Supply chain management is critical for addressing uncertainties caused by random demand and production yield. In this study, a random yield supply chain, in which the production process of fresh agricultural products is easily affected by factors, such as weather, soil, or plant diseases and insect pests, was considered. Therefore, the actual output is typically less than the planned output. A model in which the producer faces yield uncertainty was considered, and the influence of the producer’s fairness concerns on (...) the planned output of the contract-farming supply chain was considered. Methods to motivate the producer to increase planned output through reasonable contracts were investigated. The results revealed that the producer’s fairness concern considerably influences the optimal expected profit. In the case of the random output, the planned output and maximum expected profits reduce when the farmer exhibits fairness concerns. As the degree of the producer’s fairness concern increases, the planned output and expected profit gradually decrease The cost-sharing contract can effectively encourage the producer to increase his planned output and expected utility. Finally, the results were verified numerically. (shrink)

This paper develops hypotheses about the implications of different types of decision for the utilization of different types of systematically produced information: data, research, and analysis. The engineering and enlightenment models found in the knowledge utilization literature prove inadequate for this purpose. We turn to three decision models—routine, incremental, and fundamental–and determine their implied demands for information. We also examine how information might be used in scanning procedures in anticipation of decision regime shifts. The results suggest that (...) patterns of information should differ markedly in each decision context and indicate that there may be an inherent bias against the use of research in decision. (shrink)

Classroom cases and decision making models used in the teaching of business ethics may be inconsistent with the actual needs of practicing manager students. Three summary cases written by practicing manager students are included in this paper as well as evidence that concerns a focus more on interpersonal dilemmas rather than top management decisions. As well, the relevancy of philosophical perspectives of ethical decision models is questioned. More practical, hands-on models for ethical decisions are provided. Finally, conclusions of (...) relevancy for the field are drawn. (shrink)

This paper describes a decision model for an autonomous agent that provides an inhabitant with comfort based on information network technologies that connect home electric appliances with household equipment. The inhabitant enjoys the benefit of comfort, while he pays the cost for keeping that comfort. The autonomous agent should decide and control household equipment considering that cost from the inhabitant’s viewpoint. Thus, we utilized a representation scheme called an “influence diagram” that enabled us to model the (...) class='Hi'>decision-making process of the agent from the inhabitant’s point of view. First, decision modeling using the influence diagram is presented via an example. The presented model consists of three information-processing modules: a module for estimating the situation of an inhabitant based on information from home networks, a module for evaluating comfort of the inhabitant, and a module for making decisions that maximize the utility of the inhabitant from both the viewpoints of comfort and the cost paid for that comfort. Next, an experiment for verifying whether the presented model is effective or not, and its results are described. Finally, our model of the agent is discussed in relation to social intelligence design by investigating the interactive processes between the agent and the inhabitant. (shrink)

In recent years quantum probability models have been used to explain many aspects of human decision making, and as such quantum models have been considered a viable alternative to Bayesian models based on classical probability. One criticism that is often leveled at both kinds of models is that they lack a clear interpretation in terms of psychological mechanisms. In this paper we discuss the mechanistic underpinnings of a quantum walk model of human decision making and response time. (...) The quantum walk model is compared to standard sequential sampling models, and the architectural assumptions of both are considered. In particular, we show that the quantum model has a natural interpretation in terms of a cognitive architecture that is both massively parallel and involves both co-operative and competitive interactions between units. Additionally, we introduce a family of models that includes aspects of the classical and quantum walk models. (shrink)

Parametric cognitive models are increasingly popular tools for analyzing data obtained from psychological experiments. One of the main goals of such models is to formalize psychological theories using parameters that represent distinct psychological processes. We argue that systematic quantitative reviews of parameter estimates can make an important contribution to robust and cumulative cognitive modeling. Parameter reviews can benefit model development and model assessment by providing valuable information about the expected parameter space, and can facilitate the more efficient design (...) of experiments. Importantly, parameter reviews provide crucial—if not indispensable—information for the specification of informative prior distributions in Bayesian cognitive modeling. From the Bayesian perspective, prior distributions are an integral part of a model, reflecting cumulative theoretical knowledge about plausible values of the model's parameters (Lee,2018). In this paper we illustrate how systematic parameter reviews can be implemented to generate informed prior distributions for the Diffusion Decision Model (DDM; Ratcliff and McKoon,2008), the most widely used model of speeded decision making. We surveyed the published literature on empirical applications of the DDM, extracted the reported parameter estimates, and synthesized this information in the form of prior distributions. Our parameter review establishes a comprehensive reference resource for plausible DDM parameter values in various experimental paradigms that can guide future applications of the model. Based on the challenges we faced during the parameter review, we formulate a set of general and DDM-specific suggestions aiming to increase reproducibility and the information gained from the review process. (shrink)

Increasing numbers of decisions about everyday life are made using algorithms. By algorithms we mean predictive models captured from historical data using data mining. Such models often decide prices we pay, select ads we see and news we read online, match job descriptions and candidate CVs, decide who gets a loan, who goes through an extra airport security check, or who gets released on parole. Yet growing evidence suggests that decision making by algorithms may discriminate people, even if the (...) computing process is fair and well-intentioned. This happens due to biased or non-representative learning data in combination with inadvertent modeling procedures. From the regulatory perspective there are two tendencies in relation to this issue: to ensure that data-driven decision making is not discriminatory, and to restrict overall collecting and storing of private data to a necessary minimum. This paper shows that from the computing perspective these two goals are contradictory. We demonstrate empirically and theoretically with standard regression models that in order to make sure that decision models are non-discriminatory, for instance, with respect to race, the sensitive racial information needs to be used in the model building process. Of course, after the model is ready, race should not be required as an input variable for decision making. From the regulatory perspective this has an important implication: collecting sensitive personal data is necessary in order to guarantee fairness of algorithms, and law making needs to find sensible ways to allow using such data in the modeling process. (shrink)

Self-disclosures on online social networks have received increased attention in the last two decades. Researchers from different disciplines investigated manifold influencing variables, and studies applied different theories to explain why many users share very sensitive and personal information despite potential risks and negative consequences, whereas others do not. Oftentimes, it is argued that self-disclosure decisions result from a kind of rational “calculus” of risks and benefits. However, such an assumption of rationality can and has been criticized. Nevertheless, fundamental cognitive and (...) affective mechanisms that underlie self-disclosure decision making on social networks are still under-explored. By building upon previous self-disclosure theories and models, dual-and tripartite-system perspectives of decision making, and former empirical findings, we propose a Tripartite Self-Disclosure Decision model that conceptualizes inner processes of online self-disclosure decision making. Central to this model is the proposed interaction of three neural and cognitive/affective systems: a reflective, an impulsive, and an interoceptive system. We further highlight individual and environmental features, which can impact individuals’ online self-disclosure decisions by influencing the proposed inner decision-making processes targeting the aforementioned three systems. Possible short- and long-term consequences are also discussed, which in turn can affect certain model components in subsequent self-disclosure decision situations. By taking such a neurocognitive perspective, we expand current research and models, which helps to better understand potentially risky information sharing on online social networks and can support attempts to prevent users from incautious self-disclosures. (shrink)

Much of our understanding of human thinking is based on probabilistic models. This innovative book by Jerome R. Busemeyer and Peter D. Bruza argues that, actually, the underlying mathematical structures from quantum theory provide a much better account of human thinking than traditional models. They introduce the foundations for modelling probabilistic-dynamic systems using two aspects of quantum theory. The first, 'contextuality', is a way to understand interference effects found with inferences and decisions under conditions of uncertainty. The second, 'quantum entanglement', (...) allows cognitive phenomena to be modeled in non-reductionist ways. Employing these principles drawn from quantum theory allows us to view human cognition and decision in a totally new light. Introducing the basic principles in an easy-to-follow way, this book does not assume a physics background or a quantum brain and comes complete with a tutorial and fully worked-out applications in important areas of cognition and decision. (shrink)

A review of the literature indicates that linear models are frequently used in situations in which decisions are made on the basis of multiple codable inputs. These models are sometimes used normatively to aid the decision maker, as a contrast with the decision maker in the clinical vs statistical controversy, to represent the decision maker "paramorphically" and to "bootstrap" the decision maker by replacing him with his representation. Examination of the contexts in which linear models have (...) been successfully employed indicates that the contexts have the following structural characteristics in common: each input variable has a conditionally monotone relationship with the output; there is error of measurement; and deviations from optimal weighting do not make much practical difference. These characteristics ensure the success of linear models, which are so appropriate in such contexts that random linear models may perform quite well. 4 examples involving the prediction of such codable output variables as GPA and psychiatric diagnosis are analyzed in detail. In all 4 examples, random linear models yield predictions that are superior to those of human judges. (shrink)

The options in a decision problem generally have outcomes with common features. Putting aside the common features simplifies deliberations, but the simplification requires a philosophical justification that this book provides.

Inspired by recent Bayesian interpretations about the psychology underlying religion, the paper introduces a theory proposing that religious conversion is shaped by three factors: (i) novel relevant information, experienced in perceptual or in social form (e.g., following interaction with missionaries); (ii) changes in the utility (e.g., expressed in an opportunity to raise in social rank) associated with accepting a new religious creed; and (iii) prior beliefs, favouring religious faiths that, although new, still remain consistent with entrenched cultural views (resulting in (...) the phenomenon of syncretism). From the theory, a multifactorial picture of conversion emerges. Based on which factor is primarily engaged in each case, a classification of different types of conversion can be derived, with a remarkable fit with empirical literature. The theory offers a description of the processes underlying religious conversion and, highlighting the links among apparently incompatible previous views, it reconciles these views within a unifying framework. (shrink)

The relationship between mental models and ethical decision making, along with the mechanisms through which mental models affect EDM, are not well understood. Using the sensemaking approach to EDM, we empirically tested the relationship of mental models to EDM. Participants were asked to depict their mental models in response to an ethics case to reveal their understanding of the ethical dilemma, and then provide a response, along with a rationale, to a different ethical problem. Findings indicated that complexity of (...) respondents’ mental models was related to EDM, and that this relationship was mediated by sensemaking processes. The implications of these findings for improving integrity training in organizations, as well as ultimately understanding the role of mental models in EDM, are discussed. (shrink)

Using a decision theoretic model of scientists’ time allocation between potential research projects I explain the fact that on average women scientists publish less research papers than men scientists. If scientists are incentivised to publish as many papers as possible, then it is necessary and sufficient for a productivity gap to arise that women scientists anticipate harsher treatment of their manuscripts than men scientists anticipate for their manuscripts. I present evidence that women do expect harsher treatment and that (...) scientists’ are incentivised to publish as many papers as possible, and discuss some epistemological consequences of this conjecture. (shrink)

The managerial ethics literature is used as a base for the inclusion of Ethical Attribution, as an element in the consumer's decision process. A situational model of ethical consideration in consumer behavior is proposed and examined for Personal vs. Vicarious effects. Using a path analytic approach, unique structures are reported for Personal and Vicarious situations in the evaluation of a seller's unethical behavior. An attributional paradigm is suggested to explain the results.

For linear distribution classes, mean-variance and expected utility specifications have been shown in the literature to be fully compatible when studying the concepts of risk aversion, prudence, risk vulnerability and temperance. This paper shows that such compatibility does hold for the concept of standard risk aversion but not for the concepts of proper risk aversion and proper prudence.

A discussion of ethical decision-making literature is overdue. In this article, we summarize the current literature of ethical decision-making models used in mental health professions. Of 1,520 articles published between 2001 and 2020 that met initial search criteria, 38 articles were included. We report on the status of empirical evidence for the use of these models along with comparisons, limitations, and considerations. Ethical decision-making models were synthesized into eight core procedural components and presented based on the composition (...) of steps present in each model. This taxonomy provides practitioners, trainers, students, and supervisors relevant information regarding ethical decision-making models. (shrink)

Under the independence and competence assumptions of Condorcet’s classical jury model, the probability of a correct majority decision converges to certainty as the jury size increases, a seemingly unrealistic result. Using Bayesian networks, we argue that the model’s independence assumption requires that the state of the world (guilty or not guilty) is the latest common cause of all jurors’ votes. But often – arguably in all courtroom cases and in many expert panels – the latest such common (...) cause is a shared ‘body of evidence’ observed by the jurors. In the corresponding Bayesian network, the votes are direct descendants not of the state of the world, but of the body of evidence, which in turn is a direct descendant of the state of the world. We develop a model of jury decisions based on this Bayesian network. Our model permits the possibility of misleading evidence, even for a maximally competent observer, which cannot easily be accommodated in the classical model. We prove that (i) the probability of a correct majority verdict converges to the probability that the body of evidence is not misleading, a value typically below 1; (ii) depending on the required threshold of ‘no reasonable doubt’, it may be impossible, even in an arbitrarily large jury, to establish guilt of a defendant ‘beyond any reasonable doubt’. (shrink)

The basic methodology of rough set theory depends on an equivalence relation induced from the generated partition by the classification of objects. However, the requirements of the equivalence relation restrict the field of applications of this philosophy. To begin, we describe two kinds of closure operators that are based on right and left adhesion neighbourhoods by any binary relation. Furthermore, we illustrate that the suggested techniques are an extension of previous methods that are already available in the literature. As a (...) result of these topological techniques, we propose extended rough sets as an extension of Pawlak’s models. We offer a novel topological strategy for making a topological reduction of an information system for COVID-19 based on these techniques. We provide this medical application to highlight the importance of the offered methodologies in the decision-making process to discover the important component for coronavirus infection. Furthermore, the findings obtained are congruent with those of the World Health Organization. Finally, we create an algorithm to implement the recommended ways in decision-making. (shrink)

I model sequential decisions over multiple interconnected propositions and investigate path-dependence in such decisions. The propositions and their interconnections are represented in propositional logic. A sequential decision process is path-dependent if its outcome depends on the order in which the propositions are considered. Assuming that earlier decisions constrain later ones, I prove three main results: First, certain rationality violations by the decision-making agent—individual or group—are necessary and sufficient for path-dependence. Second, under some conditions, path-dependence is unavoidable in (...) decisions made by groups. Third, path-dependence makes decisions vulnerable to strategic agenda setting and strategic voting. I also discuss escape routes from path-dependence. My results are relevant to discussions on collective consistency and reason-based decision-making, focusing not only on outcomes, but also on underlying reasons, beliefs, and constraints. (shrink)

We develop a model of ethical decision making that integrates the decision-making process and the content variables considered by individuals facing ethical dilemmas. The process described in the model is drawn from Janis and Mann’s [1977, Decision Making: A Psychological Analysis of Conflict Choice and Commitment (The Free Press, New York)] work describing the decision process in an environment of conflict, choice and commitment. The model is enhanced by the inclusion of content variables (...) derived from the ethics literature. The resulting integrated model aids in understanding the complexity of the decision process used by individuals facing ethical dilemmas and suggests variable interactions that could be field-tested. A better understanding of the process will help managers develop policies that enhance the likelihood of ethical behavior in their organizations. (shrink)

A model is presented which describes the process decision-makers follow when faced with problems containing ethical dimensions. The model, based upon the empirical literature, is designed to provide guidance to researchers studying ethical behavior in business. The model portrays the decision-maker with a set of personal values which are mediated by elements of the organization's culture. The combination of personal values and organizational influences yields decisions which may be significantly different from those made based upon (...) personal values alone. Inclusion of the personal values of the decision-maker as the dominant individual input and an explicit discussion of the ethical decision process make this model more comprehensive than other recent ethics models. (shrink)

A common financial model used in business decisions is the cost/benefit comparison. The costs of a proposed project are compared with the benefits, and if the benefits outweigh the costs, the project is accepted; if the costs exceed the benefits, the project is rejected. This model is applicable when tangible costs and benefits can be reasonably measured in monetary units. However, it is difficult to consider intangible factors in this model because intangible factors cannot be readily quantified (...) in money.While some might argue that the financial model should not apply to healthcare decisions, the fact is that costs do enter into the picture. People may decide to forego needed healthcare because they cannot afford it. Healthcare providers may make choices based in part on the costs of diagnosis and treatment, rather than solely on medical information and what is best for the patient. Should financial issues enter into healthcare decisions – decisions about human health and well being? If so, how should the costs and benefits be measured and evaluated? What are some ethical issues and dilemmas involved in such decisions? (shrink)

In this paper we explore the connections between ethics and decision theory. In particular, we consider the question of whether decision theory carries with it a bias towards consequentialist ethical theories. We argue that there are plausible versions of the other ethical theories that can be accommodated by “standard” decision theory, but there are also variations of these ethical theories that are less easily accommodated. So while “standard” decision theory is not exclusively consequentialist, it is not (...) necessarily ethically neutral. Moreover, even if our decision-theoretic models get the right answers vis-`a-vis morally correct action, the question remains as to whether the motivation for the non-consequentialist theories and the psychological processes of the agents who subscribe to those ethical theories are lost or poorly represented in the resulting models. (shrink)

In this topical section, we highlight the next step of research on modeling aiming to contribute to the emerging literature that radically refrains from approaching modeling as a scientific endeavor. Modeling surpasses “doing science” because it is frequently incorporated into decision-making processes in politics and management, i.e., areas which are not solely epistemically oriented. We do not refer to the production of models in academia for abstract or imaginary applications in practical fields, but instead highlight the real entwinement of (...) science and policy and the real erosion of their boundaries. Models in decision making – due to their strong entwinement with policy and management – are utilized differently than models in science; they are employed for different purposes and with different constraints. We claim that “being a part of decision-making” implies that models are elements of a very particular situation, in which knowledge about the present and the future is limited but dependence of decisions on the future is distinct. Emphasis on the future indicates that decisions are made about actions that have severe and lasting consequences. In these specific situations, models enable not only the acquisition of knowledge (the primary goal of science) but also enable deciding upon actions that change the course of events. As a result, there are specific ways to construct effective models and justify their results. Although some studies have explored this topic, our understanding of how models contribute to decision making outside of science remains fragmentary. This topical section aims to fill this gap in research and formulate an agenda for additional and more systematic investigations in the field. (shrink)