Real Decision Research Articles

Simpson�s Paradox: Conceptual Foundational Implications in Real-Life Decision-Making in Quantitative Investment and Trading

Pankaj Mani writes that a phenomenon in probability and statistics in which a trend appears in several groups of data but disappears or reverses when the groups are combined raises foundational issues in concluding the significance of statistical relationships among different variables reliably in real-world decision-making for trading, investing, risk management.

Counterfactual curiosity in real decisions: The roles of outcome valence and aging.

Non-instrumental counterfactual curiosity (i.e., the search for information about forgone options that is not useful for improving future outcomes) has especially been observed after outcomes perceived as negative and, consequently, attributed to forms of regret management. In three online experiments (N = 620), we extended the study of counterfactual curiosity about economically incentivized decisions in younger and older adults. Participants played independent rounds of a card-drawing game by choosing one of two decks to turn over the top, covered card, which could increase, decrease, or have no effect on an initial endowment. Following that, they could examine the top card of the other deck to see if and how the outcome could have differed. Experiment 1 featured identical decks, making the choice between them random. In Experiment 2, participants made a deliberate choice between a riskier and a safer deck, each varying in the extremity of potential wins and losses. In Experiment 3, the decks were identical to those in Experiment 2, but access to counterfactual information was contingent upon participants forfeiting part of their endowment. Results showed a relevant portion of both younger and older adults displayed curiosity for non-instrumental counterfactual information, especially when it was free and likely to reveal that the forgone option would have been better than the chosen one. Older adults exhibited a higher level of curiosity than younger counterparts only when choices were deliberate and counterfactual information was free. These findings are discussed in relation to current perspectives on the regret-management function of counterfactual curiosity.

A causal role of the right dorsolateral prefrontal cortex in random exploration

Decision to explore new options with uncertain outcomes or exploit familiar options with known outcomes is a fundamental challenge that the brain faces in almost all real-life decisions. Previous studies have shown that humans use two main explorative strategies to negotiate this explore-exploit tradeoff. Exploring for the sake of information is called directed exploration, and exploration driven by behavioral variability is known as random exploration. While previous neuroimaging studies have shown different neural correlates for these explorative strategies, including right frontopolar cortex (FPC), right dorsolateral prefrontal cortex (DLPFC), and dorsal anterior cingulate cortex (dACC), there is still a lack of causal evidence for most of these brain regions. Here, we focused on the right DLPFC, which was previously supported to be involved in exploration. Using the continuous theta burst stimulation (cTBS) and Horizon task on twenty-five healthy right-handed adult participants, we showed that inhibiting rDLPFC did not change directed exploration but selectively reduced random exploration, by increasing reward sensitivity over the average reward of each option. This suggests a causal role for rDLPFC in random exploration, and further supports dissociable neural implementations for these two explorative strategies.

Assessment on Maritime Students' Awareness, Perceptions and Needs in Career Planning in Tertiary Education

Although seafaring is seen as an attractive profession for prospective students in terms of having the opportunity to see different parts of the world while working and earning more money in less time compared to other professions, the harsh conditions of duties onboard sometimes overshadow this attractiveness, which may lead students to question their choices and seek different career alternatives. This study aims at assessing maritime students' knowledge, perceptions, and needs regarding career awareness and career planning at the tertiary level. The study also seeks to understand students' awareness of career-related activities and the role and responsibilities of the career centre. The research component of the study involves administering a questionnaire to 381 first-year students at a maritime-focused university. The questionnaire comprises twenty questions based on a five-point Likert scale and has been electronically distributed. The data collected has been analysed using parametric methods based on four variables: career anchor, career awareness, career centre awareness, and career planning awareness. The study has revealed that most of the students are aware of their own characteristics and the sacrifices required by their future profession, but they had not yet decided which career path to follow after graduation. The study has also revealed that students are interested in developing their skills through extracurricular activities and consider entrepreneurship as a future career option. The results suggest that career offices in maritime universities should create more opportunities to provide students with adequate information about their future careers and to enable them to make correct and realistic decisions about their career paths. The next study on this topic can focus on how to raise awareness of the functions of career officers and how to develop maritime-oriented career planning courses so that the students can make more realistic and satisfying career choices.

Short term efficacy of biological treatment for moderate-to-severe plaque psoriasis: a systematic review and network meta-analysis.

Psoriasis is a chronic inflammatory disease that is debilitating, particularly in its more severe forms. Multiple systemic therapies are used in moderate-to-severe psoriasis, but the development of biological interventions has revolutionized its management and improved its outcomes. To compare the effectiveness and safety of the different biological interventions approved for use in moderate-to-severe plaque psoriasis. Multiple databases were searched for relevant articles and a prospectively planned network meta-analysis was conducted on randomized controlled trials that assessed biological treatments in moderate-to-severe psoriasis. The search yielded 84 trials that encompassed 39,798 patients. Infliximab 5mg/kg had the highest probability of achieving 75% reduction on PASI scale in comparison to placebo (RR = 18.76, 95% CI [12.31; 28.57], high certainty), while Ixekizumab 80mg and Brodalumab 210mg had the highest probability at achieving PASI90 and PASI100 (37.81, [28.57; 50.03] and 81.04, [26.16; 251.01], respectively, with moderate certainty) On the other hand, Risankizumab 150mg and Ustekinumab 90mg were the only regimens with significantly less withdrawal rates due to adverse events (0.41, [0.18-0.96], and 0.57, [0.35-0.91], respectively with High certainty) compared to placebo. Anti-IL17 and Infliximab were among the most effective in ameliorating the symptoms of psoriasis, however, anti-IL17 were better at achieving full or almost full improvement on the PASI scale. Real life decision-making is not so clear-cut and should remain patient centered, taking into consideration factors such as safety, comorbidities, biologic naivety, dosing preferences and insurance considerations.

A Serious Game for the Digital Transformation of Organizations

To aid human resource management professionals design a configuration of human resource management practices that facilitates the employee behaviour needed for the digital transformation, a serious game was created. The serious game challenges human resource management professionals to combine and design human resource management practices that align to the organizational strategy and optimize employee digital transformation behaviour over multiple simulated years. In this paper, the underlying rationale, design, and outcomes of the first test rounds of the game are presented. Organizational change shaped by the diffusion of technology is labelled the digital transformation (Hanelt et al., 2021). Employees can accelerate or slow down the digital transformation. Hence, organizations are looking to facilitate digital transformation enhancing employee behaviours: adaptive performance and proactive agility behaviour (Collou and Bruinsma, 2022). Aligned human resource management configurations (i.e., combination of human resource management practices such as recruitment, selection, and job design) can shape that employee behaviour (Gratton and Truss, 2003; Delery and Doty, 1996). Designing such a human resource management configuration however is challenging. There are many human resource management practices that need to be designed over multiple years and effects on employee behaviour vary. Serious games are well suited tools to enhance understanding of challenges such as strategic human resource management design. They allow professionals to experiment with choices and gauge the outcomes of their selection without the need to test these decisions in real life. Prior work (Collou and Bruinsma, 2022, 2019) illustrated that a serious game can aid human resource management professionals in their quest to design human resource management configurations that align to the organizational strategy. In the current game an additional challenge was added: shaping digital transformation behaviour. Tested in multiple rounds the game shows great promise for professionals and students to experiment with human resource management configuration design. First evaluations illustrate that responders are positive in terms of their learning experience. Balancing the need to align the human resource management configuration and affecting the employee behaviour simultaneously has proven to be challenging for players of the game. Future steps are focused on this balance and empirically validating the serious game.

A Comparative Study of The Application of NPV And IRR To Real Estate Investment Decision- Making

The China real estate industry is undergoing a fluctuation nowadays. And this paper is going to investigate this industry by researching a leading enterprise, CHINA VANKE CO., LTD. with the assistance of two financial instruments, Net Present Value (NPV) and Internal Rate of Return (IRR). Furthermore, the paper has another purpose that is comparing the properties between NPV and IRR. This paper uses literature research method and case study to analyse the situation of Vanke and list the possible considerations while having the analysis. After a series of research, the author considers NPV as a better indicator compared to IRR. NPV has the advantage of simple marginal determination, however, the related indicator, discount rate cannot be determined easily and accurately in the real estate analysis since it can be affected by many factors. For advantage of IRR, it is simple to calculate the value because it is only decided by the cashflows. On the other hand, IRR cannot clarify the real estate investment decision-making by itself, it must have the assistance of NPV versus discount rate graph. Consequently, the mixed employment would present a clearer and more comprehensive analysis for investors.

Towards accelerating discovery via physics-driven and interactive multi-fidelity Bayesian Optimization

Abstract Both computational and experimental material discovery bring forth the challenge of exploring multidimensional and often non-differentiable parameter spaces, such as phase diagrams of Hamiltonians with multiple interactions, composition spaces of combinatorial libraries, processing spaces, and molecular embedding spaces. Often these systems are expensive or time-consuming to evaluate a single instance, and hence classical approaches based on exhaustive grid or random search are too data intensive. This resulted in strong interest towards active learning methods such as Bayesian optimization (BO) where the adaptive exploration occurs based on human learning (discovery) objective. However, classical BO is based on a predefined optimization target, and policies balancing exploration and exploitation are purely data driven. In practical settings, the domain expert can pose prior knowledge on the system in form of partially known physics laws and often varies exploration policies during the experiment. Here, we propose an interactive workflow building on multi-fidelity BO (MFBO), starting with classical (data-driven) MFBO, then expand to a proposed structured (physics-driven) sMFBO, and finally extending it to allow human in the loop interactive iMFBO workflows for adaptive and domain expert aligned exploration. These approaches are demonstrated over highly non-smooth multi-fidelity simulation data generated from an Ising model, considering spin-spin interaction as parameter space, lattice sizes as fidelity spaces, and the objective as maximizing heat capacity. Detailed analysis and comparison show the impact of physics knowledge injection and real time human decisions for improved exploration with increased alignment to ground truth.

Predicting and Understanding Human Action Decisions: Insights from Large Language Models and Cognitive Instance-Based Learning

Large Language Models (LLMs) excel in tasks from translation to complex reasoning. For AI systems to help effectively, understanding and predicting human behavior and biases is essential. However, it remains an open question whether LLMs can achieve this goal. This paper addresses this gap by leveraging the reasoning and generative capabilities of LLMs to predict human behavior in two sequential decision-making tasks. These tasks involve balancing between exploratory and exploitative actions and handling delayed feedback, which is essential for simulating real-life decision processes. We compare the performance of LLMs with a cognitive instance-based learning (IBL) model, which imitates human experiential decision-making. Our findings indicate that LLMs excel at rapidly incorporating feedback to enhance prediction accuracy. In contrast, the IBL model better accounts for human exploratory behaviors and effectively captures loss aversion bias — the tendency to choose a sub-optimal goal with fewer step-cost penalties rather than exploring to find the optimal choice, even with limited experience. The results highlight the benefits of integrating LLMs with cognitive architectures, suggesting that this synergy could enhance the modeling and understanding of complex human decision-making patterns.

Game Theory Applications In The Airbus-Boeing Dispute

This study examines the intricate trade dispute between Airbus and Boeing which took place from the late 1970s all the way till 2021. By using game theory tools including Nash equilibrium, mixed strategies, Stackelberg competition and credible threats, I can explore the strategic trade decisions, such as tarif s, subsidies and complaints to the WTO, taken by each player and how this af ects the overall competitiveness and the health of the LCA sector. Each of these games use data from the real world in order to ef ectively depict the outcomes that could have arisen and those that actually happened. The key findings were able to illustrate how although some of the theoretical economic ideologies were used, the real life decisions still deviated from the stable outcomes due to external pressures and factors. The results provide us a more intricate understanding of the trade world and the economic environment of the LCA industry

Mapping the landscape: A systematic literature review on automated valuation models and strategic applications in real estate

In the rapidly evolving real estate industry, integrating automated valuation models (AVMs) has become critical for improving property assessment accuracy and transparency. Although there is some research on the subject, no thorough qualitative systematic review has been done in this field. This paper aims to provide an up-to-date and systematic understanding of the strategic applications of AVMs across various real estate subsectors (i.e., real estate development, real estate investment, land administration, and taxation), shedding light on their broad contributions to value enhancement, decision-making, and market insights. The systematic review is based on 97 papers selected out of 652 search results with an application of the PRISMA-based method. The findings highlight the transformative role of AVMs approaches in streamlining valuation processes, enhancing market efficiency, and supporting data-driven decision-making in the real estate industry, along with developing an original conceptual framework. Key areas of future research, including data integration, ethical implications, and the development of hybrid AVMs approaches are identified to advance the field and address emerging challenges. Ultimately, stakeholders can create new avenues for real estate valuation efficiency, accuracy, and transparency by judiciously utilizing AVMs approaches, leading to more educated real estate investment decisions.

Increasing recycling with charitable incentives

Many businesses have moved toward a circular economy, collecting their packaging material from customers to be reintroduced into their remanufacturing processes. For these programs to be successful, individuals must voluntarily, and often effortfully, dispose of their used materials in specific ways. The goal of the present research is to evaluate the effectiveness of charitable incentives in promoting effortful recycling. We explore whether the type of charitable recipient – human or non-human – differently promotes effortful recycling, and examine how people's environmental values may moderate these effects. Five studies (N = 3572) utilizing real disposal decisions and consequential disposal intentions demonstrate that when individuals are informed that by recycling an item a donation will be made to a non-profit organization, effortful recycling increases—an effect that is observed for both environmental and youth recipients (Studies 1–4b). However, an environmental charitable recipient was less motivating for people who had less concern for the environment (Studies 3 and 4b). We find that an environmental charitable recipient increases effortful recycling because of an enhanced perception of making an impact, while a youth charitable recipient increases effortful recycling through greater empathy (Studies 4a and 4b). We conclude that efforts to increase material recovery using charitable incentives can be effective, and should carefully consider the values of their intended audience along with charitable recipient type.

Response Coordination Model for Real Time Decision Making in Coastal Search and Rescue Operation Using Fuzzy Logic Technique

Coastal search and rescue (SAR) operations are complex, involving dynamic and uncertain conditions that demand real-time, effective decision-making. This paper aimed to analyze response coordination for real- time decision-making in coastal SAR operations using the fuzzy logic technique. The main aims of this study were to identify the key parameters and linguistic variables critical for effective decision-making in SAR operations and finally to design a fuzzy logic model tailored to the dynamic and uncertain conditions inherent in coastal SAR operations. The proposed fuzzy logic model demonstrated improved responsiveness and adaptability to changing conditions, offering a more robust framework for decision-making in SAR operations. However, this study contributes to enhancing the efficiency and effectiveness of real time decision making in SAR operations in coastal environments, with broader implications for maritime safety.

What Affects the Value of Our Time? The Case of Buying a Present vs. Buying for Ourselves and the Impact of Decision-Making Styles.

We study how the buying purpose affects the trade-off between time and money. We consider the case of buying something for ourselves versus buying a gift and the decision whether to spend time traveling to a cheaper store to save money. We hypothesized that when purchasing a gift, people make less effort to save money, and therefore will be less willing to spend time traveling to a cheaper store when they buy a gift. In experiments with several scenarios, we fail to find support for this hypothesis. We also explore the impact of telling subjects that the purchase is made abroad. This is hypothesized to increase the valuation of the buyer's time. We also hypothesize that the interaction of being abroad and buying a gift will be negative. The data support both hypotheses. Subjects answered 15 questions about their decision-making style (rational, intuitive, and spontaneous). Subjects with more rational decision-making exhibit lower time value, which is likely to be closer to the real one. Subjects with more rational decision-making also show more strongly that time abroad is more valuable. These results suggest that questions about decision-making style are correlated with decision-making in scenarios of realistic purchase decisions.

Cross-domain additive learning of new knowledge rather than replacement.

In medical clinical scenarios for reasons such as patient privacy, information protection and data migration, when domain adaptation is needed for real scenarios, the source-domain data is often inaccessible and only the pre-trained source model on the source-domain is available. Existing solutions for this type of problem tend to forget the rich task experience previously learned on the source domain after adapting, which means that the model simply overfits the target-domain data when adapting and does not learn robust features that facilitate real task decisions. We address this problem by exploring the particular application of source-free domain adaptation in medical image segmentation and propose a two-stage additive source-free adaptation framework. We generalize the domain-invariant features by constraining the core pathological structure and semantic consistency between different perspectives. And we reduce the segmentation generated by locating and filtering elements that may have errors through Monte-Carlo uncertainty estimation. We conduct comparison experiments with some other methods on a cross-device polyp segmentation and a cross-modal brain tumor segmentation dataset, the results in both the target and source domains verify that the proposed method can effectively solve the domain offset problem and the model retains its dominance on the source domain after learning new knowledge of the target domain.This work provides valuable exploration for achieving additive learning on the target and source domains in the absence of source data and offers new ideas and methods for adaptation research in the field of medical image segmentation.

Navigating barriers to reverse logistics adoption in circular economy: An integrated approach for sustainable development

Achievement of sustainability goals is an epic task for developing economies that still strive to fulfil their basic needs. The availability of limited resources in the developing world vis-à-vis the ever-increasing demand poses further challenges to developing economies willing to transition into circular economies. Reverse logistics (RL) can facilitate this transition towards a circular economy (CE) by maximising resource utilisation and minimising waste, contributing to sustainability goals. This paper contributes to emerging literature by analysing the development and comprehensive potential of reverse logistics as a sustainability tool. It explores the significant barriers to the adoption of reverse logistics towards a circular economy, considering long-term sustainability. In the first phase, thirteen barriers have been identified from the past academic literature. Three barriers with a defuzzification number less than the threshold limit are excluded, and the final ten barriers are then prioritised using the decision-making trial and evaluation laboratory (DEMATEL) method. The findings suggest that a lack of strategic plans for returns is crucial for RL adoption towards a circular economy, followed by a lack of visibility for recycling/reuse. Organisations can increase customer satisfaction, promote environmental sustainability, and gain a competitive edge in the market by creating a strategic plan for reverse logistics. Organisations may lower costs and contribute to a more sustainable and ecologically responsible supply chain by improving visibility across the reverse logistics process. The results serve as a framework for decision-making in RL towards sustainable development. Managers and policymakers can formulate more robust and realistic decisions that align with “maximising profits,” “saving the planet,” “social concerns,” and, most importantly, “consumer concerns” in the circular economy ecosystem. Several implications are derived, leading to increased competitiveness and resilient business strategies. The novelty of this work lies in the identification of barriers to reverse logistics adoption towards a circular economy using an integrated fuzzy Delphi-DEMATEL approach, considering long-term sustainability. This approach is studied for the first time in a developing economy context, proposing social, economic, and environmental effects and actions to be taken by organisations for sustainable development.

Navigating real estate purchase decisions: an interplay of influential factors

Navigating real estate purchase decisions: an interplay of influential factors

Climate storylines as a tool for interdisciplinary dialogue on risk decision-making: Analyzing a severe drought in southeastern South America

Recently, we are witnessing a growing interest in the study of climate narratives and storylines. These are seen as critical tools both for improving shared understandings involving different stakeholders (including scientists from different disciplines) and guiding initiatives for transformative adaptation actions and decision making. This paper approaches the storylines about a severe drought event that took place in southeastern South America (SESA) in 2008/2009 from an interdisciplinary dialogue between climatologists and anthropologists. This approach responds to the need for a more robust understanding of the event and the responses adopted locally, i.e: not restricted to physical aspects but considering socio-economic and political aspects, with the aim of contributing to the development of socially relevant climatic information for realistic climate risk decision making contexts. In particular it intends to contribute to the decision-making processes of government agencies focused on climate communication and public climate services, such as national and weather services and regional agencies. Considering disciplinary differences, we account for the interpretative polyphony regarding this event, i.e.: what each actor/sector is talking about (for what and to whom they are talking about) when referring to "the drought", and analyze climate storylines as an agonistic field of meanings. This implies recognizing the disputes and contradictions among them, how different storylines promote certain lines of argumentation and meanings to the detriment of others, knowledge gaps, the role of social power relations, socio-political order factors and their impact in terms of the necessary transformations towards an environmentally sustainable and socially just horizon.

Activating the sustainable consumer:The role of customer involvement in corporate sustainability

AbstractTackling grand challenges and making sustainable development a reality through sustainable consumption crucially depends upon both companies’ activities as well as individuals’ consumption choices. In opinion polls, many consumers claim to favor sustainable products over conventional ones. However, a large gap remains between their stated purchasing intentions and actual decisions, posing a challenge for companies in predicting product demand and strategically managing their product portfolios. In this study, we develop a conceptual framework to demonstrate how companies can encourage sustainable consumption behavior among their customers by involving them in their corporate sustainability (CS) activities. We introduce psychological ownership as the underlying mechanism explaining how customer involvement in CS activities translates into changes in their consumption choices. We further argue that the link between customer involvement and psychological ownership depends on the type of a company’s CS—that is, whether CS is embedded in or peripheral to the company’s core business. The results from three experiments, including one field experiment conducted in collaboration with a fashion retailer and involving real customer purchase decisions, support our theorizing. The findings reveal the power of customer involvement as a marketing tool in promoting sustainable consumption.

The influence of individual factors on the career preferences and specialty choices of final-year nursing students

BackgroundStatistical evidence shows that nursing students prefer a professional career in hospital settings, leading to a lack of career interest in non-hospital settings such as community and residential aged care facilities. The lack of preference for non-hospital settings has persisted over several decades and presents a need for different approaches that may reveal new information to better understand the individual factors that influence specialty choices and preferences from the students' viewpoints. PurposeThe aims of this study were to (1) explore individual factors that impact the nursing specialty choices of final-year nursing students and (2) explore how these factors influence the final-year nursing students' career decision-making process. MethodA narrative inquiry approach using semi-structured interviews was carried out with purposively sampled nursing students (n = 12) who had undertaken a final-year clinical placement(s). Data was analysed using two main steps. First, the interviews were restoried and then analysed using the three-dimensional framework. Subsequently, thematic analysis was applied to generate themes. ResultsData analysis generated three main themes: demographic factors, social factors, and career goals. Participants' characteristics and interactions with other individuals and systems influenced their nursing specialty preferences and professional career plans. ConclusionNursing students' career interests are influenced by individual factors external to their nursing education, such as their age, gender, and life experiences. These student characteristics and experiences facilitated or inhibited a career in some nursing specialties, with the students gauging their ability to practice in a specialty during their CPs. Nursing education should expose and inform students about the core skills, career opportunities, and how to advance their careers in the different nursing specialties. Most importantly, final-year students may need formal career guidance to encourage nursing students' positive attitudes and career interests in different nursing specialties and make realistic career decisions.