Supply Response Research Articles

Opinion Piece: New Plant-Based Food Products Between Technology and Physiology.

The rapid growth of product sectors for plant-based meat and dairy alternatives has raised significant scientific interest in their nutritional and ecological benefits. Here, it outlines the fractionation of plant-based raw materials and describes the technologies applied in the production of meat and dairy substitutes. Moreover, the study describes the effects of these new products on human nutrient supply and metabolic responses. Examples of meat-like products produced by extrusion technology and dairy alternatives are provided, addressing production challenges and the effects of processing on nutrient digestibility and bioavailability. In contrast to animal-based products, plant-based protein ingredients can contain many compounds produced by plants for defense or symbiotic interactions, such as lectins, phytates, and a wide range of secondary metabolites. The intake of these compounds as part of a plant-based diet can influence the digestion, bioaccessibility, and bioavailability of essential nutrients such as minerals and trace elements but also of amino acids. This is a critical factor, especially in regions with limited plant species for human consumption and inadequate technologies to eliminate these compounds. To fully understand these impacts and ensure that plant-based diets meet human nutritional needs, well-controlled human studies are needed.

More childcare for the poor? Budgetary impacts and female labour supply responses in Italy, Austria and Hungary

ABSTRACT This paper examines the economic implications of achieving three different childcare targets (45%, 50%, and 55%) on children from disadvantaged families in Italy, Austria and Hungary. Using a discrete choice structural labour supply model that considers childcare options, we evaluate the impact of increasing childcare slots for children under 3 in poor households, defined as those in the bottom half of the income distribution. Reaching the revised Barcelona targets of 45% formal childcare participation for children under 3 would notably boost mothers’ workforce engagement in all three countries, particularly in Austria. Moreover, the initial costs of creating additional childcare slots are nearly balanced out by the rise in income tax and social security contributions resulting from increased female labour market participation.

Category Mapping of Emergency Supplies Classification Standard Based on BERT-TextCNN

In recent years, the escalation in emergency occurrences has underscored the pressing need for expedient responses in delivering essential supplies. Efficient integration and precise allocation of emergency resources under joint government–enterprise stockpiling models are pivotal for enhancing emergency response effectiveness and minimizing economic repercussions. However, current research predominantly focuses on contract coordination and cost-sharing within these joint reserve modes, overlooking significant discrepancies in emergency supply classification standards between government and enterprise sectors, as well as the asymmetry in cross-sectoral and cross-regional supply information. This oversight critically impedes the timeliness and accuracy of emergency supply responses. In practice, manual judgment has been used to match the same materials under differing classification standards between government and enterprise reserves. Still, this approach is inefficient and prone to high error rates. To mitigate these challenges, this study proposes a methodology leveraging the BERT pre-trained language model and TextCNN neural network to establish a robust mapping relationship between these classification criteria. The approach involves abstracting textual representations of both taxonomical classes, generating comparable sentence vectors via average pooling, and calculating cosine similarity scores to facilitate precise classification mapping. Illustrated with China’s Classification and Coding of Emergency Supplies standards and Global Product Classification standards, empirical validation on annotated data demonstrates the BERT-TextCNN model’s exceptional accuracy of 98.22%, surpassing other neural network methodologies such as BERT-CNN, BERT-RNN, BERT-BiLSTM, etc. This underscores the potential of advanced neural network techniques in enhancing emergency supply management across diverse sectors and regions.

A Study on the Emergence of Sustainable Supply Chains and Response Types of Korean Seafood Exporters

A Study on the Emergence of Sustainable Supply Chains and Response Types of Korean Seafood Exporters

His unemployment, her response, and the moderating role of welfare policies in European countries. Results from a preregistered study.

Recent changes in labour markets have increased employment instability. Under these conditions, in male breadwinner families women might increase their labour supply when their male partners become unemployed. Previous studies have extensively investigated the role played by household and individual characteristics in explaining such increases in the labour supply of women. However, studies which examine the moderating role of specific welfare policies are missing. Our study contributes to the literature by investigating the moderating effect of childcare and tax-benefit policies for the labour supply response of women following the unemployment of their partner. We focus on a sample of 24 EU member states and the UK, during the period 2009-2019, combining longitudinal microdata from EU-SILC with country-period specific policy indicators generated with the use of the tax-benefit simulation model EUROMOD, UKMOD and country-period specific indicators of childcare use. We find that women indeed respond to men's unemployment by increasing their labour supply though the response is fairly weak. We also find the response is not restricted by having children at home or availability of public childcare and does not depend on the generosity of unemployment benefits. It is, however, negatively affected by marginal tax rates.

Modeling of the effect of transportation system accessibility on residential real estate prices: The case of Washington metropolitan area, USA

Deep learning accurate predictions of house prices are essential for prospective homeowners, investors, appraisers, and insurers. However, some studies lack accuracy as they overlook critical factors like accessibility and economic attributes that influence house prices. This paper aims to predict house prices by considering structural, locational, accessibility, and economic attributes, while also exploring the effect of accessibility on housing prices. The dataset contains 2,019,663 real estate transaction records from 1975 to 2018 in the Washington metropolitan area, obtained from the Zillow website. In this study, the accessibility index is calculated using Distance, Cumulative Opportunities, and Gravity measures, with the gravity measure surpassing others due to its consideration of both land use and transportation aspects. Economic attributes are then utilized to predict the average monthly house price using deep learning algorithms such as LSTM, GRU, and Simple RNN, with the Simple RNN demonstrating superior performance. Following the amalgamation of structural and locational attributes with the accessibility index and average house prices, various machine learning algorithms—including Linear Regression, Lasso, Ridge, Random Forest, GBM, LightGBM, XGBoost, Decision Tree, AdaBoost, Artificial Neural Network, and Stacked Generalization—are employed for prediction. Subsequent evaluation reveals that Stacked Generalization (ANN + LightGBM) provides the best performance, with an R-squared value of 0.96 and RMSE of $23,290. Moreover, this paper identifies accessibility index thresholds (80,003 for large buildings and 160,103 for small buildings) and demonstrates that a higher accessibility index leads to lower housing prices, attributed to noise pollution, decreased privacy, and increased supply responses.

Microbial and transcriptional response of Acropora valida and Turbinaria peltata to Vibrio coralliilyticus challenge: insights into corals disease resistance

BackgroundCoral diseases are significant drivers of global coral reef degradation, with pathogens dominated by Vibrio coralliilyticus playing a prominent role in the development of coral diseases. Coral phenotype, symbiotic microbial communities, and host transcriptional regulation have been well-established as factors involved in determining coral disease resistance, but the underlying mechanisms remain incompletely understood.MethodsThis study employs high-throughput sequencing to analyse the symbiotic microbial and transcriptional response of the hosts in order to evaluate the disease resistance of Acropora valida and Turbinaria peltata exposed to Vibrio coralliilyticus.ResultsA. valida exhibited pronounced bleaching and tissue loss within 7 h of pathogen infection, whereas T. peltata showed no signs of disease throughout the experiment. Microbial diversity analyses revealed that T. peltata had a more flexible microbial community and a higher relative abundance of potential beneficial bacteria compared to A. valida. Although Vibrio inoculation resulted in a more significant decrease in the Symbiodiniaceae density of A. valida compared to that of T. peltata, it did not lead to recombination of the coral host and Symbiodiniaceae in either coral species. RNA-seq analysis revealed that the interspecific differences in the transcriptional regulation of hosts after Vibrio inoculation. Differentially expressed genes in A. valida were mainly enriched in the pathways associated with energy supply and immune response, such as G protein-coupled receptor signaling, toll-like receptor signaling, regulation of TOR signaling, while these genes in T. peltata were mainly involved in the pathway related to immune homeostasis and ion transport, such as JAK-STAT signaling pathway and regulation of ion transport.ConclusionsPathogenic challenges elicit different microbial and transcriptional shifts across coral species. This study offers novel insights into molecular mechanisms of coral resistance to disease.

Exploring non-price factors shaping supply response: insights from Cameroon's banana and pineapple horticultural industries

Horticulture has the potential to meet the development agenda of agrarian economies, like that of Cameroon, through the cultivation of high-value fruits and vegetables. Bananas and pineapples are two widely grown fruits in Cameroon for income, employment, and foreign earnings. Cameroon remains an important global player in the banana trade. To boost production, identifying important factors that drive the supply response of such crops is an important policy question. Here, we ask if non-price factors are important determinants of supply response of such horticultural crops, a question that has received very little attention. The objective of this study is thus to estimate the effect of non-price factors on the supply response of bananas and pineapples. To do this, a Nerlovian response function is directly estimated via an Error correction model using time series data, to capture long-run dynamics of production and supply. The results show that non-price factors such as rainfall, temperature, and land are the major drivers of the supply response of both crops. The effects of these factors, however, vary with the crops. We provide plausible explanations why non-price factors are salient. Our results suggest that improving the timely availability of weather and climate information, and input subsidies are possible areas for policy interventions.

Coping with drug shortages: A study of government-enterprise option cooperation stockpiling strategies for drugs in shortage considering API surrogate stockpiling subsidies.

Drug shortage is a global problem, and the development of government-enterprise cooperative stockpiles of drugs in shortage, combining physical and production capacity, has become one of the most important means of coping with drug shortages. However, existing studies have tended to overlook the fact that shortages of Active Pharmaceutical Ingredients (APIs) have become an important constraint on production capacity stockpiling and that the lack of incentives and provisions for coordination of benefits have led to a double marginal effect of joint stockpiling by government and enterprises of drugs in shortage. Accordingly, this study introduced the option contract to the drug supply system composed of government and pharmaceutical enterprises and used the subsidy of API storage in lieu as an important initiative to incentivize the reserve of APIs, to construct a model of shortage drug reserve under the government's leadership. This study aims to improve the effect of government-enterprise joint stockpiling of drugs in shortage, which is of great theoretical and practical significance. According to the classification of production license types of pharmaceutical enterprises, this study established a three-level supply chain decentralized decision-making model consisting of the government, formulation enterprises, and API enterprises, and a two-level supply chain centralized decision-making model consisting of the government and API Formulation (API-F) integrated enterprises, respectively. By solving the inverse order derivation, the government-enterprise option cooperation conditions and optimal decision-making strategy were derived. The study results showed that: (i) The addition of enterprise API stockpiling mode can help the government conventional reserves, and enterprise production capacity reserves, broaden the way of drug reserves, and improve the effect of government-enterprise option cooperation; (ii) when the probability of drug shortages is high, the government should prefer the cooperation of API-F integrated enterprises, which is conducive to reducing intermediate links and government costs and improving the supply responsiveness to shortages of medicines; (iii) Setting appropriate government subsidies for API storage can incentivize enterprises to stockpile APIs and improve drug production capacity and physical supply response capability. This study took the problem of socialized stockpiling of drugs in shortage as an entry point and explored the problems and solution strategies in the government-enterprise cooperative stockpiling of drugs in shortage, which not only made some theoretical contributions to the application of options contract in the government-enterprise cooperative stockpiling of drugs in shortage but also provided new ideas and theoretical basis for the improvement of the stockpiling work of drugs in shortage.

Towards sustainable regional energy solutions: An optimized operational model for integrated energy systems with price-responsive planning

With dynamic changes in the energy market and continuous advances in smart energy technology, regional integrated energy systems (RIESs) have emerged as a vital direction in the evolution of energy systems. They are increasingly gaining significance in the realm of energy supply (ES) and demand response initiatives. In this context, this article introduces a novel optimal operational model for an integrated energy system (IES) that incorporates energy price responsiveness. The paper commences by delivering a comprehensive overview of the typical structure of an IES, presenting detailed models for each system module, encompassing the electrical energy supplier, heating, and cooling components. The proposed system model comprises three distinct subsystems, each catering to specific energy requirements. The primary emphasis is on devising an efficient planning scheme tailored to the energy consumption patterns and operational aspects of the IES. Through the presented model, there is substantial potential for significantly reducing the overall system cost without inducing a noteworthy upsurge in environmental pollution. Moreover, the energy efficiency of the system can experience considerable enhancement. The desired optimization problem has been solved using the proposed multi-objective Horse Herd Optimization Algorithm (MOHHOA). Additionally, in this strategy, Pareto front and fuzzy selection are employed to make better decisions among all Pareto solutions. The optimization strategy devised in this research not only enables the integrated operation of the IES but also ensures its compatibility with ongoing energy development initiatives. The proposed method yields a diverse set of Pareto solutions across the objective space, providing various trade-offs between economic, environmental, and reliability considerations. Utilizing MOHHOA, the algorithm efficiently balances exploration and exploitation during optimization, resulting in informed decision-making. In optimal planning, Scenario 2 exhibits lower operational costs (8.2 % reduction) and a dramatic improvement in LESP (1.24 %–1.176 %) compared to Scenario 1. Sensitivity analysis reveals an 11.2 % increase in environmental costs in Scenario 1 with a 36 % rise in electricity prices. Conversely, in Scenario 2, a 10 % reduction in natural gas prices leads to a 24.5 % increase in system running costs. These findings underscore the significance of considering energy price fluctuations for optimizing integrated energy system performance.

Supply response of major oilseeds in India: A mix of price and non-price factors

Supply response of major oilseeds in India: A mix of price and non-price factors

Design of a reliable electrical photovoltaic generator based on power converters control

This work proposes a renewable energy generation system that operates with a similar behavior as a synchronous generator in terms of reliability in the power supply and inertial response properties against power changes and grid voltage disturbances. The main contributions of this work are: (1) the renewable energy variability managing by means of a battery energy storage strategy, whose charge and discharge are determined by a forecasted-based power adjustment algorithm, (2) the dynamical modeling of an inverter that includes physical inertia and its corresponding response to power and voltage variations, and (3) the synthesis of a nonlinear optimal control for the inertia-based inverter system where the reactive power injection is regulated. Simulation results for a photovoltaic-based generator are presented to demonstrate the effectiveness of the proposed methodologies.

Take-up and labor supply responses to disability insurance earnings limits

In most disability insurance programs beneficiaries lose some or all of their benefits if they earn above an earnings threshold. While intended to screen out applicants with high remaining working capacity, earnings limits can also distort the labor supply of beneficiaries. We use a reduction in the earnings limit in Hungary to evaluate this trade-off and examine screening and labor supply responses. We find that the policy changed selection into the program modestly but reduced labor supply on the intensive margin significantly. These findings suggest that the earnings threshold should be higher.

Liberalization vis-à-vis non-liberalization trade policy: Exploring the impact of price volatility on producer share price and cocoa supply response in Nigeria and Ghana

Cocoa producers respond differently to volatile price shocks, but the nature of these responses remains unknown, especially in the liberalized and non-liberalized markets in Nigeria and Ghana, respectively. Therefore, we assess the extent to which price volatility affects the supply of cocoa while also analyzing the effect of price volatility on Nigeria's cocoa producer price share vis-à-vis Ghana's cocoa producer price share. We further analyze how producers react given the asymmetric nature of price volatility in Nigeria and Ghana. Annual secondary data were obtained from the World Development Index, National Bureau of Statistics, International Cocoa Organization, Central Bank of Ghana, Nigeria, and so on, from 1970 to 2019. We used the Ordinary Least Squares method, generalized autoregressive conditional heteroskedastic (GARCH) model, extensions, and the Vector Error Correction Model (VECM) for this study's analysis. Our results show the presence of volatility in price series and that volatility is asymmetric in nature. The results of the supply response show that price volatility has no significant relationship with cocoa supply in Ghana. In contrast, price volatility has a significantly positive relationship with the supply of cocoa in Nigeria at the 1 % level. The results of the VECM show that, in the long run, the cocoa producer price in Ghana will be negatively affected by both international price volatility and inflation rates at 5 % and 1 %, respectively. We suggest that cocoa farmers should have licensing to sell commodities to the international market directly without interference from the marketing board.

Coordinated Operation Strategy for Equitable Aggregation in Virtual Power Plant Clusters with Electric Heat Demand Response Considered

To tackle the variability of distributed renewable energy (DRE) and the timing differences in load demand, this paper perfects the integrated layout of “source-load-storage” energy control in virtual power plants (VPPs). Introducing a comprehensive control approach for VPPs of varying ownerships, and encompassing load aggregators (LAs), a robust and cost-efficient operation strategy is proposed for VPP clusters. Initially, the influence of real-time electricity prices on cluster energy utilization is taken into account. Flexible shared electricity prices are formulated cluster-wide, based on the buying and selling data reported by each VPP, and are distributed equitably across the cluster. Following this, a flexible supply and demand response mechanism is established. With the goal of minimizing operational costs, this strategy responds to demand (DR) on the end-user side, instituting shifts and reductions in electricity and heat loads based on electricity and heat load forecasting data. On the supply side, optimization strategies are developed for gas turbines, residual heat boilers, and ground-source heat pumps to restrict power output, thus achieving economical and low-carbon cluster operations. Finally, the efficacy of the proposed optimization strategy is demonstrated through tackling numerous scenario comparisons. The results showcase that the proposed strategy diminishes operational costs and carbon emissions within the cluster by 11.7% and 5.29%, respectively, correlating to the unoptimized scenario.

SPOUSAL LABOR SUPPLY, CAREGIVING, AND THE VALUE OF DISABILITY INSURANCE

AbstractThis article evaluates the insurance value of the Social Security Disability Insurance (SSDI) program among married households when wives face a trade‐off between market hours and spousal care following their husbands' disability. Event study analyses show that wives' labor supply responses to their husbands' disability are small, and instead, a considerable amount of time is spent in spousal care. Using a dynamic structural model, I find that incorporating time loss due to spousal care increases the insurance value of SSDI relative to its costs. Finally, budget‐neutral policy reforms that subsidize the cost of care can improve social welfare.

Housing prices, costs, and policy: The housing supply equation in Ireland since 1970

AbstractThis article examines the responsiveness of new housing supply to prices and costs, using the case of Ireland at quarterly frequency from the 1970s, as well as a county‐level panel from the 1990s. Across four error‐correction specifications, and supported by an instrumental variables approach, we find the estimated elasticity of new housing supply to prices of +0.9 in the baseline, while that of costs is larger in magnitude (−1.9). We present evidence that responsiveness to prices rose after the 1980s, then fell in the 2000s, before rising again and also that elasticities vary at the county level.

A Panel Data Analysis of Antidumping Duties in Seafood Trade: A Gravity Model Approach

ABSTRACT This study uses a panel of monthly data to investigate the effects of antidumping (AD) duties imposed on shrimp imports to the U.S. The results from the augmented gravity model show that initiating AD investigations and the final AD duty rate harm trade with the named countries. Distribution of AD duties among domestic industry producers stimulates a positive supply response. Rejection of imports by European countries for food safety reasons deflects trade to the U.S. The pass-through effects of the AD duty rate (and exchange rate) on import prices are small, indicating minimal adverse effects of AD policy on consumer welfare.

Enhancing resilience in transnational E-commerce supply chains: Critical factors, perspectives and strategic action plan

This study develops a hybrid model to investigate the factors affecting transnational e-commerce supply chain resilience (TNSCRE) by integrating the Entropy Weight Method (EWM), Simple Additive Weighting (SAW), and Interpretive Structural Modeling (ISM). The study identifies 36 critical factors categorized under supply chain adaptability, supply chain efficiency, and supply chain evolution, and five criteria are used to rank these factors. The EWM is used to calculate the relative weights of the criteria, and the SAW method is used to rank the factors based on their weighted scores. The ISM is then used to evaluate the interrelationships among the key factors. The research highlights the significance of several factors, such as the speed of supply chain disruption recovery, interactive collaboration, and response time to supply chain disruption. Sensitivity analysis was performed to assess the robustness of the findings. Finally, a SWOT analysis is conducted to develop a strategic action plan for addressing these significant factors. The study provides a comprehensive understanding of the factors that impact TNSCRE from the perspective of multiple stakeholders. The findings can help e-commerce business owners improve their existing supply chain resilience and achieve sustainable growth in the context of globalization.

When Nurses Travel: Labor Supply Responses to Peak Demand for Nurses

Abstract We study how a market uses temporary workers to accommodate extraordinary demand shocks. When COVID-19 surges, hospitals need additional nurses—especially in specialties central to COVID-19 care. By comparing markets for COVID-relevant and other specialties, we show that the market for travel nurses expands dramatically and estimate travel nurse labor supply across space. Supply is quite elastic, as workers can choose to travel where they are needed. Workers travel longer distances to temporary jobs when payment increases, suggesting that an integrated national market facilitates reallocation when demand spikes. But when national cases peak, travel distance is less responsive to local demand.