Plant Shutdown Research Articles

Understanding the Social Value of Geelong’s Design and Manufacturing Heritage for Extended Reality

Post-industrial cities often find themselves at a crossroads as to whether to find a new identity or embrace their industrial past. In late 2017, after the closure of major manufacturing plants in the region, the Australian city of Geelong was designated a UNESCO City of Design and embraced a “Clever and Creative” strategy which acknowledged Geelong’s industrial and design past in responding to contemporary technological, demographic, and economic challenges. However, questions remain as to which versions of the past are valued by the local community and how these stories can be shared. To better understand the social value of design and manufacturing heritage in Geelong as well as to get initial feedback on how to interpret this type of heritage through novel immersive extended reality (XR) experiences, the researchers took a community-led approach. This paper reports on the results of the initial online community surveys (N = 55–137) and in-person stakeholder interviews (N = 5) with carefully selected representatives of the local government, education, heritage, tourism, and engineering sectors. The study’s outcome demonstrates the importance of design and manufacturing heritage for the local community’s identity. Moreover, this type of heritage provides a source of inspiration, learning opportunities for future creative problem-solvers, and economic opportunities through tourism. By engaging with the social value of design and manufacturing heritage, this paper argues that more effective and targeted storytelling, game-like applications, and other digital immersive experiences such as extended reality (XR) can be used to better engage with audiences.

Geomechanical analysis of the geothermal reservoir at San Emidio, Nevada

The WHOLESCALE (Water and Hole Observations Leverage Effective Stress Calculations and Lessen Expenses) project is aiming to simulate the spatial distribution and temporal evolution of stress throughout the geothermal system at San Emidio, Nevada, United States, via a thermo-hydro-mechanical reservoir model. Focal mechanisms for microseismic events during a temporary shutdown of the geothermal power plant in 2016 were analyzed through linear stress-inversion methods to infer the in-situ reservoir stress state. This analysis was supplemented by other geophysical and geological data, including focal mechanisms from regional earthquakes, slickenlines on exposed fracture surfaces, wellbore stress indicators observed in the surrounding region, and secular strain rate measurements. From the inferences of in-situ reservoir stress, 78 different realizations of stress models were generated over reasonable ranges for the values of maximum compressive horizontal stress (SHmax) azimuth and ratios of principal stress magnitudes. Evaluation of slip tendencies on fault planes determined for the microseismic events for each realization of the initial stress model suggests the reservoir stress state as transtensional with an SHmax azimuth between N and N30∘E.

The relationship between economic and political factors and the development of the manufacturing industry

With the development of global economy, people can often see many foreign products, which can not be separated from the development of national politics, economy, and there is an excellent general environment. The development of the manufacturing industry is crucial to the economic and political development of a country, through the analysis of the economic, political and Covid-19 perspectives on the development of the manufacturing industry. Many manufacturing industries are facing the possibility of bankruptcy under the influence of Covid-19. Firstly, this paper investigates that economic development and political measures have different degrees of impact on the manufacturing industry through extensive data analysis. Secondly, By analyse the impact of the global spread of coronavirus on the manufacturing industry, such as the decline in the quality of raw materials leading to a lack of market demand and the increased risk of plant closures. Businesses, oversupply. In the face of the Covid-19, regionalization and digitalization trends, a three-step countermeasure is proposed to help the manufacturing industry recover from a macro perspective and to better assist the subsequent transformation and upgrading of the manufacturing industry.

"The impact of unemployment on cognitive, affective, and eudaimonic well-being facets: Investigating immediate effects and short-term adaptation": Correction.

Reports an error in "The impact of unemployment on cognitive, affective, and eudaimonic well-being facets: Investigating immediate effects and short-term adaptation" by Mario Lawes, Clemens Hetschko, Ronnie Schöb, Gesine Stephan and Michael Eid (Journal of Personality and Social Psychology, Advanced Online Publication, Apr 04, 2022, np). In the original article, the letter "M" in "M1" and "M2" throughout should not be italicized. The word "occurred" is corrected to "occurred" and the word "occurring" is corrected to "occurring" in several places throughout. The acronym LCS in Figure 1 note is corrected to latent change score model. The average immediate effect on life satisfaction that appears in the first sentence of the Cognitive Well-Being section is -4.74. The second sentence of the second paragraph in the Cognitive Well-Being section should appear as Luhman et al. (2014), for example, reported that life satisfaction dropped by 4.1 p.p. The third paragraph in the Cognitive Well-Being section should appear as Moreover, the effects can be compared to international panel studies. Variable names in Figures 2 and 3 notes should appear italicized. All versions of this article have been corrected. (The following abstract of the original article appeared in record 2022-47585-001). While long-lasting declines in life satisfaction following unemployment have been well documented, evidence on the impact of unemployment on affective and eudaimonic well-being is scarce. Moreover, most existing studies relied on yearly panel data and were unable to separate the immediate effects of entering unemployment from prospective effects occurring before individuals become unemployed. The present study identified the immediate effects of entering unemployment on cognitive, affective and eudaimonic well-being facets using a control-group design based on monthly panel data of initially employed German jobseekers who were at high risk of losing their job. In order to investigate patterns of short-term adaptation, the study further examined whether average well-being levels change within the first months of unemployment using a mixed-effects trait-state-occasion model. All effects were separately computed for jobseekers affected by mass-layoffs or plant closures and individuals who registered as jobseekers due to other reasons. Multi-item instruments and experience sampling were used to validly measure the various well-being facets. The results indicate that life satisfaction and income satisfaction significantly decreased for individuals affected by mass-layoffs or plant closures from the last month in employment to the first month in unemployment. For individuals who registered as jobseekers due to other reasons, these effects were smaller and not significant in the case of life satisfaction. Crucially, there were no immediate effects of entering unemployment on the examined affective and eudaimonic well-being facets. Moreover, well-being levels were generally stable within the first months of unemployment indicating a general absence of short-term adaptation. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

The impact of unemployment on cognitive, affective, and eudaimonic well-being facets: Investigating immediate effects and short-term adaptation.

[Correction Notice: An Erratum for this article was reported online in Journal of Personality and Social Psychology on Jun 02 2022 (see record 2022-66262-001). In the original article, the letter "M" in "M1" and "M2" throughout should not be italicized. The word "occurred" is corrected to "occurred" and the word "occurring" is corrected to "occurring" in several places throughout. The acronym LCS in Figure 1 note is corrected to latent change score model. The average immediate effect on life satisfaction that appears in the first sentence of the Cognitive Well-Being section is -4.74. The second sentence of the second paragraph in the Cognitive Well-Being section should appear as Luhman et al. (2014), for example, reported that life satisfaction dropped by 4.1 p.p. The third paragraph in the Cognitive Well-Being section should appear as Moreover, the effects can be compared to international panel studies. Variable names in Figures 2 and 3 notes should appear italicized. All versions of this article have been corrected.] While long-lasting declines in life satisfaction following unemployment have been well documented, evidence on the impact of unemployment on affective and eudaimonic well-being is scarce. Moreover, most existing studies relied on yearly panel data and were unable to separate the immediate effects of entering unemployment from prospective effects occurring before individuals become unemployed. The present study identified the immediate effects of entering unemployment on cognitive, affective and eudaimonic well-being facets using a control-group design based on monthly panel data of initially employed German jobseekers who were at high risk of losing their job. In order to investigate patterns of short-term adaptation, the study further examined whether average well-being levels change within the first months of unemployment using a mixed-effects trait-state-occasion model. All effects were separately computed for jobseekers affected by mass-layoffs or plant closures and individuals who registered as jobseekers due to other reasons. Multi-item instruments and experience sampling were used to validly measure the various well-being facets. The results indicate that life satisfaction and income satisfaction significantly decreased for individuals affected by mass-layoffs or plant closures from the last month in employment to the first month in unemployment. For individuals who registered as jobseekers due to other reasons, these effects were smaller and not significant in the case of life satisfaction. Crucially, there were no immediate effects of entering unemployment on the examined affective and eudaimonic well-being facets. Moreover, well-being levels were generally stable within the first months of unemployment indicating a general absence of short-term adaptation. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Statistical Test-Based Practical Methods for Detection and Quantification of Stiction in Control Valves

Control valve, affected by stiction, causes closed-loop signals to experience oscillations, which ultimately leads to a decrease in product quality, reduced plant throughput, and increased environmental footprint. Therefore, it is indispensable to detect and quantify stiction in control valves. To accomplish this objective, in the present work, four noninvasive practical and simple methods are developed with the help of statistical tests such as F-test, t-test (Student’s t-test), modified Hotelling T2-test, and reverse arrangement test (RAT). The developed methods are applied to benchmark control loops espoused from chemical, paper, and mining industries. The results of the proposed methods are compared with that of existing methods found in the literature. It is found that the t-test-based method, the modified Hotelling T2-test-based method, and the RAT-based method demonstrate equally good or better performance than the existing methods, while the F-test-based method outperforms some of the existing methods. In addition to detecting stiction, the proposed methods can quantify stiction to timely notify panel operators of stiction severity and assist plant maintenance engineers to arrange plant shutdowns well ahead in time. The proposed methods are applicable to all types of control loops except level loops.

Stem girdling enhances ABA-induced stomatal closure of phosphorus-deprived soybean plants

To investigate whether shoot-to-root communication modulates physiological (leaf water relations and growth), phytohormonal and transcriptomic responses to phosphorus (P) deprivation, soybean (Glycine max L. Merr.) plants received a factorial combination of low P conditions and girdling. Stem phloem tissue was surgically excised from the first internode between the cotyledonary and the first unifoliate leaf, immediately before imposing different P treatments (250 and 5 μM P in hydroponics). Root and leaf expression of genes involved in P homeostasis, sucrose metabolism and transporters, starch metabolism, hormone homeostasis and ABA signalling were analysed, to determine their regulation and relationships to tissue P / ABA concentrations. P deprivation mainly upregulated root and leaf P homeostasis gene expression only in intact plants, acting to maintain foliar P homeostasis. Although girdling suppressed root expression of these genes, it increased root P concentrations and decreased leaf P concentrations. Initially, P deprivation decreased stomatal conductance before leaf water status decreased, irrespective of girdling. Later, stomatal closure of girdled P-deprived plants was greater than intact P-deprived plants at the same, lower leaf water status, coincident with enhanced foliar ABA accumulation and expression of ABA biosynthesis genes. In contrast, P deprivation decreased foliar concentrations of the antitranspirant jasmonic acid and increased root and leaf SA concentrations at the end of the experiment. P deprivation also decreased foliar cytokinin and gibberellin concentrations before leaf growth was inhibited and leaf water status declined, suggesting non-hydraulic growth regulation. Girdling and P deprivation increased foliar sucrose and hexoses, corresponding to increased sucrose invertase and transporter gene expression in the leaves, while decreasing root sucrose and hexoses concentrations and downregulating sucrose metabolism but increasing transporter gene expression. Girdling perturbs multiple root and shoot phytohormonal responses that modulate physiological adaptation to P deprivation.

Demand response for frequency regulation with neural network load controller under high intermittency photovoltaic systems

The rate of change of frequency (ROCOF) has become a key parameter to be monitored under high penetration of renewable energy. Any significant ROCOF should be mitigated immediately to avoid any shutdown of power plants and hence power interruptions to the customers. However, ROCOF is found to be significant and often in a region near to equatorial line because the power output of PV is highly intermittent due to a large number of passing clouds. Demand response (DR) is one of the most cost-effective means for mitigating any high ROCOF through controlling heating elements, refrigerators, and air-conditioners. However, most of the DR controllers use pre-determined conditions, also known as the condition-based approach, to switch the loads for reducing frequency changes. This approach may not be effective enough to respond to a new load condition. Furthermore, many DR controllers, including those accompanied by machine learning, are mainly developed to mitigate frequency changes with little focus on the mitigation of high ROCOF. Hence, an artificial neural network (ANN)-based controller is proposed in this article for frequency regulation with auto corrective efforts on high ROCOF under high intermittency of PV systems. The proposed controller is designed to manage several controllable loads on a grid emulator with PV systems at Universiti Tunku Abdul Rahman, Malaysia. It is shown that the proposed controller can reduce the frequency deviation by 23% and improve ROCOF by 19.7% as compared to that without any controller.

City-scale analysis of annual ambient PM2.5 source contributions with the InMAP reduced-complexity air quality model: a case study of Madison, Wisconsin

Air pollution is highly variable, such that source contributions to air pollution can vary even within a single city. However, few tools exist to support city-scale air quality analyses, including impacts of energy system changes. We present a methodology that utilizes regional ground-based monitor measurements to scale speciation data from the Intervention Model for Air Pollution (InMAP), a national-scale reduced-complexity model. InMAP, like all air quality models, has biases in its concentration estimates; these biases may be pronounced when examining a single city. We apply the bias correction methodology to Madison, Wisconsin and estimate the relative contributions of sources to annual-average fine particulate matter (PM2.5), as well as the impacts of coal power plant retirements and electric vehicle (EV) adoption. We find that the largest contributors to ambient PM2.5 concentrations in Madison are on-road transportation, contributing 21% of total PM2.5; non-point sources, 16%; and electricity generating units, 14%. State-wide coal power plant closures from 2014 to 2020 and planned closures through 2025 were modeled to assess air quality benefits. The largest relative reductions are seen in areas north of Milwaukee (up to 7%), though population-weighted PM2.5 was reduced by only 3.8% across the state. EV adoption scenarios lead to a relative reduction in PM2.5 over Madison of 0.5% to 13.7% or a 9.3% reduction in total PM2.5 from a total replacement of light-duty vehicles (LDVs) with EVs. Similar percent reductions are calculated for population-weighted concentrations over Madison. Replacing 100% of LDVs with EVs reduced CO2 emissions by over 50%, highlighting the potential benefits of EVs to both climate and air quality. This work illustrates the potential of combining data from models and monitors to inform city-scale air quality analyses, supporting local decision-makers working to reduce air pollution and improve public health.

A corrosion and tribo-failure analysis of Ni-P-Cu coated mild steel (AISI-1040) at varied copper concentration

Mild steel considers the key structural ingredient for manufacturing shell and tube heat exchangers. Corrosion and tribo-failures, on the other hand, is a very crucial industrial problem that can even lead to plant shutdown. The present study thus focuses on utilising Electroless Ni-P-Cu coating on mild steel (AISI-1040) for improving its hardness, corrosion and wear resistance properties. The experiments are carried out varying the Cu concentration at 0 g/l, 0.2 g/l, 0.4 g/l, 0.6 g/l, 0.8 g/l, 1 g/l and 1.2 g/l in the electroless solution bath. The microstructure of the coating has been characterised using SEM and XRD analysis. Coating thickness is determined using FESEM, which has been analysed to be uniform. The corrosion failure analysis of the sample has been studied using Potentiodynamic polarization method. The Tafel and Nyquist Plot showcased a comparative corrosion resistance of the prepared samples. The wear resistance, on the other hand is analysed using a pin-on-disc tribometer depicting the tribo-failure study of the experiment. Both corrosion and tribological analysis proved the sample Ni-P-Cu-1 with a copper concentration 1 g/l to be the best-optimised concentration for the experiment. Moreover, Vickers’s microhardness of the coating with respect to mild steel specimen shows an increment of 40–70 %. The study can be readily scaled up by analysing the application on an industrial shell and tube heat exchangers; thus will be helpful for engineers and industrialists of the related field.

The challenge of just transition in China’s coal power sector: a city-level employment vulnerability assessment

ABSTRACT China’s target to achieve carbon neutrality by 2060 entails the phase-out of high-emissions coal power. However, a just transition policy must be implemented, given that coal power and its upstream coal mining industry provide many employment opportunities. Leveraging a bottom-up tabular analysis, we assessed the impact on employment of coal-fired power plant closures in China’s 330 prefecture-level cities. We identify vulnerable areas for employment in the transition and propose a customized employment incentive policy through a vulnerability assessment framework. Results show that in 2020, the direct employment in the coal power industry was 1.68 million, among which 16.76% will be affected by the 2045 net-zero deadline for the power sector. This number will increase to 36.90% if coal power capacity increases to 1300GW by 2030. However, 92% of Chinese cities will not suffer from unemployment risks since cities with high employment vulnerability are mostly concentrated in coal resource-based cities like Shuozhou (Shanxi Province), Huainan (Anhui Province), and Yulin (Shaanxi Province). In addition, the contraction of China's coal power-related employment will emerge only after 2035; a transition management framework focusing on highly vulnerable areas should be established as soon as possible to protect the well-being of affected workers and facilitate a just transition. Key policy insights New coal power projects should be cut back as much as possible, and instead the service life of incumbent coal power units should be extended where necessary. If no new coal power plants are built after 2020, only 16.76% of existing employment will be affected by 2045, but the share would double if new units were added. In order to effectively manage a just transition, it is necessary to plan early and establish a comprehensive policy system that takes regional differences fully into account.

RELIABILITY OF WATER CONTENT DATA FOR NATURAL GAS-HYDRATE SYSTEMS USING SEMI-EMPIRICAL CORRELATIONS

Water in natural gas can result in various operational problems, which may lead to equipment failure and plant shutdown. Knowing the amount of water capable of condensing from natural gas is essential. Many methods have been developed for ascertaining the amount of this condensable water (water content) from many gas mixtures. However, when hydrates are present, available methods for estimating the amount of condensable water are scarce and very limited in the open literature. The reliability of the data has always been a cause for concern due to the tendency for the inaccuracy of the results. In this study, two semi-empirical methods for ascertaining the amount of condensable water in natural gas with and without hydrates were used to test the reliability of the water content data of four different published natural gas-hydrate systems, including methane and propane gas mixture, raw/unprocessed, binary (methane + water), and synthetic natural gas. The results showed that only the data set for the methane and propane gas mixture was a reliable gas-hydrate equilibrium system, while the synthetic gas mixture needed further validation. Therefore, the methodology in this study can be used as a quick and simple means for ascertaining the reliability of water content data of natural gas-hydrate systems.

Hazard and Operability Study (HAZOP) and Risk Analysis of Boiler Section of Egbin Power Plant Lagos

In this paper, the Hazard and Operability Analysis HAZOP) studies carried out on the boiler section of Egbin Power Plantto validate the hazard and safe operations of the plant are presented. The aim is to identify all the corrective measures to improve safety and to provide refresher training for the operating personnel as well as to look at different scenarios that may come up as production is going on. The methodology used in carrying out the Hazard and Operability Studies was by using a well-structured and systematic method such as the combination of relevant keywords and parameters/variables like flow, temperature, pressure, level, etc. which resulted in deviations. These deviations were caused byequipment malfunctions, operational problems, and other factor. These resulted in consequences thatlead to low power output. The consequences of any action are the risks that should be avoided for the plant to continue to run. To overcome these problems, a tentativeactionwas provided which would make the operator take immediate action to mitigate the problems while maintenance would be carried out to avoid plant shutdown.

Design, Development, and Validation of a Culture-Independent Nucleic Acid Diagnostics Method for the Rapid Detection and Quantification of the Burkholderia cepacia Complex in Water with an Equivalence to ISO/TS 12869:2019.

In the wake of a series of outbreaks of finished pharmaceutical product-related Burkholderia cepacia complex (Bcc) human infections worldwide, the United States Food and Drug Administration (FDA) in 2017, and subsequently in 2021, issued advisory notifications to the pharmaceutical industry for stringent Bcc testing requirements for pharmaceutical manufacturing processes and for finished pharmaceutical products prior to release to the marketplace. The advisory notifications highlight non-sterile aqueous finished pharmaceutical products as being a major culprit associated with many of these human infection events. As such, there has been a significant number of Bcc-contaminated finished product recalls resulting in company revenue losses, delayed finished product release, finished product shortages for patients, and manufacturing plant shutdowns coupled with company reputational damage. With many of the finished product recall events, pharmaceutical grade water and/or manufacturing facility water distribution systems were identified as the primary origin source of Bcc contamination. Testing and monitoring regimes currently employed to identify Bcc contamination of water associated with pharmaceutical manufacturing are often limited by costly, laborious, lengthy, and nonspecific traditional microbial culture-based methodologies. Presently FDA approved, European Conformity (CE) marked, and International Organization for Standardization (ISO) standard microbial culture-independent rapid, quantitative, specific, and sensitive nucleic acid diagnostics (NAD) methodologies are now gaining greater widespread acceptance in their routine usage in testing laboratories. Here we present the development of a rapid (<4 hours from sample in to result out) single test culture-independent Bcc NAD method, incorporating a quantitative real-time polymerase chain reaction (qPCR) assay. This method can be used for the detection and simultaneous identification of all 24 Bcc species currently assigned, directly from water samples. This culture-independent Bcc NAD method is validated to the testing method equivalent of the ISO/TS 12869:2019 standard, which is a widely used rapid culture-independent NAD method for detecting Gram-negative Legionella species in water.

Introduction to the special issue on mobility, climate change, and economic inequality

Introduction to the special issue on mobility, climate change, and economic inequality

The Unintended Consequences of Coal-fired Power Plant Closures: Evidence from China

The Unintended Consequences of Coal-fired Power Plant Closures: Evidence from China

Data driven-based model for predicting pump failures in the oil and gas industry

Equipment reliability is a critical aspect of the oil and gas industry because the failure of such equipment can lead to catastrophic outcomes on different levels. In these industries, the need for safe, accurate, and cost-effective equipment operation requires reliable failure estimation and identification in order to improve performance and ensure that the maintenance strategy is efficient and effective. Thus, failure prediction is vital in the oil and gas industries for extending part lifetime and reducing unexpected equipment failures, thereby avoiding costly plant shutdowns and equipment damage. This paper proposes a simple and easy-to-implement data-driven model based on multiple linear regression for predicting the failures of a seawater pump in the oil and gas industry. Real-world historical data from equipment and process sensors mounted on the selected pump is collected and analyzed to develop the proposed model. The factors used to build the proposed model have been identified through a review of the literature and expert interviews. In addition, the correlation between the input factors is investigated. The results revealed that the proposed model has the capability to predict pump failure with more than 97% accuracy. Furthermore, sensitivity analysis revealed that temperature and pressure are the most important factors influencing pump failure. The findings of the proposed model can assist maintenance managers and decision-makers in properly detecting and predicting failure. It also helps to monitor and control the input factor levels in order to prevent failures. This study contributes to the development of failure prediction alerts, which will serve as a maintenance decision support system for operatives to avoid potential incoming failures.

Retirement of US fossil fuel-fired power plants will increase water availability

Nearly two-thirds of fossil fuel-fired electricity generation capacity in the United States is expected to reach its typical end of life by 2035. While the closure of fossil fuel-fired power plants will help advance decarbonization goals, the cessation of water use for fossil fuel-fired power plant cooling - the largest water user in the US - will also impact the nation’s water resources. We assess when, where, and how much water will be made available upon the expected retirement of the nation’s nearly one thousand fossil fuel-fired power plants by combining a lifespan-based model of fossil fuel-fired generator retirements for the US fossil fuel-fired electricity generation fleet with a national-scale hydrologic model. We show that annual water withdrawals and consumption of fossil fuel-fired power generators will be significantly curtailed (85 % and 68 % reduction, respectively) by 2035 if these generators follow their typical retirement timeline. Most rivers with fossil fuel-fired power plants diverting and/or discharging water will have a net increase in annual streamflow after plant retirement (maximum decrease of 2 %, maximum increase of 57 % by 2050), with the most pronounced increases occurring in the summer months. The retirement of fossil fuel-fired power plants will lead to a large relative change (>5%) in streamflow at least one month per year by 2050 in 31 subbasins. The retirement of power generators was shown to produce noticeable streamflow impacts up to hundreds of kilometers downstream. By the retirement of the last US fossil fuel-fired power generator, 2.6 billion m3 of water that was once consumed by these power plants could be made available for other uses. In addition to the global benefits of reduced greenhouse gas emissions, the notable increases in streamflow and water availability in many US rivers due to the retirement of fossil fuel-fired power plants could benefit local water users and ecosystems.

Downsizing decisions: The joint influence of equity incentives and behavioral biases

AbstractAlthough new investment can be viewed as a decision to pursue projects from a wide number of growth opportunities with easily discernible (and presumably preferable) risk profiles, downsizing (e.g., through layoffs, plant closings, asset divestitures, etc.) is a dichotomous choice to either abandon or continue an existing project where the relative risk between these options is not clear. Our evidence suggests that vega in the pre‐downsizing period is associated with risky investment that necessitates future downsizing. We further find that contemporaneous vega is associated with a greater likelihood of downsizing. On the other hand, our evidence suggests that delta is a significant impediment to downsizing. We examine the influence of behavioral factors in the decision‐making process and find downsizing decisions are discouraged by managerial overconfidence but encouraged by managers’ aversion to ambiguity. Finally, we investigate whether equity incentives and behavioral factors lead to better downsizing decisions. We find that downsizing firms with high ambiguity perform better after downsizing relative to their matched pair with lower ambiguity.

Resilience of U.S. Cattle and Beef Sectors: Lessons from COVID-19

Abstract The upheaval wrought on the U.S. beef industry by the global COVID-19 pandemic carried with it several lessons that might help improve resiliency should there be a reoccurrence. First, the futures market for fed cattle fell well before cash prices, which sent a signal to market cattle early, and those who did so benefited. Second, the decline in futures anticipated the closure of slaughter plants and provided an opportunity to purchase and store beef primals in anticipation of future scarcity. Third, the beef industry has ways of slowing or stopping the pipeline of animals destined for feed yards and can “store” these animals in background feeding facilities or on pasture or rangeland. Producers who waited to sell feeder cattle benefited from higher feeder cattle prices once the processing facilities reopened. Fourth, cow slaughter plants responded to the pandemic and subsequent scarcity of labor much better than large fed-cattle plants. Cow plants are not as sophisticated and complex as fed-cattle plants. This relative simplicity may help explain the superior performance of these plants during the crisis. Sixth, the academic work on the value of building smaller plants as a response against concentration provides mixed results—these plants require more labor per animal and can be even more susceptible to labor scarcity. Seventh, the observed increase in boxed beef prices, even as fed cattle prices fell, demonstrates the risk-mitigating impact of producer ownership of downstream activities in the value chain.