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People have conflicting responses for support from algorithms or humans in decision-making. On the one hand, they fail to benefit from algorithms due to algorithm aversion, as they reject decisions provided by algorithms more frequently than those made by humans. On the other hand, many prefer algorithmic over human advice, an effect of algorithm appreciation. However, currently, we lack a shared understanding of these constructs’ meaning and measurements, resulting in a lack of theoretical integration of empirical findings. Thus, in this research note, we conceptualize algorithm aversion as the preference for humans over algorithms in decision-making and analyze approaches in current research to measure this preference. First, we outline the implications of focusing on a specific understanding of algorithms as computational procedures or as embedded in material or nonmaterial objects. Then, we classify four decision configurations that distinguish individuals’ evaluations of algorithms, human advisors, their own judgments, or combinations of these. Consequently, we develop a classification scheme that provides guidance for future research to develop more specific hypotheses on the direction of preferences (aversion vs. appreciation) and the effect of moderators. [ABSTRACT FROM AUTHOR]

Parcel hub (PH), as one of the logistic system entities, plays a significant role in delivering packages. PH operations are identical to a cross-docking system. Numerous studies were conducted to examine solutions in PH and cross-docking in general. This paper aims to investigate scientific references published within the last fifteen years through a systematic literature review (SLR). The objectives are to determine the critical decisions related to PH problems, classify the applied solution approach, and identify the future challenges regarding the transformation towards intelligent logistics. This study implements an SLR methodology that consists of five stages: planning, searching, screening, analysing, and reporting. This study utilises two publication databases and one reference management system. More than four thousand documents were collected in the searching stage. Then, five assessments are conducted to sort the most relevant papers. One hundred and forty-six articles are included in the further analysis. This study classifies four important decisions associated with PH problems: truck scheduling, internal process planning, facility planning, and technology selection. In addition, this study categorises ten solution approaches employed to find the best decision in the prior research. Moreover, this study explains the future research directions and managerial implications of managing parcel hub systems. [ABSTRACT FROM AUTHOR]

Firms from a variety of industries regularly partner with Formula One racing teams to achieve marketing objectives on an international scale. The sponsored properties offer signals of brand foreignness/localness, country of origin, and the potential for highly visible achievements. Firms enter and exit brand partnerships with some of the world's most famous athletes and iconic teams, yet the partnership decision-making process remains opaque, particularly concerning the impact of geographic origin and team performance among other criteria, including macroeconomic conditions and brand-related factors. This study contributes a quantitative model that analyzes 53 years of data encompassing more than 3,000 sponsorships across six continents. The findings improve understanding of brand partnership continuity/dissolution by explicating a shared nationality effect and a link with sponsored organizational performance that is robust across three distinct eras of Formula One. In doing so, the study contributes to theory by completing the sponsorship performance cycle and distilling partnership limits with regard to brand foreignness. The theory and quantitative analyses are buttressed by interviews with brand decision-makers, excerpts from which also shape the discussion of managerial applications. Implications include efficiencies in partner prospecting that enhance the likelihood of enduring brand relationships in sponsorship-linked international marketing. [ABSTRACT FROM AUTHOR]

Extreme heat is the leading cause of weather-related mortality in the United States, and extreme heat events are projected to continue to increase in geographic extent, frequency, and severity in the United States as climate change progresses. Transportation infrastructure is a significant driver of the urban heat island (UHI) effect and exacerbating extreme heat events. Efforts to mitigate UHI impacts often focus on reflecting incoming solar radiation (i.e., increasing surface albedo) and providing shade (e.g., planting street trees). However, advanced and novel materials (ANM) for pavements that reduce heat storage, and green stormwater infrastructure (GSI) that promotes evaporative cooling, can provide additional heat mitigation pathways. Sidewalks facilitate non-motorized transportation, and are relatively low-risk, low-cost, and have simple structural requirements compared to other transportation infrastructure. Hence, sidewalks and adjacent planting strips can offer a logical test bed for new materials and designs. With the thermal comfort, safety, and efficiency of users in mind, environmentally responsible designs can also minimize energy embedded in construction materials and help maintain natural ecosystem processes. Although ANMs hold significant promise for heat mitigation, they have not yet achieved widespread implementation. This project systematically reviewed the growing literature related to theapplication of ANMs and GSI to reduce UHI effects and implemented a survey of urban planners and public works engineers to assess the current and planned use of these strategies and identify barriers to implementation. This report summarizes the emergent themes from the systematic literature review, survey results and policy recommendations for an anticipated reading audience of urban policy makers, planners, and practitioners. View the NCST Project Webpage

Learning structures that effectively abstract decision policies is key to the flexibility of human intelligence. Previous work has shown that humans use hierarchically structured policies to efficiently navigate complex and dynamic environments. However, the computational processes that support the learning and construction of such policies remain insufficiently understood. To address this question, we tested 1026 human participants, who made over 1 million choices combined, in a decision-making task where they could learn, transfer, and recompose multiple sets of hierarchical policies. We propose a novel algorithmic account for the learning processes underlying observed human behavior. We show that humans rely on compressed policies over states in early learning, which gradually unfold into hierarchical representations via meta-learning and Bayesian inference. Our modeling evidence suggests that these hierarchical policies are structured in a temporally backward, rather than forward, fashion. Taken together, these algorithmic architectures characterize how the interplay between reinforcement learning, policy compression, meta-learning, and working memory supports structured decision-making and compositionality in a resource-rational way.

BACKGROUND: The American College of Cardiology, American Heart Association, and Centers for Medicare and Medicaid Services recommend shared decision-making (SDM) for patients with severe aortic stenosis choosing between transcatheter aortic valve replacement (TAVR) and surgical aortic valve replacement (SAVR). Although tools such as patient decision aids (DAs) and training in SDM have been shown to improve SDM, implementation of SDM and DAs is limited. The IMproving treatment decisions for Patients with AortiC stenosis Through Shared Decision Making (IMPACT SDM) study aims to (1) determine the effectiveness of the interventions (a DA and clinician SDM training) in achieving SDM (primary outcome) and improving the quality of decisions about aortic valve replacement, (2) determine the reach of the DAs and adoption of training, and (3) explore potential mechanisms of effectiveness and implementation at the patient-, clinician-, and clinic-level. METHODS: The study is a hybrid type II effectiveness-implementation study using a cluster randomized batched stepped wedge trial with 8 sites across the USA. Eligible patients will be surveyed before and after visits with the heart valve team; clinicians will be surveyed after visits. Reach of DAs and adoption of training will be tracked. Clinicians will be interviewed regarding barriers and facilitators to implementation. DISCUSSION: The IMPACT SDM Study seeks to provide evidence of the ability of the interventions to improve SDM and decision quality, and also to shed light on barriers and facilitators to SDM implementation to promote future implementation efforts. TRIAL REGISTRATION: ClinicalTrials.gov NCT06171737. Registered on December 15, 2023.

Decision-making on childbearing and safer conception use in HIV sero-different couples involves an intricate balance of individual desires and perceived HIV acquisition risk. This paper addresses an important knowledge gap regarding HIV sero-different couples considerations and the relationship and power dynamics involved when deciding to use a safer conception method. Between February and June 2019, we conducted semi-structured in-depth interviews among 14 men and 17 women, representing 17 couples, who exited the SAFER study - a pilot study assessing the feasibility, acceptability and cost-effectiveness of a safer conception programme for HIV sero-different couples in Zimbabwe. All couples in SAFER were provided with a choice of safer conception methods and were followed for up to 12 months of pregnancy attempts and 3 months following pregnancy. While couples generally perceived their safer conception discussions to be easy and consensus-driven, the decision-making process also involved complex gender dynamics and trade-offs in relationship power, which resulted in differing interpretations of what constituted a joint or shared couple decision. Participants regarded effective couple communication as an essential component of and precursor to good safer conception conversations and requested additional training in couple communication. Couples relied on information from healthcare providers to kickstart their safer conception discussions. Safer conception programmes should address relationship power imbalances, promote effective couple communication and offer healthcare provider support to enable HIV sero-different couples to make informed choices about conception in a manner that upholds their safety and reproductive autonomy.