategy against these bias effects in CIM.

Understanding Clinician Macrocognition to Inform the Design of a Congenital Heart Disease Clinical Decision Support System.

Background and ObjectivesChildren with congenital heart disease (CHD) are at risk of deterioration in the face of common childhood illnesses, and their resuscitation and acute treatment requires guidance of CHD experts. Many children with CHD, however, present to their local emergency departments (ED) with gastrointestinal and respiratory symptoms that closely mimic symptoms of CHD related heart failure. This can lead to incorrect or delayed diagnosis and treatment where CHD expertise is limited. An understanding of the differences in cognitive decision-making processes between CHD experts and ED physicians can inform how best to support ED physicians when treating CHD patients.MethodsCardiac intensivists (CHD experts) and pediatric emergency department physicians (ED physicians) in a major academic cardiac center were interviewed using the critical decision method. Interview transcripts were coded deductively based on Schubert and Klein's macrocognitive frameworks and inductively to allow for new or modified characterization of dimensions.ResultsIn total, 6 CHD experts and 7 ED physicians were interviewed for this study. Although both CHD experts and ED physicians spent a lot of time sensemaking, their approaches to sensemaking differed. CHD experts reported readily recognizing the physiology of complex congenital heart disease and focused primarily on ruling out cardiac causes for the presenting illness. ED physicians reported a delay in attributing the signs and symptoms of the presenting illness to congenital heart disease, because these clinical findings were often non-specific, and thus explored different diagnoses. CHD experts moved quickly to treatment and more time anticipating potential problems and making specific contingency plans, while ED physicians spent more time gathering a range of data prior to arriving at a diagnosis. These findings were then applied to develop a prototype web-based decision support application for patients with CHD.ConclusionThere are differences in the cognitive processes used by CHD experts and ED physicians when managing CHD patients. An understanding of differences in the cognitive processes used by CHD experts and ED physicians can inform the development of potential interventions, such as clinical decision support systems and training pathways, to support decision making pertaining to the acute treatment of pediatric CHD patients.

Method for Evaluation and Application of Production Process Chain Complexity in Sewing Workshops considering Human Factor

Existing methods for evaluating manufacturing process chain complexity consider the number of machines, state of machines, number of parts, operation time, and processing sequence of parts. However, such evaluation methods ignore human factors. To consider human factors, human cognitive decision‐making process factors are considered in the complexity evaluation of production processes. Accordingly, a new objective evaluation method of the human factor complexity is proposed. In the proposed method, sewing operations are taken as an example, and the human factor complexity is classified into perceived and cognitive complexity. Information entropy is used to measure cognitive complexity according to the type and quantity of sewing workers’ cognitive activities. The results show that various methods have significant differences in the evaluation of the complexity level of the production process chain. Specifically, the calculation results of the proposed evaluation method are much greater than those of other methods. This indicates that human cognitive and perceived complexities account for a large proportion. Therefore, human factor complexity cannot be omitted.

A cognitive and participative decision-making model for transportation planning under different uncertainty levels

Decision-making processes related to transportation systems are often very complex, belonging to the class of “wicked problems” in social studies. The literature and the media abound in examples of transportation planning “failures” including decisions made, delayed or withdrawn without any traceable motivations, public opposition, public opposition, extra costs/implementation times and outright cancellation, wrong traffic/revenue forecasts. Planning failures stem from several causes, including technical errors in forecasting predictable effects, lack of consensus, new governance cycles and inability to recognize the intrinsic uncertainty affecting some key variables. The underlying assumption of this paper is that the quality of the decision-making process critically depends on how the process is structured and managed. The paper proposes a conceptual model to represent and organize transport planning as a cognitive decision-making process with strong involvement of different stakeholders in various stages, accounting for different levels of uncertainty and including short- and long-term decisions options. The result is a planning process that allows for changes in objectives, strategies and decisions during different stages of the process itself, as is usually the case when different governance and socio-economic cycles succeed over time. However, the process maintains a form of procedural consistency and is intended to counteract the “Penelope syndrome”, whereby decisions made under previous governance cycles are undone regardless of their merits and costs. The real-life implementation of the proposed model requires strong “political commitment” to an open and accountable decision-making process, a technical structure able to act as “process owner” coordinating technical and engagement activities, and a general societal attitude towards organized participation to public decision making. The proposed model was applied to the Regional Transportation Plan of Veneto in Italy where the above conditions applied. A number of lessons were learnt from that exercise: i) stakeholders’ engagement revealed an important potential to manage uncertainty and increase consensus; ii) flexibility and robustness with respect to medium–to–high uncertainty levels already recognized at the time of the plan (immediately before the COVID-19 crisis) were an appreciated feature of the plan; iii) separation between mature decisions and those needing further analysis was a success strategy, reducing political “decision costs” (from naysaying) by delaying decisions still recognizing underlying needs; iv) reduced decision time (a largely bi-partisan vote in less than one year).

Utilizing a cognitive engineering approach to conduct a hierarchical task analysis to understand complex older adult decision-making during over-the-counter medication selection.

Adults aged 65+ (older adults) disproportionately consume 30% of over-the-counter (OTC) medications and are largely responsible for making OTC treatment decisions because providers lack awareness of their consumption. These treatment decisions are complex: older adults must navigate age-related body/cognitive changes, developed comorbidities, and complex medication regimens when selecting the right OTC. Yet little is known about how older adults make such decisions. This study characterizes older adults' cognitive decision-making process when seeking to self-medicate with OTCs from their community pharmacy, and demonstrates how hierarchical task analysis (HTA) can be used to evaluate a pharmacy intervention's impact on their decision-making. A pre-/post-implementation approach, using a think-aloud interview process, was conducted with older adults within a community pharmacy setting as they completed a hypothetical scenario to treat either pain, sleep, or cough/cold/allergy symptoms. HTA developed a conceptualization of older adult decision-making regarding OTC selection and use before/after Senior Section implementation. An HTA constructed from 12 purposefully-selected interviews (pre-n=9/post-n=3), consisting of 8 goals/15 sub-goals. While selecting an OTC, older adults considered quantity, cost, form, regimen, safety, strength, appropriateness of OTC safety, generic/name-brand, past experiences, and ingredients. The intervention reduced by half the number of factors considered. Older adult decision-making is more complex than just selecting OTC medication from a pharmacy shelf. HTA-informed decision profiles can provide pharmacists critical insights into safety issues that older adults may not be considering (e.g., factors related to safety, strength, or appropriateness of OTC for symptoms) so that pharmacists can support their decision-making.

Evolutionary Game and Numerical Simulation of Cultivated Land Protection Policies Implementation in China

The effective implementation of cultivated land protection policies (CLPP) has important practical significance for improving China’s food security and ecological security. The central government, local governments, and farmers have mutually restricted and influencing interest relations. At the same time, the codes of behavior of multistakeholders also affect the implementation of CLPP in the social system. Therefore, this article discusses the behavioral tendencies and game relationships of relevant stakeholders in the implementation of CLPP from the perspective of evolutionary games and portrays a cognitive decision-making process closer to reality. Finally, numerical simulation reveals the key variables that affect the stability strategy. Results show the following: (1) As the main body of system supply, the central government should reconstruct the political achievement evaluation system and improve the status of the effective implementation of cultivated protection policies in the political achievement evaluation of local governments. (2) The central government should increase incentives for local governments to implement CLPP and increase penalties for violations to improve the effectiveness of policy implementation. (3) To optimize the actual implementation of CLPP, increasing awareness of farmers’ rights protection, reducing rights protection costs of farmers, and increasing the constraints on the flexible implementation of CLPP are necessary.

Interval-Valued Hesitant Fuzzy Linguistic Multiattribute Decision-Making Method Based on Three-Parameter Heronian Mean Operators

Numerous variants have been proposed for sets of linguistic terms and the interval-valued hesitant fuzzy set (IVHFS). In particular, the interval-valued hesitant fuzzy linguistic set (IVHFLS) is more suitable for defining the hesitancy and inconsistency inherent in the human cognitive processes of decision making. A key aggregation operator is Heronian mean (HM), based on which the correlation among aggregated arguments can be captured. However, the existing HM operators partially overlook the correlation among more than two arguments and lack the properties of idempotency and reducibility. In this work, the limitations of HM operators are first analyzed. Then, two new HM variants are introduced: three-parameter weighted Heronian mean (TPWHM) and three-parameter weighted geometric Heronian mean (TPWGHM). Thus, the reducibility, idempotency, monotonicity, and boundedness properties are proven for the two computational procedures, and unique situations are mentioned. Furthermore, two more elaborate operators are also introduced which are called the interval-valued hesitant fuzzy linguistic TPWHM (IVHFLTPWHM) and the interval-valued hesitant fuzzy linguistic TPWGHM (IVHFLTPWGHM). The main properties, as well as unique situations of these two computational procedures, are discussed. Finally, the introduced methods are clarified by illustrative examples. In addition, the parameter effects on the decision-making outcomes are discussed and comparisons with other reference methods are made.

278 Understanding Biosecurity Perceptions in Pennsylvania Pig Producers

Abstract The group mental model of swine-related biosecurity for producers and experts was assessed and compared using network analysis. The proper implementation of biosecurity plans reduces the risk of biological hazards that could cripple the industry. Recently collected survey data show producer motivation to adopt a biosecurity protocol is not driven solely by the value of the operation (Hines and Falcone, unpublished). Other motivating factors exist for how producers perceive risk relating to biosecurity management. To identify how pig producers and experts conceptualize biosecurity, open-ended survey questions were asked. Survey responses (n = 123) were coded using a newly developed codebook. Intercoder reliability was established using Krippendorff’s a. Code co-occurrence was used to build a network diagram showing producer and expert mental models, or depiction of the interdependent relationships among values, beliefs, behavior, and cognitive processes of decision making. Analyses of code co-occurrence revealed differences between producers and experts. The results suggest PA-based producers think of biosecurity relating to the protection of their property (ie. inward protection) which was closely associated with limiting access of “outsiders.” Also, the mental model diagram suggests producers think about biosecurity more broadly due to less clustering of ideas. Whereas experts think about biosecurity more specifically relating to two to three themes. Specifically, the expert biosecurity diagram revealed record keeping as an important component of biosecurity, which was strongly related to how experts think about cleanliness and limiting outsider access. Regarding strategies to address biohazard risks, both producers and experts recognize several options. However, experts proved to have stronger connections between concepts. Specifically, the diagrams revealed experts see all strategies as connected. From an expert perspective, strategies to address biohazard risks should be implemented simultaneously. These findings are the first step to designing communication to bridge the gaps between expert and producer understanding of biosecurity.