Cost Trade-offs Research Articles

A Real Options Perspective on Entrepreneurial Orientation and Government Ties

Firms’ strategic orientation toward entrepreneurship exposes them to regulatory uncertainties. Prior research suggests that addressing these uncertainties through corporate political activities (CPA) may require costly trade-offs, such as the loss of strategic flexibility. We argue that some of these trade-offs can be mitigated by the way firms structure their CPA. We extend the insights from real options reasoning (ROR) to offer a framework for how firms may circumvent some of these trade-offs through greater CPA breadth, which allows firms to retain their strategic flexibility while reaping some of the benefits of CPA.

Evaluation of Reporting Quality of Systematic Reviews on Health Economic Evaluation Studies Based on the CHEERS Statement: An Overview of Reviews

Background: Economic evaluations in healthcare are designed to inform decisions by the estimation of cost and effect trade-off of two or more interventions. We aimed to evaluate the standards of systematic reviews on health economic evaluation studies using the CHEERS (Consolidated Health Economic Evaluation Report Standards) tool. Methods: We searched the PubMed database with keywords CHEERS and its complete form in combination with keywords related to cost or economic evaluation without language and time limits until November 17, 2021. The CHEERS tool was then used to include systematic reviews. Results: Overall, 32 systematic reviews, included 610 primary studies were included. Of the 32 included studies, only 1 study (3.1%) had poor quality, 5 studies (15.6%) had good quality, remaining studies had very good and excellent quality. Conclusion: Some studies still have problems in expressing the standards. The necessity of standards for reporting economic evaluation studies in the field of health is very serious, and Cheers is one of the most important tools.

More Efficient Smaller Multi-Cancer Screening Trials.

The NHS-Galleri trial has demonstrated feasibility for multi-cancer screening trial design where all participants provide a 'sample' for screening, but only samples from the intervention arm are tested and acted upon during the trial. We assess efficiency of analysis methods when the control arm may be retrospectively tested at time of analysis. Analyses considered are: (1, traditional) by randomised allocation with all events included; (2, 'intended-effect') nested in those who tested positive in both arms and all events therein; and (3, targeted) by randomised allocation but with endpoint 'test-positive event'. They are compared using approximate statistical methods and scenario analysis. Provided the number who die from cancer after a test-positive sample is a small fraction of the total number who die from cancer, intended-effect and targeted analyses require a much smaller sample size to evaluate cancer-specific mortality than the traditional approach. Intended-effect analysis has a smaller sample size requirement than targeted analysis. This gain is only substantial when the risk of cancer death in test positives is high. Intended-effect or targeted analysis will substantially reduce the sample size needed to evaluate cancer-specific mortality in blood-based screening trials. Targeted analysis requires many fewer retrospective tests and avoids potential effects of needing to inform those whose stored samples test positive. Trialists should consider the trade-off of costs between sample size and retrospective testing requirements when choosing the analysis.

Increased Reproductive Output and Telomere Shortening Following Calcium Supplementation in a Wild Songbird.

Life history theory predicts increased parental investment comes with fitness costs, often expressed as negative effects on survival and future reproduction. To better understand the costs of reproduction and life history trade-offs, we evaluated calcium supplementation at a high-elevation site in Colorado as a novel approach to experimentally alter reproductive investment in nesting female Tachycineta bicolor (tree swallow). Calcium is a nutrient critical to avian reproduction as the intake of natural calcium is essential for egg production, embryo development, and nestling growth. Altering calcium availability exclusively during the breeding season allowed examination of individual biological responses to experimental modification of reproduction, as well as the reproductive costs associated with egg production and laying an entire clutch. As a functional endpoint and proxy for fitness and longevity, telomere length was measured at the beginning and end of each breeding season. Telomeres-protective "caps" at the ends of chromosomes-have been shown to shorten with aging and a variety of stressors, including higher reproductive output. Results demonstrate that tree swallow mothers supplemented with calcium during the breeding season experience higher reproductive output and produce offspring with longer telomeres, which came at the cost of relatively shorter telomeres during the reproductive season. These findings provide additional support for reproductive trade-offs, and also challenge previous calcium supplementation studies that suggest excess calcium reduces the cost of reproduction.

Tank pool fire domino effect prevention by inherently safer layout planning: A techno-economic analytical index

Tank pool fire domino effects, represented by their capacities of accident consequence escalation and extensive damages, present substantial safety challenges within chemical storage systems. In this work, the inherent safety concept is introduced to proactively address these challenges while ensuring cost-effectiveness. Accordingly, a dedicated novel metric called Inherent Safety & Economic Risk Index (IS&ERI) is proposed to make safety and cost trade-offs for indicating the risk levels of various tank farm layout options. To develop the IS&ERI, the Dow's loss estimate procedure is adapted for representing the economic implications, and the Bayesian Networks are employed for indicating the failure probabilities of target units considering the synergistic effects of multiple pool fires. Two improved graph theory metrics are presented to determine the root nodes of the Bayesian Networks. For demonstrating the proposed IS&ERI, a case study is conducted and the results show that the IS&ERI of 4 tank farm layout options are 0.2991, 0.3120, 0.3525, and 0.2285, implying that Option 4 is the best layout with the lowest potential loss in case of the pool fire domino effects. As the key research contribution, the IS&ERI is presented and it can be used as a useful tool to compare and select the best tank farm layout option to eliminate or significantly reduce the knock-on effects of tank pool fires at their sources.

Voltage Stacking: A First-Order Modelization of an m × n Asynchronous Array for Chip and Architectural Design Exploration

Voltage stacking is a technique in which multiple integrated circuits are stacked in series between the supply voltage instead of in parallel, thus improving the energy efficiency of the power distribution network. Unfortunately, voltage stacking presents stability challenges for integrated circuits within the stack. A first-order model to quantify variability, stability, and power metrics for an array of voltage-stacked asynchronous integrated circuits is presented. Voltage variability and power consumption are accounted for and discussed. Limitations of the model are identified outside of the nominal behavior. The number of columns in the architecture, chip leakage, and supply voltage are shown to be the key contributors to the stability, performance, and energy efficiency of a system of voltage-stacked asynchronous processors. A higher leakage to active power ratio, though usually avoided by chip designers, is shown to improve stability and be key in designing stacks without external balancing. Outputs of the model enable system and chip designers to evaluate first-order trade-offs in energy efficiency, performance, and system cost. These fundamental data allow designers to make informed design and optimization trade-offs between asynchronous voltage-stacked architectures and the integrated circuits used therein. Analysis of this model shows that various voltage-stacked configurations, such as one with a 48 V supply using 100 rows and 11 columns, can be designed with less than 10% voltage variation per chip, mitigating the need for external voltage balancing.

Greenhouse gas, water, and economic implications of permeable pavements: Quantification for pilot sponge cities in China

Climate change has exacerbated the occurrence of extreme storms, resulting in urban flooding. However, rainwater is a potential source of water for various end uses of municipal water. In this context, permeable pavements are promising for mitigating floods and alleviating water stress in cities. Herein, a process-based life-cycle inventory modeling approach was used to quantify the life-cycle greenhouse gas (GHG) and water footprints of different road pavements in 28 pilot sponge cities in China. Three asphalt pavements were considered in this study: permeable-surface, permeable-base, and conventional nonpermeable pavements. Moreover, life-cycle cost analyses were performed to reveal the cost-effectiveness of these pavements. Results showed that permeable-base pavements exhibited the highest levelized GHG emissions (5.9 kg CO2e/m2/yr), followed by nonpermeable (5.5 kg CO2e/m2/yr) and permeable-surface pavements (3.8 kg CO2e/m2/yr). In terms of levelized water footprint, permeable-base and permeable-surface pavements enabled water savings (433.8 and 304.1 kg/m2/yr, respectively), while nonpermeable pavements consumed 30.6 kg/m2/yr of water. The levelized life-cycle costs of permeable-surface, permeable-base, and nonpermeable pavements were 32.8, 35.4, and 40.5 yuan/m2/yr, respectively. With regard to transitioning from nonpermeable to permeable pavements in urban road construction, Chongqing and Shenzhen presented favorable potential for GHG mitigation (22 and 26 kt CO2e/yr, respectively) and water savings (196 and 187 Mt/yr, respectively). Contrarily, Hebi, Yuxi, Sanya, Qianan, Chizhou, and Xining were not cost-effective in terms of GHG emission reduction. Moreover, in this study, GHG–water–cost tradeoffs were identified among different pavements, highlighting directions for unlocking the green benefits of installing permeable asphalt pavements in China.

Design-Point Techno-Economics of Brayton Cycle PTES for Combined Heat and Power

Abstract Pumped thermal energy storage (PTES) systems are grid batteries that use heat pumps to create both hot and cold thermal energy stores when there is excess electricity and then use a power cycle to convert the thermal energy into electricity when there is demand for electricity. In normal operation, Joule-Brayton PTES discharges low-grade heat at temperatures useful for thermal energy consumers like district and industrial heating. Furthermore, PTES designs, like conventional combined heat and power (CHP) technology, can be modified to sacrifice some round-trip efficiency (RTE) to increase the temperature of heat rejection. This paper uses design-point performance and cost models that provide a detailed understanding of the efficiency and cost trade-offs of rejecting heat at various temperatures in ideal-gas Brayton PTES configurations. First, we keep the heat rejection in its nominal location in the PTES system. Next, we move the heat rejection to the discharge turbine exit. We define design-point metrics that isolate both the cost and performance penalty associated with the hotter heat rejection and attribute it exclusively to the heat economic metrics. We find that the levelized cost of heat, including the cost of thermal energy storage (TES) buffering the PTES and heat off-taker, compares favorably versus electric technologies and is less than the cost of natural gas for low temperature scenarios and competitive with the cost of natural gas in some regions of the contiguous United States in high temperature scenarios.

(Invited) Analog Computation-in-Memory (CiM) for AI and Neuromorphic Computing

[Invited talk]This paper overviews analog Computation-in-Memory (CiM) with non-volatile memories for AI applications and neuromorphic computing. In the edge IoT/mobile devices, CiM will be heterogeneously integrated with digital processors such as CPUs to realize the inference of AI with high energy efficiency.This talk also introduces the approximate CiM. Inspired by the approximate computing, by tolerating some degree of memory errors, the trade-off of performance, energy and cost is resolved.Finally, this paper covers various AI algorithms and neuromorphic computing such as Convolutional Neural Network (CNN), Recurrent Neural Network (RNN), event driven Spiking Neural Network (SNN) and Reservoir Computing.

(Invited) Comparing and Contrasting the Advantages and Challenges of Catalysts for Low Temperature AEM, AEL, and PEM Electrolysis

Electrolysis has been promoted as a critical route to enabling green hydrogen and a broader US Department of Energy supported H2@Scale vision enabling a clean, economic and sustainable energy system.1 Low temperature electrolysis offers advantages over high temperature electrolysis in high temperature materials challenges, limited intermittency capabilities, thermal integration, lower manufacturing and technology readiness, steam conversion and separation challenges.2 Within low temperature electrolysis anion exchange membrane (AEM), (liquid) alkaline (AEL) and proton exchange membrane (PEM) electrolysis are the three primary electrolysis technologies being investigated.These electrolysis environments are different and the catalyst materials they employ, and the cost, natural abundance, performance, and durability limitations are all different. These factors have a significant impact on the research focus and needs for each of these competing technologies. This presentation will explore catalysis in each one of these systems and compare critical limitations of each.The PEM system depends on Ir for anode (OER) catalysis. Ir is expensive and one of the least abundant elements in the earth’s crust. While earth abundance of Ir may is a potential concern for projections of electrolysis needs,3,4 the ability to thrift Ir more efficiently and achieve improved durability are critical for achieving hydrogen cost targets. Specific features impacting the cost, performance and durability trade-offs of Ir in PEM electrolysis will be discussed in terms of hydrogen levelized costs and the research advances necessary to have a positive impact on PEM electrolyzers.AEM and AEL electrolysis are distinct in terms of the concentration of supporting (KOH) electrolytes being investigated and the types of electrodes typically employed. AEM electrolyzers typically work at 1M KOH concentrations or below and employ thin film electrodes with alkaline ionomer as a parallel to most PEM designs. AEL electrolyzers typically operate at high (30 wt% KOH) concentrations and consist of electrodes deposited onto metal substrates rather than deposited as a thin film onto the membrane/separator. The materials sets and some of the performance and durability challenges of each of these systems are similar. They also have challenges at both the anode and cathode, where as PEM cathodes operate highly efficiently and durably with low loadings of Pt. The primary advantage of alkaline systems is the ability to enable highly earth abundant electrocatalysis, but challenges remain for performance and durability tradeoffs. These aspects as well as their implications for hydrogen levelized cost will be presented along with target research needs. https://www.energy.gov/eere/fuelcells/h2scale.Alex Badgett, Mark Ruth, Bryan Pivovar, “Economic considerations for hydrogen production with a focus on polymer electrolyte membrane electrolysis,” Electrochemical Power Sources: Fundamentals, Systems, and Applications, 2022, 327-364.Cortney Mittelsteadt, Esben Sorensen, and Qingying Jia, Ir Strangelove, or How to Learn to Stop Worrying and Love the PEM Water Electrolysis Energy Fuels 2023, 37, 17, 12558–12569.Mark Clapp, Christopher M. Zalitis, Margery Ryan, Perspectives on current and future iridium demand and iridium oxide catalysts for PEM water electrolysis, Catalysis Today 420 (2023) 114140.

Time and Cost Optimization Analysis of Reservoir Building Work in Wosusokas Regional SPAM Project using Time Cost Trade Off Method

Cost and time optimization is an important aspect of project management that aims to achieve optimal efficiency in the use of resources. Time Cost Trade Off (TCTO) method is often used to manage the relationship between time and cost in project completion. This research analyzes cost and time op-timization on construction projects using Primavera P6 software. In optimi-zation with the addition of working hours, 4 alternatives were carried out, namely the addition of 1 hour, 2 hours, 3 hours, and 4 hours of work, the re-sults obtained were a shorter duration but the total cost was getting bigger. Whereas in the alternative of adding workers as many as 1 worker and 2 workers, the optimization results obtained a shorter duration and a reduced total cost. Thus, the TCTO method and the use of Primavera P6 proved ef-fective in identifying the most efficient optimization strategy to achieve pro-ject success on time and within budget.

Signatures of Bayesian inference emerge from energy-efficient synapses.

Biological synaptic transmission is unreliable, and this unreliability likely degrades neural circuit performance. While there are biophysical mechanisms that can increase reliability, for instance by increasing vesicle release probability, these mechanisms cost energy. We examined four such mechanisms along with the associated scaling of the energetic costs. We then embedded these energetic costs for reliability in artificial neural networks (ANNs) with trainable stochastic synapses, and trained these networks on standard image classification tasks. The resulting networks revealed a tradeoff between circuit performance and the energetic cost of synaptic reliability. Additionally, the optimised networks exhibited two testable predictions consistent with pre-existing experimental data. Specifically, synapses with lower variability tended to have (1) higher input firing rates and (2) lower learning rates. Surprisingly, these predictions also arise when synapse statistics are inferred through Bayesian inference. Indeed, we were able to find a formal, theoretical link between the performance-reliability cost tradeoff and Bayesian inference. This connection suggests two incompatible possibilities: evolution may have chanced upon a scheme for implementing Bayesian inference by optimising energy efficiency, or alternatively, energy-efficient synapses may display signatures of Bayesian inference without actually using Bayes to reason about uncertainty.

Signatures of Bayesian inference emerge from energy-efficient synapses

Biological synaptic transmission is unreliable, and this unreliability likely degrades neural circuit performance. While there are biophysical mechanisms that can increase reliability, for instance by increasing vesicle release probability, these mechanisms cost energy. We examined four such mechanisms along with the associated scaling of the energetic costs. We then embedded these energetic costs for reliability in artificial neural networks (ANNs) with trainable stochastic synapses, and trained these networks on standard image classification tasks. The resulting networks revealed a tradeoff between circuit performance and the energetic cost of synaptic reliability. Additionally, the optimised networks exhibited two testable predictions consistent with pre-existing experimental data. Specifically, synapses with lower variability tended to have (1) higher input firing rates and (2) lower learning rates. Surprisingly, these predictions also arise when synapse statistics are inferred through Bayesian inference. Indeed, we were able to find a formal, theoretical link between the performance-reliability cost tradeoff and Bayesian inference. This connection suggests two incompatible possibilities: evolution may have chanced upon a scheme for implementing Bayesian inference by optimising energy efficiency, or alternatively, energy-efficient synapses may display signatures of Bayesian inference without actually using Bayes to reason about uncertainty.

A location fingerprinting approach for the automated radio telemetry of wildlife and comparison to alternative methods

BackgroundAutomated radio telemetry (ART) systems enable high-temporal resolution data collection for species unsuited to satellite-based methods. A challenge of ART systems is estimating the location of radio tagged animals from the radio signals received on multiple antennas within an ART array. Localisation methods for ART systems with omni-directional receivers have undergone rapid development in recent years, with the inclusion of machine learning techniques. However, comparable machine learning methods for ART systems with directional antennas are unavailable, despite their potential for improved accuracy and greater versatility. To address this, we introduce an open-source machine learning-based location fingerprinting method for directional antenna-based ART systems. We compare this method to two alternative localisation approaches. Both alternatives use relative signal strengths recorded among multiple antennas to estimate the signal’s angle of arrival at each receiver. In the ‘biangulation’ approach, the location is estimated by finding the intersection of these angles from two receivers. In contrast, the ‘linear regression’ approach uses a linear regression model to estimate the distance from the receiver along the angle of arrival, providing a location estimate. We evaluate these methods using an ART data set collected for the southern black-throated finch (Poephila cincta cincta), in the Desert Uplands Bioregion of Queensland, Australia.ResultsThe location fingerprinting method performed slightly better than the best performing alternative, the linear regression method, with mean positional errors of 308 m (SE = 17.7) and 335 m (SE = 18.5), respectively. The biangulation method performed substantially worse, with a mean positional error of 550 m (SE = 42.9, median = 540 m). Improved accuracy was observed with shorter distances between transmitters and receivers, higher signal strengths, and a greater number of detecting receivers, suggesting that increasing receiver density improves localisation accuracy, albeit with potential trade-offs in system coverage or cost. Furthermore, shorter pulse intervals of transmitters resulted in greater accuracy, highlighting the trade-offs among battery life, transmitter weight and radiative power.ConclusionsThe open-source location fingerprinting method offers an improved and versatile localisation approach suitable for a wide variety of ART system designs, addressing the challenge of developing study-specific localisation methods using alternative approaches.

Achieving net-zero U.S. ammonia: Technology and policy options and their emissions, investment, and cost tradeoffs

Ammonia production is responsible for around 35% of the CO2 emissions associated with the global chemical sector. In this study, a bottom-up model with high technical and economic resolution is implemented to assess potential least-cost pathways to achieve a net-zero U.S. ammonia industry by 2050. Results indicate that natural gas reformers equipped with carbon capture technologies may play a key role in decarbonizing U.S. ammonia production in the near term, while water electrolysis will be required in the long term to achieve net-zero emissions. Technical improvements and cost reductions in electrolyzers and lower-cost renewable electricity will be needed to accelerate the adoption of water electrolysis. Furthermore, two key policy interventions were investigated (carbon pricing and production tax credits) and were found to hold significant potential for accelerating low-carbon ammonia production technologies and for further reducing the cumulative carbon emissions. The methodology and analyses presented in this study provide important insights into available transition pathways to decarbonized U.S. ammonia production, providing fundamental insights for policy makers on required actions and investments to achieve the net-zero emissions targets.

A Constraint Programming Approach for Discrete Time–Cost Tradeoff Problems in a Time-Constrained Activity Network

The discrete time-cost tradeoff problem (DTCTP) is a well-researched topic in the field of operations research. The majority of existing DTCTP models are based on traditional activity networks, which permit the execution of an activity as soon as all its predecessors have been completed. This assumption is reasonable, but it is important to note that there are always exceptions. The main work of this study was threefold. Firstly, we expanded the analysis of the DTCTP to encompass time-constrained activity networks (DTCTPTC), which encompassed three different types of time constraints. The first constraint was the time-window constraint, which limited the time interval during which an activity could be executed. The second constraint was the time-schedule constraint, which specified the times at which an activity could begin execution. The third constraint was the time-switch constraint, which required project activities to start at specific times and remain inactive during designated time periods. Secondly, a constraint programming (CP) model was developed for the purpose of solving the DTCTPTC. The model employed interval variables to define the activity and its potential time constraints, while CP expressions were utilized to ensure the feasibility of the solution. The objective was to identify the optimal execution mode for each activity, the optimal start times for time-scheduled activities, and the optimal work/rest patterns for time-switch activities, with the aim of minimizing the total cost of the project. Finally, the efficacy of the proposed CP model was validated through two case studies based on two illustrative projects of varying sizes. The outcomes were then compared against existing algorithms. The results demonstrated that time constraints were important factors affecting schedule optimization, and the proposed CP model had the ability to solve large-scale DTCTPTC.

Opportunistic and delayed maintenance as strategies for sustainable maintenance practices

PurposeOpportunistic and delayed maintenances are increasingly becoming important strategies for sustainable maintenance practices since they increase the lifetime of complex systems like aircrafts and heavy equipment. The objective of the current study is to quantify the optimal time window for adopting these strategies.Design/methodology/approachThe current study considers the trade-offs between different costs involved in the opportunistic and delayed maintenances (of equipment) like the fixed cost of scheduled maintenances, the opportunistic rewards that may be earned and the cost of premature parts replacement. The probability of the opportunistic maintenance has been quantified under two different scenarios – Mission Reliability and Renewal Process. In the case of delayed maintenance, the cost of the delayed maintenance is also considered. The study uses optimization techniques to find the optimal maintenance time windows and also derive useful insights.FindingsApart from finding the optimal time window for the maintenance activities the study also shows that opportunistic maintenance is beneficial provided the opportunistic reward is significantly large; the cost of conducting scheduled maintenance in the pre-determined slot is significantly large. Similarly, the opportunistic maintenance may not be beneficial if the pre-mature equipment parts replacement cost is significantly high. The optimal opportunistic maintenance time is increasing function of Weibull failure rate parameter “beta” and decreasing function of Weibull failure rate parameter “theta.” In the case of optimal delayed maintenance time, these relationships reverse.Originality/valueTo the best of our knowledge, very few studies exist that have used mission reliability to study opportunistic maintenance or considered the different cost trade-offs comprehensively.

Paternal care plasticity: males care more for early- than late-developing embryos in an arboreal breeding treefrog

BackgroundParental care benefits offspring but comes with costs. To optimize the trade-off of costs and benefits, parents should adjust care based on intrinsic and/or extrinsic conditions. The harm to offspring hypothesis suggests that parents should invest more in younger offspring than older offspring because younger offspring are more vulnerable. However, this hypothesis has rarely been comprehensively tested, as many studies only reveal an inverse correlation between parental care and offspring age, without directly testing the effects of offspring age on their vulnerability. To test this hypothesis, we studied Kurixalus eiffingeri, an arboreal treefrog with paternal care. We first performed a field survey by monitoring paternal care during embryonic development. Subsequently, we conducted a field experiment to assess the prevalence of egg predators (a semi-slug, Parmarion martensi) and the plasticity of male care. Finally, we conducted a laboratory experiment to assess how embryo age affects predation by P. martensi.ResultsOur results showed that (1) male attendance and brooding frequency affected embryo survival, and (2) males attended and brooded eggs more frequently in the early stage than in the late stage. The experimental results showed that (3) males increased attendance frequency when the predators were present, and (4) the embryonic predation by the semi-slug during the early was significantly higher than in the late stage.ConclusionsOur findings highlight the importance of paternal care to embryo survival, and the care behavior is plastic. Moreover, our results provide evidence consistent with the predictions of the harm to offspring hypothesis, as males tend to care more for younger offspring which are more vulnerable.

Employing Tank Constraints to Present Total Cost and Water Age Trade-Offs in Optimal Operation of Water Distribution Systems

Employing Tank Constraints to Present Total Cost and Water Age Trade-Offs in Optimal Operation of Water Distribution Systems

Behavioural responses of brown bears to roads and hunting disturbance.

Harvest regulations commonly attenuate the consequences of hunting on specific segments of a population. However, regulations may not protect individuals from non-lethal effects of hunting and their consequences remain poorly understood. In this study, we compared the movement rates of Scandinavian brown bears (Ursus arctos, n = 47) across spatiotemporal variations in risk in relation to the onset of bear hunting. We tested two alternative hypotheses based on whether behavioural responses to hunting involve hiding or escaping. If bears try to reduce risk exposure by avoiding being detected by hunters, we expect individuals from all demographic groups to reduce their movement rate during the hunting season. On the other hand, if bears avoid hunters by escaping, we expect them to increase their movement rate in order to leave high-risk areas faster. We found an increased movement rate in females accompanied by dependent offspring during the morning hours of the bear hunting season, a general decrease in movement rate in adult lone females, and no changes in males and subadult females. The increased movement rate that we observed in females with dependant offspring during the hunting season was likely an antipredator response because it only occurred in areas located closer to roads, whereas the decreased movement rate in lone females could be either part of seasonal activity patterns or be associated with an increased selection for better concealment. Our study suggests that female brown bears accompanied by offspring likely move faster in high-risk areas to minimize risk exposure as well as the costly trade-offs (i.e. time spent foraging vs. time spent hiding) typically associated with anti-predator tactics that involve changes in resource selection. Our study also highlights the importance of modelling fine-scale spatiotemporal variations in risk to adequately capture the complexity in behavioural responses caused by human activities in wildlife.