Cost Estimates Research Articles

Hybrid manufacturing cost models: Additive friction stir deposition, measurement, and CNC machining

Based on its potential to reduce lead times, hybrid manufacturing, which often includes both additive manufacturing and machining processes, is receiving more attention from manufacturers as they seek to increase their supply chain resilience and efficiency. A new solid-state additive manufacturing, referred to as additive friction stir deposition (AFSD), has shown the potential to become an important process for hybrid manufacturing. To justify the selection of a hybrid manufacturing approach, the cost needs to be estimated for comparison to conventional approaches. Historically, hybrid manufacturing costs have been difficult to estimate due to the complexity and diversity of the manufacturing processes. This paper proposes cost models that include additive friction stir deposition, structured light scanning, milling, and turning, which can be combined in hybrid manufacturing process planning. These cost models are demonstrated in a case study and cost estimates are compared for hybrid and conventional (machining-only) manufacturing approaches. For the selected case, the hybrid manufacturing process cost was $1007.58, while the conventional milling process cost was $833.60. The results of the case study show that both labor and material costs must be considered to make an informed decision between hybrid and conventional manufacturing approaches.

Costs and benefits of routine labs in hospital patients: iatrogenic anaemia and undiagnosed acute kidney injury

ImportanceGuidelines recommend avoiding unnecessary laboratory tests to minimise risks of anaemia in hospitalised patients as well as reduce costs, but there are costs to skipping routine labs including missing acute...

Cost effectiveness of a vascular access education and training program for hospitalized emergency department patients.

Education and training in vascular access is a critical component to delivering quality vascular access care. Given that organizations must invest resources to implement and sustain high-quality vascular access programming, we aimed to demonstrate the cost effectiveness of a program (Operation STICK (OSTICK)) in the emergency department (ED). This was an observational cohort study conducted at a tertiary care academic center with 120,000 ED visits. Consecutive hospitalized adults with ultrasound-guided (DIVA) and traditionally-placed (non-DIVA) peripheral intravenous catheters (PIVC) in the ED were included in the analysis. Two groups (OSTICK and non-OSTICK) were compared in the analysis: OSTICK PIVCs were inserted by clinicians with formal, standardized training in peripheral venous access while non-OSTICK PIVCs were inserted by staff with basic departmental training in PIVC care. Cost factors included number of procedures, wait time to establish a PIVC, complications, and training. Effect was complication-free PIVC functionality. Multiple linear regressions were used to estimate incremental cost (ΔC), incremental effect (ΔE), and incremental net benefit (INB) of the OSTICK program. From 10/1/2022 thru 3/31/2023, 21,259 PIVCs including 1681 OSTICK and 19,578 non-OSTICK PIVCs were included in the analysis. Average age was 64.8 and 53.7% were female. The estimate of incremental cost (ΔC) for each patient was -$83.175 (95% CI: -$103.953 to -$62.398; p<0.001), indicating that the OSTICK group saves money compared to the non-OSTICK group. The OSTICK group is also more effective at increasing the proportion of catheter dwell time relative to hospital length of stay (ΔE), with an estimate of 0.037 (95% CI: 0.016 to 0.059; p<0.001), compared to those in the non-OSTICK group. The estimated incremental cost-effectiveness ratio (ICER) for the OSTICK group compared with the non-OSTICK group was -$221.964 (95% CI: -$177.400 to -$381.716) per ten percentage points of PIVC dwell time to hospital length of stay increase. Strategic investment in vascular access education and training can yield impressive financial returns while simultaneously enhancing vascular access outcomes. It is imperative for organizations to recognize the significant impact of such initiatives and prioritize the implementation of comprehensive programs.

National Estimates of Direct Health Care Costs Associated with Catheter-Related Bloodstream Infection among Hospitalized Hemodialysis Patients in Australia

National Estimates of Direct Health Care Costs Associated with Catheter-Related Bloodstream Infection among Hospitalized Hemodialysis Patients in Australia

The Controversy over Price Transparency: Patients and Plastic Surgeons Disagree.

The No Surprises Act (NSA) went into effect on January 1, 2022. This federal law is designed to minimize surprise bills for emergency care, out of network (OON) care, and care for uninsured or self-pay individuals. To achieve these goals, the NSA relies heavily on physicians providing cost estimates to patients prior to administering care. Because healthcare is often price-opaque, this study was conducted to assess physician and patient attitudes toward price transparency in plastic surgery and aesthetic/self-pay medicine. Two cohorts of providers received a survey asking whether and how their practice offers pricing information prior to a consultation and their views regarding the NSA. Patients who had previously used an online price estimator tool also received a survey regarding their experience and accuracy of estimates received online. Most surveyed providers do not share the costs of their services online, whereas patients had a positive experience when receiving estimates of medical services before consultation. Although many providers cited the inaccuracy of price estimator tools as a reason not to incorporate them into their website, most patients reported that their final cost of service was close to (or even less than) the estimate received online prior to the consultation. This study suggests that price transparency is a patient satisfier. Therefore, plastic surgeons should exercise price transparency to be compliant with federal law and to gain a competitive advantage in the market, as the decision to implement price transparency can be mutually beneficial to patients and providers.

Estimation of two-year hospital costs of hip and knee periprosthetic joint infection treatments using activity-based costing.

Our aim was to estimate the total costs of all hospitalizations for treating periprosthetic joint infection (PJI) by main management strategy within 24 months post-diagnosis using activity-based costing. Additionally, we investigated the influence of individual PJI treatment pathways on hospital costs within the first 24 months. Using admission and procedure data from a prospective observational cohort in Australia and New Zealand, Australian Refined Diagnosis Related Groups were assigned to each admitted patient episode of care for activity-based costing estimates of 273 hip PJI patients and 377 knee PJI patients. Costs were aggregated at 24 months post-diagnosis, and are presented in Australian dollars. The mean cost per hip and knee PJI patient was $64,585 (SD $53,550). Single-stage revision mean costs were $67,029 (SD $47,116) and $80,063 (SD $42,438) for hip and knee, respectively. Two-stage revision costs were $113,226 (SD $66,724) and $122,425 (SD $60,874) for hip and knee, respectively. Debridement, antibiotics, and implant retention in hips and knees mean costs were $53,537 (SD$ 39,342) and $48,463 (SD $33,179), respectively. Suppressive antibiotic therapy without surgical management mean costs were $20,296 (SD $8,875) for hip patients and $16,481 (SD $6,712) for knee patients. Hip patients had 16 different treatment pathways and knee patients had 18 treatment pathways. Additional treatment, episodes of care, and length of stay contributed to substantially increased costs up to a maximum of $369,948. Treating PJI incurs a substantial cost burden, which is substantially influenced by management strategy. With an annual PJI incidence of 3,900, the cost burden would be in excess of $250 million to the Australian healthcare system. Treatment pathways with additional surgery, more episodes of care, and a longer length of stay substantially increase the associated hospital costs. Prospectively monitoring individual patient treatment pathways beyond initial management is important when quantifying PJI treatment cost. Our study highlights the importance of optimizing initial surgical treatment, and informs treating hospitals of the resources required to provide care for PJI patients.

Evaluating the Impact of Artificial Intelligence in Managing Construction Engineering Projects

This study evaluates the impact of utilizing artificial intelligence (AI) in managing construction engineering projects. With the increasing complexity and scale of construction projects, AI offers promising solutions to enhance efficiency, accuracy, and decision-making processes. The study investigates the potential benefits, challenges, and practical applications of AI through detailed case studies. The study employs a mixed-methods approach, combining qualitative and quantitative research methods. Data was collected through literature reviews and case studies where AI had been successfully implemented. The analyses included comparisons between projects that used AI and those that did not. The findings demonstrated significant improvements in project efficiency, cost estimation accuracy, and risk management. For instance, AI-powered systems reduced scheduling errors by 35%, leading to more accurate timelines. Additionally, the integration led to a 20% reduction in project durations due to improved resource allocation and proactive risk management. Furthermore, AI-supported systems contributed to a 25% improvement in stakeholder satisfaction. In terms of cost estimation, AI-powered estimation tools improved the accuracy of cost estimates by 30%, helping to reduce budget overruns by 40%. In risk management, AI-supported tools enhanced the accuracy of risk identification by 45%, leading to the early detection of potential issues and the development of effective mitigation strategies that reduced the impact of risks by 30%. Thanks to these improvements, project success rates increased by 20%. These results demonstrate that integrating AI into the management of engineering construction projects can lead to tangible improvements in project efficiency, cost accuracy, and risk management, thereby enhancing stakeholder satisfaction and contributing to more successful project outcomes.

BIM IMPLEMENTATION FOR HERITAGE RENOVATION THROUGHOUT PROJECT LIFECYCLE: CURRENT USE, BENEFITS, AND BARRIERS

Introduction: Building Information Modeling (BIM) has garnered significant attention due to advancements in sophisticated technologies and methods. However, a comprehensive review of the existing literature indicates a lack of research exploring the application of BIM in managing the entire intervention design and renovation processes from a broader system perspective. The purpose of the study was to fill this gap by identifying and evaluating the current utilization, benefits, and barriers associated with implementing BIM in the lifecycle of renovation projects. The study methodology is based on conducting 31 structured interviews with experienced professionals who have employed BIM in their project deliveries. The results reveal that the primary benefits of BIM adoption, in descending order of importance, pertain to improved collective understanding of design intent, lower risk and better predictability of outcomes, better-designed and performing buildings, more accurate project documentation, and increased accuracy of the cost estimate. However, there are several prominent barriers: project budget, complexity of modeling historic structures, cost to hire BIM professionals, and the lack of BIM knowledge. The findings will advance BIM adoption for heritage renovation and enable project stakeholders to focus on realizing the benefits and potential uses of lifecycle BIM, while also addressing the critical challenges discussed in this study.

Development of Agribusiness in Tiwi, Albay

This study determined the status of agribusiness in Tiwi, Albay, as basis for the development of business plan. Specifically, it sought to answer the following sub- problems: 1) What are the areas of agribusiness in the Municipality of Tiwi, Albay?; 2) What are the status of agribusiness along; crop production, animal production, aquaculture production, and agri-support services and manufacturing?; 3) What are the contributions of the above areas in the agribusiness in Tiwi, Albay?; 4) What are the problems encountered in agribusiness?; and 5) What business plan may be proposed to address the problems encountered in agribusiness? The study involved presenting the agribusiness sectors contributions through tables and charts, emphasizing their economic impact and community significance. It addressed challenges by organizing issues like infrastructure or market access, supported by relevant data or case studies. It proposed a comprehensive business plan targeting specific problems with detailed strategies, cost estimates, and potential outcomes. Descriptive surveys are crucial in agribusiness research, providing detailed insights into agricultural practices and factors affecting productivity within a specific population. These surveys utilize statistical tools such as frequency percentage and weighted mean to accurately depict response distribution and measure the significance of variables. Synthesizing findings and ensuring proper citation and definition of terms in research helps draw meaningful conclusions and contribute to a broader understanding of agribusiness practices in the region. Incorporating literature demands a structured approach, starting with an introduction highlighting the topic's significance, organizing sources thematically or chronologically, and synthesizing findings while ensuring proper citation and defining terms for clarity. Descriptive surveys in agribusiness employed tools like frequency percentage to depict response distribution and weighted mean to gauge variable significance, offering precise insights into agricultural practices and factors affecting productivity within the surveyed population.

Waiting for surgery after hip fracture-Health and/or economic risk?

Waiting for surgery is a disconcerting experience. It can have a negative impact on patients' outcomes and length of stay (LOS) as driver for treatment costs. Process-optimisation may be a strategy to improve quality and cost-efficacy. The study investigates the correlation between waiting for hip fracture surgery and patient characteristics, organisational variables, outcomes, LOS, and the distribution of waiting times and LOS over time, including cost estimates. Thereby the study aims to identify the potential for organisational improvements with respect to managing the waiting time. Ten-year routine health data (patient characteristics and follow-up information) and process-indicators that is, waiting time and LOS from a Swiss trauma-centre were analysed retrospectively. Cost-estimates were calculated based on Swiss diagnosis related groups and daily costs to evaluate hospital revenues. In total, 2572 patients aged ≥60years with low-energy hip fractures were included. Waiting times >48h were associated with sub-optimal outcomes. Over the years long waiting times decreased. This reduction was not reflected by a reduction in LOS which remained stable around 10days, primarily driven by late discharge to in-patient rehabilitation. Reimbursement persisted at an average revenue in the low 4-5-digit range, depending on implant costs. While there has been a reduction of waiting times, this has not translated into a reduction of LOS or potential savings in health care costs, due to the various dependencies along the patient journey. Managing waiting times may be an area for improvement, increasing cost-efficacy, especially since long waiting times are still associated with inferior outcomes and LOS.

A tree-based approach to identify indispensable foods in minimum-cost food baskets.

Optimization techniques, such as linear programming, can be used to estimate the minimum cost of a nutrient-adequate food basket, to determine if individuals or households can afford nutritious diets. These cost estimates typically account for seasonal fluctuations but often overlook significant disruptions in the availability of affordable nutritious food that can severely impact food and nutrition security. This paper proposes a tree-based method, the binary search tree, to assess the resilience of the cost estimate of the minimum-cost food basket. In particular, this method aims to identify indispensable foods in these baskets - those whose unavailability would lead to a substantial cost increase. The binary search tree operates by iteratively excluding essential food items while ensuring the construction of minimum-cost nutritious baskets. It considers all relevant combinations of foods up to a specified size and avoids unnecessary optimizations, thereby saving computation time. We describe how the resulting tree can be evaluated and condensed to capture only the necessary information for decision makers. The construction and evaluation of the binary search tree are independent of the (dietary) restrictions or type of optimization model (i.e., linear, non-linear or integer) included. In general, the binary search tree can identify all (combinations of) foods whose exclusion leads to a significant cost increase of a nutritious food basket. Furthermore, it can detect possible substitute effects between foods and identify key limiting nutrients. A case study is presented in which the binary search tree is applied to data from Ebonyi, Nigeria, modeled using linear programming. We report all combinations of up to five foods that, when unavailable, can impact food and nutrition security in Ebonyi. The BST can provide insights into local food and nutrition security when facing drastic disruptions in access to nutritious foods by identifying indispensable foods. Its results can be used to inform and design interventions in the context of humanitarian operations.

Improvement of the UCP method for estimating labor costs in the implementation of IT-projects

An important stage of planning in the implementation of IT-projects is the assessment of the complexity of software development. An accurate estimate of labor costs at the early stage of the project life cycle significantly affects the allocation of resources, time planning and budget costs. Therefore, regardless of the large number of methods used to estimate labor costs during the implementation of an IT-project, the task of increasing the accuracy of this predictive estimate is relevant. The paper examines in detail the possibilities of using the well-known method for estimating labor costs Use Case Points (UCP), which is based on the use of use cases. It belongs to algorithmic methods, which makes it quite reliable and predictable in use. It also allows you to take into account the functional requirements for the system, which is especially useful in the early stages of project implementation. In addition, UCP is not tied to specific technologies or programming languages, which indicates its universality and flexibility. The purpose of the study is to improve the UCP method of estimating labor costs necessary for the successful implementation of an IT-project, which will allow taking into account interval estimates of technical complexity factors and external factors that affect the estimation of the amount of software and, accordingly, the estimation of the project's labor intensity. To experimentally verify the operability and efficiency of the proposed modified UCP method, a dataset containing information on 71 real projects was used. The results of computer modeling and comparative analysis of the accuracy of estimates of labor costs for the implementation of the project obtained using the proposed and original UCP methods are given. The results of the experiments showed that the proposed modification of the UCP method allows obtaining more accurate predictive estimates of labor costs in the implementation of IT-projects, which can significantly affect the efficiency of planning and project management processes.

State of HIV costing in Latin America and the Caribbean: a systematic literature review.

To summarize available data on unit costs for human immunodeficiency virus (HIV) testing, prevention, and care interventions in Latin America and the Caribbean. We conducted a systematic literature review of costing studies published between 2012 and 2024, and selected those reporting empirically measured costing data. The available data were categorized according to predefined intervention categories and compared by time and place. We also explored variations in unit costs by intervention type. Of 1 746 studies identified, 22 met the inclusion criteria, which provided 103 unique unit cost estimates from nine countries. About 50% of the included studies were published between 2019 and 2021. Antiretroviral therapy services had the most cost data available (39% of unit costs), followed by inpatient care (27%) and HIV testing (24%). Considerable cost variations were observed both within and between interventions. Our analysis underscores the need for accurate and reliable cost data to support HIV budgeting and decision-making efforts. We identified several gaps in the availability of cost data and emphasize the importance of presenting results more effectively by incorporating key contextual variables. Given the challenges of shrinking budgets and sustainability risks, robust evidence is indispensable to inform priority setting and budget allocation for HIV services.

A cost comparison of GLP-1 receptor agonists and bariatric surgery: what is the break even point?

With the prevalence of obesity rising in the US, medical management is of increasing importance. Two popular options for the treatment of obesity are bariatric surgery (e.g. sleeve gastrectomy and Roux-en-Y gastric bypass) and the increasingly popular GLP-1 Receptor Agonists (GLP-1s). This study examines the initial and long-term costs of GLP-1s compared to bariatric surgery. We compared average 2023 national retail prices for GLP-1s to surgical cost estimates from 2015 adjusted for inflation. We then plotted the cumulative medication cost over time against the flat cost of each surgery, thus calculating "break-even points" (when medication costs equal surgery costs). The findings revealed a crucial insight, for some GLP-1s like Saxenda and Wegovy, the high cost of ongoing use surpasses the cost of RYGB in less than a year and sleeve gastrectomy within nine months. Even the most affordable option, Byetta, becomes costlier than surgery after around 1.5years. This highlights the importance of looking beyond the initial financial investment when considering cost-effectiveness. Additionally, while not directly assessed, this study acknowledges that GLP-1s take time to reach full effectiveness, potentially delaying weight loss while accumulating costs. Concerns also exist about weight regain after discontinuing the medication. This study is limited by the real-world variation for individual treatment costs (e.g. insurance), a limited evaluation of long-term costs associated with either treatment modality and their co-morbidities, and the reality of patient preference providing subjective value to either modality. Overall, the study offers insights into the financial trade-offs between GLP-1s and bariatric surgery.

Dynamic soaring decouples dynamic body acceleration and energetics in albatrosses.

Estimates of movement costs are essential for understanding energetic and life-history trade-offs. Although overall dynamic body acceleration (ODBA) derived from accelerometer data is widely used as a proxy for energy expenditure (EE) in free-ranging animals, its utility has not been tested in species that predominately use body rotations or exploit environmental energy for movement. We tested a suite of sensor-derived movement metrics as proxies for EE in two species of albatrosses, which routinely use dynamic soaring to extract energy from the wind to reduce movement costs. Birds were fitted with a combined heart-rate, accelerometer, magnetometer and GPS logger, and relationships between movement metrics and heart rate-derived V̇O2, an indirect measure of EE, were analyzed during different flight and activity modes. When birds were exclusively soaring, a metric derived from angular velocity on the yaw axis provided a useful proxy of EE. Thus, body rotations involved in dynamic soaring have clear energetic costs, albeit considerably lower than those of the muscle contractions required for flapping flight. We found that ODBA was not a useful proxy for EE in albatrosses when birds were exclusively soaring. As albatrosses spend much of their foraging trips soaring, ODBA alone was a poor predictor of EE in albatrosses. Despite the lower percentage of time flapping, the number of flaps was a useful metric when comparing EE across foraging trips. Our findings highlight that alternative metrics, beyond ODBA, may be required to estimate energy expenditure from inertial sensors in animals whose movements involve extensive body rotations.

Food Insecurity Cost Estimates for El Paso, Texas

Food insecurity is a fairly pervasive problem throughout the United States that is especially burdensome for low-income regions. While the latter is generally recognized, there have been very few efforts to quantify the dollar costs of food insecurity, especially at the regional level. This study attempts to do so for El Paso County, Texas. This is achieved by first adjusting for inflation cost estimates in a prior national level study. Regional differences with respect to the nation are then utilized to calculate comparable costs for El Paso. Results indicate that the economic damage wrought by food insecurity in El Paso during 2023 exceeded $745 million. That represents nearly 2 percent of total personal income in the county for that year.

System-based ship design of a deep-sea mining vessel

ABSTRACT This paper applies the system-based ship design (SBSD) method to the conceptual design of a deep-sea mining vessel. The anticipated mine site is situated on the Norwegian extended continental shelf, where three production scenarios are assessed. The design process is documented, including a problem statement, mission description, functions, space requirements of various sub-systems, stability calculations, and preliminary cost estimates. A combination of data from existing technologies and estimates is used to set the relevant parameters, and the applicability of SBSD in the conceptual design of novel vessels is discussed. We find that when data is lacking in conceptual ship design, inspiration can be found from similar systems in established maritime industries, such as the offshore oil and gas industry.

393 The role of on-animal sensors in understanding feed intake, behavior, and performance of grazing livestock

Abstract Intake by grazing animals is difficult to reliably measure in the field, particularly in more diverse grazing systems where pastures vary greatly across time and space in resource availability, which in turn leads to greater variation in animal time budgets and intake patterns. Advances in remote livestock monitoring (e.g., on-animal sensors, walk -over-weighing), and advanced analytics such as machine learning algorithms can contribute to the development of robust, adaptable tools for better understanding of animal performance and behavior in grazing systems. Many existing tools for predicting livestock production require estimates of feed intake, and while estimates based on forage sward characteristics have been developed and used for temperate, relatively homogenous pastures, they are less well defined for more diverse rangelands. These diverse pastures are more difficult to characterize due to their greater variation in quantity and quality; consequently, animal selectivity is greater in more variable pastures. However, such feedback loops between pasture diversity and animal behavior may not yet be adequately represented in biophysical models. On-animal sensors such as accelerometers and GPS devices can be used to develop new ways of assessing relative intake by providing accurate estimates of animal location and behavior profiles, such as the use of machine learning algorithms to detect how much time is spent grazing, walking, ruminating, or resting. Measurements of animal behavior could then be combined with other animal-based methods such as walk-over-weighing and fecal NIR to improve estimates of intake and production for a wide range of extensive grazing environments. Sensor-derived measurements of animal movement could also be used to improve estimates of the energetic costs of grazing, thereby improving estimates of energy available for growth. As an example, data on recent activity and paddock use from on-animal sensors could be entered into a model to estimate current feeding requirements, then combined with weather and pasture quality forecasts. The ensuing baseline could then be used to explore the potential variability of these projections and generate a range for possible expected performance over the next month or season. This approach could be repeated over time, and animal performance and behavior measures used to update model estimates and improve forward projections. These methods could also be used in conjunction with estimates of animal energy requirements to provide real-time prediction of relative feed intake, which would provide a step-change in modelling livestock production in extensive grazing systems. For these approaches to be successful, additional calibration data are needed across a wide variety of environments and species, and the tools must be cost-effective to implement. In summary, on-animal measurements provide an adaptable, data-driven approach that could be integrated with existing tools to improve our understanding of feed intake, behavior, and performance of grazing animals.

Towards a social cost of carbon with national characteristics

The majority of estimates of the social cost of carbon use preference parameters calibrated to data for North America and Europe. We here use statistically representative data for attitudes to time and risk across the world. The social cost of carbon is substantially higher in the global north than in the south. The difference is more pronounced if we count people rather than countries.

Cost of a Healthy Diet: A Population-Representative Comparison of 3 Diet Cost Methods in Canada

BackgroundDifferent food price sources and dietary assessment tools may impact the estimation of diet costs and hamper our understanding of the relationship between diet costs and dietary intakes. ObjectivesWe aimed to investigate the effect of 3 diet cost derivation methods, with increasing numbers of food prices and geographic specificity, holding consistent the dietary assessment tool, on the estimation of diet costs overall and by food group. MethodsWe matched 24-h dietary recall data from the 2015 Canadian Community Health Survey-Nutrition (CCHS-N) to food price data from 3 Canadian Consumer Price Index (CPI) food price lists; national short list, national long list, and provincial long list. We compared the daily ($/day) and energy-adjusted ($/2000 kcal) diet costs overall and by food groups for the overall population (4+), children (4–18), and adults (19+). ResultsThe proportion of dietary intakes (grams) that were covered by CPI prices significantly increased from the national short list to the national long list but did not significantly differ from the national long list to the provincial long list. The national short list resulted in the highest daily and energy-adjusted diet costs overall. No difference in diet costs was noted between the national and provincial long lists. Diet costs for 4 food groups—additions, sweets, fruits, and vegetables, which were poorly covered by the national short list—significantly differed using the national and provincial long lists. All 3 diet cost methods were significantly correlated with energy intakes; however, a strong/very strong correlation was detected for children, and a weak/moderate correlation for adults. ConclusionsThe choice of food price data may introduce bias in the diet cost estimate, as well as limiting our understanding of how individuals allocate their diet costs. Refinement of diet cost estimation methodology and measures can strengthen future studies of how consumers allocate their purchases to their diets.