Search

Respondent burden is considered a decisive factor affecting response quality in web surveys. To investigate the objective and perceived burden on web survey respondents and its effects on response quality, we conducted a web survey among members of a German online access panel using a questionnaire with a completely randomized question order and measures of perceived burden at four time points. We found that perceived burden increased only slightly during the survey, suggesting that objective burden―as measured by the position of a question in the questionnaire―has a modest impact on the level of perceived burden. Although the position of a question in the questionnaire also had little effect on response quality, higher perceived burden consistently resulted in lower response quality. [ABSTRACT FROM AUTHOR]

The risk of multitasking is high in online surveys. However, knowledge on the effects of multitasking on answer quality is sparse and based on suboptimal approaches. Research reports inconclusive results concerning the consequences of multitasking on task performance. However, studies suggest that especially sequential-multitasking activities are expected to be critical. Therefore, this study focusses on sequential-on-device-multitasking activities (SODM) and its consequences for data quality. Based on probability-based data, this study aims to reveal the prevalence of SODM based on the javascript function OnBlur, to reflect the its determinants and to examine the consequences for data quality. Results show that SODM was detected for 25% of all respondents and that respondent attributes and the device used to answer the survey are related to SODM. Moreover, it becomes apparent that SODM is significantly correlated to data quality measures. Therefore, I propose SODM behavior as a new instrument for researching suboptimal response behavior. [ABSTRACT FROM AUTHOR]

In this paper, we address the issue of whether to optimize or satisfice in model-based engineering design. When dealing with operations research problems in the context of engineering design, one may encounter (i) nonlinear, nonconvex objectives and constraints, (ii) objectives with different units, and (iii) computational models that are abstractions of reality and fidelity, Seeking a single-point optimal solution that meets the necessary and sufficient Karush–Kuhn–Tucker (KKT) conditions makes it impossible to obtain a solution that satisfies all the targeted goals. Instead, a method to identify satisficing solutions that satisfies necessary KKT condition but not the sufficient condition is proposed. These solutions are relatively robust, easy to acquire, and often good enough. In this paper, we demonstrate the combined use of the compromise Decision Support Problems and the adaptive linear programming algorithm, as proposed by Mistree and co-authors. This method is appropriate in formulating design problems and obtaining solutions that satisfy only the necessary KKT condition. Further, the use of the proposed method circumvents complications associated with the use of gradient-based optimization algorithms typically used to solve optimization problems. We discuss the efficacy of our proposed method using four test problems to illustrate how the satisficing strategy outperforms the optimizing strategy in model-based engineering design. [ABSTRACT FROM AUTHOR]

Incentive contracts often do not govern all task elements for which an employee is responsible. Prior research, particularly in the tradition of principal-agent theory, has studied incomplete incentive contracts as multi-task problems focusing on how to motivate the employee to incur effort for a not-contracted task element. Thus, emphasis is on the "vertical" relation between superior and subordinate, where both are modeled as gifted economic actors. This paper takes another perspective focusing on the "horizontal" interferences of—contracted and not-contracted—task elements across various employees in an organization and, hence, on the complexity of an organization's task environment. In order to disentangle the interactions among tasks from agents' behavior, the paper pursues a minimal intelligence approach. An agent-based simulation model based on the framework of NK fitness landscapes is employed. In the simulation experiments, artificial organizations search for superior performance, and the experiments control for the complexity of the task environment and the level of contractual incompleteness. The results suggest that the complexity of the task environment in terms of interactions among task elements may considerably shape the effects of incomplete incentive contracts. In particular, the results indicate that moderate incompleteness of incentive contracts may be beneficial with respect to organizational performance when intra-organizational complexity is high. This is caused by stabilization of search resulting from incomplete contracts. Moreover, interactions may induce that the not-contracted task elements could serve as means objectives, i.e., contributing to achieving contracted task elements. [ABSTRACT FROM AUTHOR]

Background: Uncertainty poses a pervasive challenge in decision analysis and risk management. When the problem is poorly understood, probabilistic estimation exhibits high variability and bias. Analysts then utilize various strategies to find satisficing solutions, and these strategies can sometimes adequately address even highly complex problems. Previous literature proposed a hierarchy of uncertainty, but did not develop a quantitative score of analytical complexity. Methods: In order to develop such a score, this study reviewed over 90 strategies to cope with uncertainty, including methods utilized by expert decision-makers such as engineers, military planners and others. Results: It found that many decision problems have pivotal properties that enable their solution despite uncertainty, including small action space, reversibility and others. The analytical complexity score of a problem could then be defined based on the availability of these properties. [ABSTRACT FROM AUTHOR]

This note in the Milestones series is dedicated to the paper "A Behavioral Model of Rational Choice", written by Herbert Simon and published in 1955 on the Quarterly Journal of Economics. [ABSTRACT FROM AUTHOR]

Inferential decision-making algorithms typically assume that an underlying probabilistic model of decision alternatives and outcomes may be learned a priori or online. Furthermore, when applied to robots in real-world settings they often perform unsatisfactorily or fail to accomplish the necessary tasks because this assumption is violated and/or because they experience unanticipated external pressures and constraints. Cognitive studies presented in this and other papers show that humans cope with complex and unknown settings by modulating between near-optimal and satisficing solutions, including heuristics, by leveraging information value of available environmental cues that are possibly redundant. Using the benchmark inferential decision problem known as “treasure hunt”, this paper develops a general approach for investigating and modeling active perception solutions under pressure. By simulating treasure hunt problems in virtual worlds, our approach learns generalizable strategies from high performers that, when applied to robots, allow them to modulate between optimal and heuristic solutions on the basis of external pressures and probabilistic models, if and when available. The result is a suite of active perception algorithms for camera-equipped robots that outperform treasure-hunt solutions obtained via cell decomposition, information roadmap, and information potential algorithms, in both high-fidelity numerical simulations and physical experiments. The effectiveness of the new active perception strategies is demonstrated under a broad range of unanticipated conditions that cause existing algorithms to fail to complete the search for treasures, such as unmodelled time constraints, resource constraints, and adverse weather (fog).

Problem definition: We consider a multiportfolio optimization problem in which nonlinear market impact costs result in a strong dependency of one account's performance on the trading activities of the other accounts. Methodology/results: We develop a novel target-oriented model that jointly optimizes the rebalancing trades and the split of market impact costs. The key advantages of our proposed model include the consideration of clients' targets on investment returns and the incorporation of distributional uncertainty. The former helps fund managers to circumvent the difficulty in identifying clients' utility functions or risk parameters, whereas the latter addresses a practical challenge that the probability distribution of risky asset returns cannot be fully observed. Specifically, to evaluate the quality of multiple portfolios' investment payoffs in achieving targets, we propose a new class of performance measures, called fairness-aware multiparticipant satisficing (FMS) criteria. These criteria can be extended to encompass distributional uncertainty and have the salient feature of addressing the fairness issue with the collective satisficing level as determined by the least satisfied participant. We find that, structurally, the FMS criteria have a dual connection with a set of risk measures. For multiportfolio optimization, we consider the FMS criterion with conditional value-at-risk being the underlying risk measure to further account for the magnitude of shortfalls against targets. The resulting problem, although nonconvex, can be solved efficiently by solving an equivalent converging sequence of tractable subproblems. Managerial implications: For the multiportfolio optimization problem, the numerical study shows that our approach outperforms utility-based models in achieving targets and in out-of-sample performance. More generally, the proposed FMS criteria provide a new decision framework for operational problems in which the decision makers are target-oriented rather than being utility maximizers and issues of fairness and ambiguity should be considered. Funding: This work was supported by the Hong Kong Research Grants Council [Grants 14210821, 16204521], Leading Talent Program of Guangdong Province [Grant 2016LJ06D703], and the National Natural Science Foundation of China [Grants 71971187, 72171156, 72231002, 72331009]. Supplemental Material: The online appendix is available at https://doi.org/10.1287/msom.2021.0363. [ABSTRACT FROM AUTHOR]

Health institutions recommend that young infants be exclusively breastfed on demand, and it is widely held that parents who can breastfeed have an obligation to do so. This has been challenged in recent philosophical work, especially by Fiona Woollard. Woollard's work critically engages with two distinct views of parental obligation that might ground such an obligation—based on maximal benefit and avoidance of significant harm—to reject an obligation to breastfeed. While agreeing with Woollard's substantive conclusion, this paper (drawing on philosophical discussion of the 'right to rear') argues that there are several more moderate views of parental obligation which might also be thought to ground parental obligation. We first show that an obligation to breastfeed might result not from a general obligation to maximally benefit one's child, but from what we call 'choice-specific' obligations to maximise benefit within particular activities. We then develop this idea through two views of parental obligation—the Dual Interest view, and the Best Custodian view—to ground an obligation to exclusively breastfeed on demand, before showing how both these more moderate views fail. Finally, we argue that not only is there no general obligation to breastfeed children, but that it is often morally right not to do so. Since much advice from health institutions on this issue implies that exclusive breastfeeding on demand is the best option for all families, our argument drives the feeding debate forward by showing that this advice often misrepresents parents' moral obligations in potentially harmful ways. [ABSTRACT FROM AUTHOR]

Problem solvers often need to choose between adapting a current solution and exchanging it for a new one. However, previous studies have not considered how such decisions might depend on structural and surface features of the task. Therefore, the present study investigated the interplay between the costs of the two solutions (a structural feature) and the format in which this information is presented (a surface feature). In a computer-based modular plant scenario, participants chose between modifying process parameters (Adapt) and reconfiguring the module setup (Exchange). The solution costs were presented either as graphs depicting parameter relations, separate numbers for each parameter, or integrated numbers for each solution. It was hypothesised that graphs induce satisficing (i.e., basing decisions only on Adapt), whereas the numeric formats foster a comparison of the solutions (i.e., basing decisions on the Adapt/Exchange ratio). The hypothesised effects were restricted to situations with medium Adapt costs. A second experiment replicated these findings while adjusting the scale of the numeric formats. In conclusion, Adapt/Exchange decisions are shaped by an interaction of structural and surface features of the task. These findings contribute to a more detailed understanding of the influences on decision strategies in complex scenarios that require a balance between stability and flexibility. [ABSTRACT FROM AUTHOR]

• Expected utility theory is not appropriate for understanding the behavior of low-income farmers. • Lexicographic ordering has the advantages of procedural rationality and the behavioral focus on thresholds. • Lexicographic ordering is readily adaptable to the narrative that low income farmers put safety first. • Focusing on safety does not imply avoidance of variance-increasing techniques. As Richard Day explained, expected utility theory suffers from procedural irrationality. This and other problems are illustrated here in the context of decision-making among low-income farmers. Farmers in developing countries are commonly thought to underinvest in modern techniques because their low incomes make them especially risk averse. In addition to the procedural leap of faith, highly restrictive assumptions are needed to apply expected utility theory to the problem. Nor does expected utility theory, as usually prescribed, fit the narrative of loss aversion. The reader is introduced to a procedurally rational substitute called lexicographic safety first. The model is illustrated for the case of rice fertilization in the Philippines, and policy implications are drawn. To illustrate the potential appeal of lexicographic ordering for other applications involving thresholds, a lexicographic model of rational addiction is also provided. [ABSTRACT FROM AUTHOR]

This article presents Herbert A. Simon's critique of the two basic assumptions of the neoclassical notion of agent: perfect rationality and self-interest. It shows how Simon criticized both assumptions by recognizing that the cognitive capacities of agents are limited, showing that there are specific problems that do not have optimal solutions and that there are other motivations irreducible to self-interest, such as loyalty and group identification, which are fundamental for understanding the behavior of organizations. It is shown how Simon pointed towards a notion of rationality that is historically bounded by the interaction of the agent with its environment, which presents a complex and dynamic vision of human behavior. However, the article also shows the difficulties Simon had in achieving the full realization of this project by assuming an assumption of individualistic cognition that prevented him from giving a more substantive role to the environment in structuring agents' behaviors. It ends by showing how the notion of habit can give a more substantive role to the environment in order to develop a historically bounded conception of rationality. [ABSTRACT FROM AUTHOR]

Several studies suggest that 'don't know' (DK) responses to risk perception items may represent meaningful expressions of uncertainty about disease risk. However, researchers are often discouraged from including a DK response option in survey items due to concerns about respondents overusing it to minimize cognitive effort—a phenomenon often referred to as satisficing. Our objective was to investigate whether patterns of DK responses to risk perception survey items were consistent with satisficing behavior. We conducted a secondary analysis of survey data from 814 parents and guardians (hereafter caregivers) of children with asthma. Caregivers answered 18 items assessing their perceived risk of their child experiencing two types of poor asthma outcomes: asthma exacerbation, and low asthma control. We examined differences in the frequency and distribution of DK responses across all 18 items and by type of risk perception item (i.e. 2 vs. 5 response options, absolute vs. comparative risk). We found that 32% (n = 548) of respondents marked DK at least once. Of the 266 caregivers who provided any DK response, most did so for only 1 or 2 items (51.9%, n = 138), and only 6% (n = 15) answered DK to more than half of the items. Using random coefficient Poisson models, we found more DK responding for dichotomous absolute (30.1%) than ordinal absolute items (5.3%), b = 1.72, p<.001. We also found fewer DK responses to the ordinal absolute items than the comparative items (8.2%), b=-0.49, p<.001. Using Chi-square tests, we found that inattentive responding was not associated with responding DK. Our findings suggest that satisficing is unlikely to completely explain DK responding to perceived risk survey items. Researchers who exclude DK response options from risk perception survey items may obtain an incomplete understanding of their study sample's beliefs about risk. [ABSTRACT FROM AUTHOR]

We design a set of satisficing heuristic algorithms that mimic the online information retrieval behavior of rational decision makers (DMs) as reflected in their click through rates (CTRs). We illustrate how basic heuristic algorithms formalizing binary decision trees composed by 21 nodes and requiring DMs to observe one satisficing alternative lack the structural capacity to characterize the retrieval process. The algorithm requiring DMs to observe two satisficing alternatives –formalizing binary decision trees composed by 111 nodes – provides a sufficient approximation to their CTRs. Adding a third alternative – accounting for 351 nodes – delivers an almost identical set of CTRs to those displayed by DMs. The mimicking quality of the heuristic algorithms prevails as alternatives are added up to include the ten ranked within the first page of search results, incorporating 2,047 nodes to formalize the corresponding retrieval process. The set of algorithms bridges the gap between purely rational decision theory and heuristic behavior, illustrating how the CTRs observed can be generated by rational DMs performing a sequential search process while aiming to observe two or three satisficing alternatives. The decision-tree algorithmic structures presented are sufficiently malleable to introduce any potential modification to the beliefs and preferences of DMs and study its consequences in terms of CTRs.

The previous literature has provided mixed findings regarding whether consumers appreciate or are opposed to algorithms. The primary goal of this paper is to address these inconsistencies by identifying the maximizing tendency as a critical moderating variable. In Study 1, it was found that maximizers, individuals who strive for the best possible outcomes, exhibit greater reactance toward algorithm-recommended choices than satisficers, those who are satisfied with a good-enough option. This increased reactance also resulted in decreased algorithm adoption intention. Study 2 replicated and extended the findings from Study 1 by identifying the moderating role of choice goals. Maximizers are more likely to experience reactance to algorithm-recommended options when the act of choosing itself is intrinsically motivating and meaningful (i.e., autotelic choices) compared to when the decision is merely a means to an end (i.e., instrumental choices). The results of this research contribute to a nuanced understanding of how consumers with different decision-making styles navigate the landscape of choice in the digital age. Furthermore, it offers practical insights for firms that utilize algorithmic recommendations in their businesses. [ABSTRACT FROM AUTHOR]

Scholars developing the concept of post-normal science have focused on high stakes and uncertainty to illustrate scientific inquiry and decision-making under post-normal conditions. While uncertainty and decision stakes are often challenges in any decision-making process, we argue that they are not the key factors that warrant the use of a post-normal approach, in which facts are ambiguous, values are in dispute, and stakes are high. In this paper, we center the role of time in the definition of post-normal science and offer a model of decision-making that incorporates uncertainty and high stakes within an overarching context of urgency. We then present three cases of decision-making with varying time horizons to illustrate the significance of time: The period leading up to the 2022 Russian invasion of Ukraine, the U.S. development of the atomic bomb during the Manhattan Project, and U.S. space exploration in the 1960s, culminating in the Apollo 11 Moon landing. Elaborating on the role of time in post-normal science is crucial to public administration because our field routinely involves decision making amidst ambiguous facts, disputed values, high stakes, and urgency. As the three illustrative cases further show, administrators on the ground during the lead-up to the Russian invasion of Ukraine, the Manhattan Project, and space exploration also included extended peer communities. [ABSTRACT FROM AUTHOR]

This study aims to assess student motivation to provide valid responses to the PISA student questionnaire. This was done by modeling response times using a three-component finite mixture model, comprising two satisficing response styles (rapid and idle) and one optimizing response style. Each participant's motivation was operationalized as their probability of providing an optimizing response to questionnaire items. Overall, the model offered a good fit to the data. Results indicate that most responders were motivated to optimize, with a slight decline toward the end. Further, results showed a positive effect of questionnaire-taking motivation on PISA performance, suggesting a positive relationship to test-taking motivation. In conclusion, response times can be valuable indicators for assessing survey response quality and may serve as a proxy for test-taking motivation. [ABSTRACT FROM AUTHOR]

Intuitively, high online review ratings should benefit sales. However, the previous findings show mixed results. The effect of online review ratings on purchases might vary by many factors. We utilize the bounded rationality theory to predict that consumers might seek to satisfice rather than maximize when they evaluate online review ratings to make purchase decisions. The effect of online review ratings on purchase decisions is likely to be concave if bounded rationality prevails in decision-making. If consumers seek a 'good-enough' level of online review ratings rather than the optimal rating, the marginal merit is smaller for higher ratings that are more than satisfactory. Findings from more than ten million consumer choices on Expedia.com indicate that the marginal effect of online review ratings on consumer decisions varies and the effect is concave. [ABSTRACT FROM AUTHOR]

We examined the extent to which intentionally underperforming a goal-directed reaching task impacts how memories of recent performance contribute to sensorimotor adaptation. Healthy human subjects performed computerized cognition testing and an assessment of sensorimotor adaptation, wherein they grasped the handle of a horizontal planar robot while making goal-directed out-and-back reaching movements. The robot exerted forces that resisted hand motion with a spring-like load that changed unpredictably between movements. The robotic test assessed how implicit and explicit memories of sensorimotor performance contribute to the compensation for the unpredictable changes in the hand-held load. After each movement, subjects were to recall and report how far the hand moved on the previous trial (peak extent of the out-and-back movement). Subjects performed the tests under two counter-balanced conditions: one where they performed with their best effort, and one where they intentionally sabotaged (i.e., suppressed) kinematic performance. Results from the computerized cognition tests confirmed that subjects understood and complied with task instructions. When suppressing performance during the robotic assessment, subjects demonstrated marked changes in reach precision, time to capture the target, and reaction time. We fit a set of limited memory models to the data to identify how subjects used implicit and explicit memories of recent performance to compensate for the changing loads. In both sessions, subjects used implicit, but not explicit, memories from the most recent trial to adapt reaches to unpredictable spring-like loads. Subjects did not "give up" on large errors, nor did they discount small errors deemed "good enough". Although subjects clearly suppressed kinematic performance (response timing, movement variability, and self-reporting of reach error), the relative contributions of sensorimotor memories to trial-by-trial variations in task performance did not differ significantly between the two testing conditions. We conclude that intentional performance suppression had minimal impact on how implicit sensorimotor memories contribute to adaptation of unpredictable mechanical loads applied to the hand. [ABSTRACT FROM AUTHOR]

Satisficing response behavior can be a threat to the quality of survey responses. Past research has provided broad empirical evidence on the existence of satisficing and its consequences on data quality, however, relatively little is known about the extent of satisficing over the course of a panel study and its impact on response quality in later waves. Drawing on panel conditioning research, we use question design experiments to investigate whether learning effects across waves of a panel study cause changes in the extent of satisficing and if so, whether general survey experience (process learning) or familiarity with specific question content (content learning) accounts for those changes. We use data from a longitudinal survey experiment comprising six panel waves administered within a German non-probability online access panel. To investigate the underlying mechanism of possible learning effects, the experimental study randomly assigned respondents to different frequencies of receiving identical question content over the six panel waves. Our results show the existence of satisficing in every panel wave, which is in its magnitude similar to the extent of satisficing in the probability-based GESIS Panel that we use as a benchmark study. However, we did not find changes in the extent of satisficing across panel waves, nor did we find moderation effects of the interval between the waves, respondents’ cognitive ability, or motivation. Additional validity analyses showed that satisficing does not only affect the distribution of individual estimates by 15 percent or more but also can have an effect on associations between variables.

Copyright of Journal of International Business Studies is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Computational models of managerial search often build on backward-looking search based on hill-climbing algorithms. Regardless of its prevalence, there is some evidence that this family of algorithms does not universally represent managers' search behavior. Against this background, the paper proposes an alternative algorithm that captures key elements of Simon's concept of satisficing which received considerable support in behavioral experiments. The paper contrasts the satisficing-based algorithm to two variants of hill-climbing search in an agent-based model of a simple decision-making organization. The model builds on the framework of NK fitness landscapes which allows controlling for the complexity of the decision problem to be solved. The results suggest that the model's behavior may remarkably differ depending on whether satisficing or hill-climbing serves as an algorithmic representation for decision-makers' search. Moreover, with the satisficing algorithm, results indicate oscillating aspiration levels, even to the negative, and intense—and potentially destabilizing—search activities when intra-organizational complexity increases. Findings may shed some new light on prior computational models of decision-making in organizations and point to avenues for future research. [ABSTRACT FROM AUTHOR]

Recent years have seen a growing number of studies investigating the accuracy of nonprobability online panels; however, response quality in nonprobability online panels has not yet received much attention. To fill this gap, we investigate response quality in a comprehensive study of seven nonprobability online panels and three probability-based online panels with identical fieldwork periods and questionnaires in Germany. Three response quality indicators typically associated with survey satisficing are assessed: straight-lining in grid questions, item nonresponse, and midpoint selection in visual design experiments. Our results show that there is significantly more straight-lining in the nonprobability online panels than in the probability-based online panels. However, contrary to our expectations, there is no generalizable difference between nonprobability online panels and probability-based online panels with respect to item nonresponse. Finally, neither respondents in nonprobability online panels nor respondents in probability-based online panels are significantly affected by the visual design of the midpoint of the answer scale. [ABSTRACT FROM AUTHOR]

Against the maximizing conception of practical rationality, Michael Slote has argued that rationality does not always require choosing what is most rational. Instead, it can sometimes be rational to do something that is less-than-fully rational. In this paper, I will argue that maximizers have a ready response to Slote's position. Roy Sorensen has argued that 'rational' is an absolute term, suggesting that it is not possible to be rational without being completely rational. Sorensen's view is confirmed by the fact that, by the lights of contemporary linguistics, 'rational' is an absolute gradable adjective. Because 'rational' is an absolute gradable adjective, being rational requires being at the top of the scale of rationality, making anyone who is not fully rational positively irrational. Contra Slote, the only way to be rational enough is to be maximally rational. [ABSTRACT FROM AUTHOR]

Problem solvers often need to choose between adapting a current solution and exchanging it for a new one. However, previous studies have not considered how such decisions might depend on structural and surface features of the task. Therefore, the present study investigated the interplay between the costs of the two solutions (a structural feature) and the format in which this information is presented (a surface feature). In a computer-based modular plant scenario, participants chose between modifying process parameters (Adapt) and reconfiguring the module setup (Exchange). The solution costs were presented either as graphs depicting parameter relations, separate numbers for each parameter, or integrated numbers for each solution. It was hypothesised that graphs induce satisficing (i.e., basing decisions only on Adapt), whereas the numeric formats foster a comparison of the solutions (i.e., basing decisions on the Adapt/Exchange ratio). The hypothesised effects were restricted to situations with medium Adapt costs. A second experiment replicated these findings while adjusting the scale of the numeric formats. In conclusion, Adapt/Exchange decisions are shaped by an interaction of structural and surface features of the task. These findings contribute to a more detailed understanding of the influences on decision strategies in complex scenarios that require a balance between stability and flexibility.

Decision making (DM) generally assumes that the person is performing a choice between a multitude of alternatives under uncertainty and possible risk. According to the concept of dynamic regulative systems (Kornilova, 2016), preferred or most relied on DM strategies are linked in an integrative way with a variety of personality traits that can be at the top of the hierarchy. These include risk readiness, rationality, and Dark Triad traits as reflective of a generally unstable personality core. Decision-Making Tendency Inventory (DMTI; Misuraca et al., 2015) defined DM characteristics via maximization, satisficing and minimization. However, the relationships between DM characteristics captured by DMTI and the listed personality traits have not been explored before. The goal of the current study was establishing latent personality profiles in a person-centered approach that integrates DM “tendencies” and the listed personality traits by identifying relatively homogenous subgroups of individuals with similar profiles. Methods. 625 individuals in the age from 17 to 39 years (М = 20,17, SD = 3,02; 84% females) participated in the study. We used DMTI, Dirty Dozen, and LFR questionnaires to measure DM tendencies, Dark Triad traits, and risk readiness/rationality, respectively. Latent profile analysis was performed in VarSelLCM for R. Results. The results indicated the presence of three latent profiles in the data after adjustments for age and sex. Risk readiness and Dark Triad traits were positively related with maximizing and satisficing, forming one latent class. In another class lower rationality, on the other hand, was linked with minimization. In the third class higher rationality accompanied lower Dark Triad traits. Conclusions. The results provide evidence in favor of the general hypothesis that latent profiles of personality traits are associated with distinct preferences for specific DM tendencies. Higher levels of maximizing, satisficing, and minimizing were not related to subclinical psychopathy or Machiavellianism. Higher narcissism and risk readiness, generally unrelated, are nonetheless characteristic of the latent class that prefers maximizing and satisficing. Preference for minimization of effort during DM was associated with lower rationality. Latent class or latent profile analysis is a powerful technique that sheds new light on the relationships between personality and DM, beyond the contributions of variable-centered approaches such as correlational analysis.

Climate change urgency requires a fast transition to a low carbon society which implies broad-scale changes at all levels, hence the need of an energy transition based on enhancing energy efficiency and renewable energy. Energy efficiency is pivotal to combat climate change, it is the most affordable and readily accessible resource, and the most profitable path to sustainability. Manufacturing companies are increasingly adopting energy efficiency practices (EEP) as they become more knowledgeable about the central role energy efficiency plays in their companies’ competitiveness and the planet’s sustainability. However, the severity of climate change requires the adoption of “optimal” EEP rather than “fairly good” ones. Companies’ satisficing behavior occurs when they do not operate as profit-maximisers, but as satisfactory solutions-seekers. This study explores avenues to address companies’ satisficing behavior regarding EEP. Our research model was empirically tested through survey data collected from 193 manufacturing companies in Morocco. Results show that satisficing negatively affects EEP. Financial slack and governments’ incentives have a positive direct effect on EEP without attenuating the negative relationship between satisfying and EEP. Mimetic pressure attenuates the negative relationship between satisfying and EEP. Based on our findings, policy implications are discussed.

This paper investigates how maximizing or satisficing decision styles and cultural orientation influence individuals' entrepreneurial intentions. With a growing interest in social entrepreneurship, it also measures if these factors encourage individuals to start ventures with a social mission. Two studies are conducted to compare students' entrepreneurial intentions in the U.S. and in Slovenia. By identifying that maximizing decision styles are associated with an individualistic cultural orientation in both the U.S. and Slovenia, the current study indicates that the maximizing -- individualism connection spans national and cultural boundaries. In the U.S. sample, individualism mediated the relationship between decision styles and entrepreneurial intentions, suggesting that in individualistic cultures, such as the U.S., those who maximize their decision efforts and apply a more individualistic cultural perspective are especially inclined to pursue entrepreneurial opportunities. Similarly, individualism mediated the relationship between maximizing and social entrepreneurial intentions in the U.S. sample; suggesting that maximizers who are less individualistic may be more likely to start social enterprises over traditional ventures. Among the Slovenian sample, there was a marginally significant relationship between maximizing and entrepreneurial intentions and no relationship with social entrepreneurial intentions. These cross-cultural differences are discussed in relation to the economic and social conditions in each country. [ABSTRACT FROM AUTHOR]

The previous literature has provided mixed findings regarding whether consumers appreciate or are opposed to algorithms. The primary goal of this paper is to address these inconsistencies by identifying the maximizing tendency as a critical moderating variable. In Study 1, it was found that maximizers, individuals who strive for the best possible outcomes, exhibit greater reactance toward algorithm-recommended choices than satisficers, those who are satisfied with a good-enough option. This increased reactance also resulted in decreased algorithm adoption intention. Study 2 replicated and extended the findings from Study 1 by identifying the moderating role of choice goals. Maximizers are more likely to experience reactance to algorithm-recommended options when the act of choosing itself is intrinsically motivating and meaningful (i.e., autotelic choices) compared to when the decision is merely a means to an end (i.e., instrumental choices). The results of this research contribute to a nuanced understanding of how consumers with different decision-making styles navigate the landscape of choice in the digital age. Furthermore, it offers practical insights for firms that utilize algorithmic recommendations in their businesses.

The present study aims to understand rural-urban differences in India as determined by market regimes, as well as by cultural and prosperity factors. The study focuses on people's maximizing as opposed to satisficing decision preferences. Maximizing stands for people's preference to continuously strive for better options, whereas satisficing means choosing a ‘good enough’ option. It was predicted that corporate employees in an urban metropolitan region would maximize more than the rural farmers due to socio-cultural and economic factors being more market-conducive in the urban region. Individualism-collectivism, achievement motivation, neoliberalism, as well as various classical socioeconomic indicators were taken into account as cultural and economic factors. The study was conducted utilizing field surveys in two Hindi-speaking rural and urban regions in Northern India by using established scales translated to Hindi. Middle-income farmers were recruited in the rural region, while corporate employees were recruited in the urban region. Overall, data were collected for 417 participants in both regions (rural, n = 195/urban, n = 222). Results show that urban participants maximize significantly more than the rural participants. This difference was fully mediated by stronger neoliberal beliefs in the urban region. Higher maximizing tendencies in the metropolitan region can be attributed to more competitive neoliberal–capitalist–market orientation rooted in urban rather than rural India. The findings contribute to the understanding of ecological differences in terms of culture and economy and their effects on people's decision making, especially in low and middle-income countries.

This paper investigates how maximizing or satisficing decision styles and cultural orientation influence individuals’ entrepreneurial intentions. With a growing interest in social entrepreneurship, it also measures if these factors encourage individuals to start ventures with a social mission. Two studies are conducted to compare students’ entrepreneurial intentions in the U.S. and in Slovenia. By identifying that maximizing decision styles are associated with an individualistic cultural orientation in both the U.S. and Slovenia, the current study indicates that the maximizing – individualism connection spans national and cultural boundaries. In the U.S. sample, individualism mediated the relationship between decision styles and entrepreneurial intentions, suggesting that in individualistic cultures, such as the U.S., those who maximize their decision efforts and apply a more individualistic cultural perspective are especially inclined to pursue entrepreneurial opportunities. Similarly, individualism mediated the relationship between maximizing and social entrepreneurial intentions in the U.S. sample; suggesting that maximizers who are less individualistic may be more likely to start social enterprises over traditional ventures. Among the Slovenian sample, there was a marginally significant relationship between maximizing and entrepreneurial intentions and no relationship with social entrepreneurial intentions. These cross-cultural differences are discussed in relation to the economic and social conditions in each country.

This paper examines the frequency of midpoint responses in agree/disagree scales in a survey measuring attitudes toward science and scientific policy, a low-salience and difficult topic. It also examines the contribution of individual differences to explain the tendency to select this option. It is assumed that the use of the midpoint "Neither agree nor disagree" (NA/ND) in Agree/Disagree (A/D) scales is to some extent an indication of satisficing. It is also assumed that there are individual differences in respondents' tendency to select the NA/ND response. Using a Generalized Linear Mixed Model we include Krosnick's regulators of satisficing, socio-demographics and individual differences as predictors. We find that the contribution of the regulators of satisficing identified by Krosnick is small. In turn, factors associated with individual differences explain a great amount of variance on the number of NA/ND responses. We conclude that the presence of this option in a survey of a low-salience topic increases satisficing as strategy of the respondents to deal with the cognitive burden of both the A/D scale and the difficulty of the topic. Furthermore, the number of NA/ND responses may be understood as an indicator of individual differences in the propensity of respondents to satisficing when answering a survey on a low-salience or difficult topic. [ABSTRACT FROM AUTHOR]

Descendants of indigenous people in the United States (Native Americans) are underrepresented in happiness studies. The social-cognitive mechanisms involved in happiness are also poorly understood. Here we test a social-cognitive model for theorizing the happiness of Native Americans. Self-identified Native Americans (120 women, 59 men, aged 18–79 years) in the Phoenix, Arizona metropolitan area answered a survey which measured interdependent and independent self-construals, decision-making style (satisficing and maximizing), and subjective happiness. Relationships among these variables were examined using path analysis. For the participants' happiness, independent self-construal was relatively less important than interdependent self-construal, as social harmony and interdependence with others tend to be salient traditional Native American cultural values. However, in agreement with previous studies with Euro-American samples, subjective happiness was positively correlated with satisficing, and negatively correlated with maximizing, suggesting societal factors such as the availability of options and choices in the U.S. as possible influences. These findings contribute to the literature by revealing the basis of happiness in social-cognitive processes, and have important implications for understanding the happiness of an under-researched population. [ABSTRACT FROM AUTHOR]

Much of the recent literature on bandit learning focuses on algorithms that aim to converge on an optimal action. One shortcoming is that this orientation does not account for time sensitivity, which can play a crucial role when learning an optimal action requires much more information than near-optimal ones. Indeed, popular approaches, such as upper-confidence-bound methods and Thompson sampling, can fare poorly in such situations. We consider instead learning a satisficing action, which is near-optimal while requiring less information, and propose satisficing Thompson sampling, an algorithm that serves this purpose. We establish a general bound on expected discounted regret and study the application of satisficing Thompson sampling to linear and infinite-armed bandits, demonstrating arbitrarily large benefits over Thompson sampling. We also discuss the relation between the notion of satisficing and the theory of rate distortion, which offers guidance on the selection of satisficing actions. [ABSTRACT FROM AUTHOR]

Why would decision makers (DMs) adopt heuristics, priors, or in short “habits” that prevent them from optimally using pertinent information—even when such information is freely-available? One answer, Herbert Simon’s “procedural rationality” regards the question invalid: DMs do not, and in fact cannot, process information in an optimal fashion. For Simon, habits are the primitives, where humans are ready to replace them only when they no longer sustain a pregiven “satisficing” goal. An alternative answer, Daniel Kahneman’s “mental economy” regards the question valid: DMs make decisions based on optimization. Kahneman understands optimization not differently from the standard economist’s “bounded rationality.” This might surprise some researchers given that the early Kahneman, along with Tversky, have uncovered biases that appear to suggest that choices depart greatly from rational choices. However, once we consider cognitive cost as part of the constraints, such biases turn out to be occasional failures of habits that are otherwise optimal on average. They are optimal as they save us the cognitive cost of case-by-case deliberation. While Kahneman’s bounded rationality situates him in the neoclassical economics camp, Simon’s procedural rationality echoes Bourdieu’s “habitus” camp. To abridge the fault line of the two camps, this paper proposes a “two problem areas hypothesis.” Along the neoclassical camp, habits satisfy wellbeing, what this paper calls “substantive satisfaction.” Along the Bourdieu camp, habits satisfy belonging, love, and bonding with one’s environment, what this paper calls “transcendental satisfaction.” [ABSTRACT FROM AUTHOR]

To reduce strategic misreporting on sensitive topics, survey researchers increasingly use list experiments rather than direct questions. However, the complexity of list experiments may increase nonstrategic misreporting. We provide the first empirical assessment of this trade-off between strategic and nonstrategic misreporting. We field list experiments on election turnout in two different countries, collecting measures of respondents' true turnout. We detail and apply a partition validation method which uses true scores to distinguish true and false positives and negatives for list experiments, thus allowing detection of nonstrategic reporting errors. For both list experiments, partition validation reveals nonstrategic misreporting that is: undetected by standard diagnostics or validation; greater than assumed in extant simulation studies; and severe enough that direct turnout questions subject to strategic misreporting exhibit lower overall reporting error. We discuss how our results can inform the choice between list experiment and direct question for other topics and survey contexts. [ABSTRACT FROM AUTHOR]

In recent years, conjoint experiments have been in vogue across the social sciences. A reason for the conjoint experiments' popularity is that they allow researchers to estimate the causal effects of many components of stimuli simultaneously. However, for conjoint experiments to produce valid results, respondents need to be able to process and understand the wide range of dimensions presented to them in the experiment. If the information processing is too demanding or too complicated, respondents are likely to turn to satisficing strategies, leading to poorer data quality and subsequently decreasing the researcher's ability to make accurate causal inferences. One factor that may lead to the adoption of satisficing strategies is the presentation format used for the conjoint experiment (i.e., presenting the information within a text paragraph or a table). In the present paper, a direct replication of the single conjoint presentation format experiment described in Shamon, Dülmer, and Giza's (2019) paper in Sociological Methods & Research is presented, and extending their work to paired conjoint experiment. The results of the direct replication showed that respondents evaluated the questionnaire more favorably when reading the table format but were, on the other hand, less likely to participate in subsequent panel waves. Albeit the number of break-offs, refusals, and non-responses did not differ between the two formats, respondents who saw the table format evaluated the scenarios with more consistency and less dimension reduction, thus favoring the table presentation format. For paired conjoint experiments, the presentation format did not affect survey evaluations or panel participation but the table format heavily outperformed the text format on every data quality measure except for dimension reduction. Conceptually, albeit not directly replicating the findings in Shamon, Dülmer, and Giza (2019), the present manuscript concludes that the table format appears preferable over the text format for conjoint experimental designs. [ABSTRACT FROM AUTHOR]

In this paper, we assume that the natural rate of interest is fundamentally uncertain. Based on a small‐scale macroeconomic model, info‐gap theory is used to rank different monetary policy strategies in terms of their robustness against this uncertainty. Applied to the euro area, we find that an inert or patient monetary strategy is more robust to natural rate uncertainty than a strategy that follows an estimated Taylor rule. An actively responsive monetary strategy is least robust. Our analysis presents a methodology that is applicable in a wide range of policy analyses under deep uncertainty. [ABSTRACT FROM AUTHOR]

A decision maker (DM) may not perfectly maximize her preference over the feasible set. She may feel it is good enough to maximize her preference over a sufficiently large consideration set; or just require that her choice is sufficiently well-ranked (e.g., in the top quintile of options); or even endogenously determine a threshold for what is good enough, based on an initial sampling of the options. Heuristics such as these are all encompassed by a common theory of order-k rationality, which relaxes perfect optimization by only requiring choices from a set S to fall within the set's top k(S) elements according to the DM's preference ordering. Heuristics aside, this departure from rationality offers a natural way, in the classic 'as if' tradition, to gradually accommodate more choice patterns as k increases. We characterize the empirical content of order-k rationality (and related theories), and provide a tractable testing method which is comparable to the method of checking SARP. [ABSTRACT FROM AUTHOR]

The presence of an interviewer (face-to-face or via telephone) is hypothesized to motivate respondents to generate an accurate answer and reduce task difficulty, but also to reduce the privacy of the reporting situation. To study this, we used respondents from an existing face-to-face probability sample of the general population who were randomly assigned to face-to-face, telephone and web modes of data collection. The prevalence of indicators of satisficing (e.g., non-differentiation, acquiescence, middle category choices and primacy and recency effects) and socially desirable responding were studied across modes. Results show differences between interviewer modes and web in levels of satisficing (non-differentiation, acquiescence and middle category choices) and in socially desirable responding. There were also unexpected findings of (1) different ways of satisficing by mode and (2) of a telephone mode primacy/positivity effects.