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Federally funded Emergency Food Assistance Program (TEFAP) aims to improve nutrition equity through hunger relief setting. However, little is known about TEFAP disbursement method (choice, modified choice, and no choice) to pantries or the quality received by pantries. Food inventory data from 239 pantries in 2020 were used to assess the association between TEFAP quality and type of disbursement methods longitudinally. While no significant differences were observed in quality across disbursement types and months. Our study suggests there are tradeoffs across different methods. TEFAP for the most part is a healthy food source that should be maximized by food pantries.Copyright © 2023 Taylor & Francis Group, LLC.
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The supply chain networks that support a business have usually evolved over time, shaped by various market and supply forces and by the expectations and strategic intent of a series of leaders. Recent shocks and higher awareness of risk and shifts on both the demand and supply side are expected to require global networks to be reassessed. This chapter reviews some of the key changes impacting global chains and considers the implications for future supply chain networks and the people who will manage them. © Springer Nature Switzerland AG 2023. All rights reserved.
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This article analyzes the influence of ride-sourcing in reducing demand on public transportation systems among university students in the Metropolitan Region of Recife before and during the COVID-19 pandemic. The literature points out that, depending on the local context, the relationship between public transport and ride-sourcing can be one of competition or complementation. Because the pandemic's reality has had a significant impact on urban mobility, we sought to comprehend its implications in this context. The model chosen was logistic regression. A questionnaire via the web obtained 404 valid interviews. The results indicate that there was a reduction in the use of both modes during the pandemic, with the public system being considerably higher. The main reason for the use of public transport shifted from study to work, while in ride-sourcing it was no longer leisure. Higher education, the availability of a driving license, and higher income reduce the chances of using public transportation. Being formally employed and attending class personally positively influences the use of ride-sourcing. Public transportation was the most cited as a substitute in the case of unavailability of ride-sourcing and vice-versa. If ride-sharing transportation did not lead to the desired destination, public transportation was the preferred complementary mode. It was concluded that the effects of competition were stronger.
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During a public health crisis like the COVID-19 pandemic, a credible and easy-to-access information portal is highly desirable. It helps with disease prevention, public health planning, and misinformation mitigation. However, creating such an information portal is challenging because 1) domain expertise is required to identify and curate credible and intelligible content, 2) the information needs to be updated promptly in response to the fast-changing environment, and 3) the information should be easily accessible by the general public;which is particularly difficult when most people do not have the domain expertise about the crisis. In this paper, we presented an expert-sourcing framework and created Jennifer, an AI chatbot, which serves as a credible and easy-to-access information portal for individuals during the COVID-19 pandemic. Jennifer was created by a team of over 150 scientists and health professionals around the world, deployed in the real world and answered thousands of user questions about COVID-19. We evaluated Jennifer from two key stakeholders' perspectives, expert volunteers and information seekers. We first interviewed experts who contributed to the collaborative creation of Jennifer to learn about the challenges in the process and opportunities for future improvement. We then conducted an online experiment that examined Jennifer's effectiveness in supporting information seekers in locating COVID-19 information and gaining their trust. We share the key lessons learned and discuss design implications for building expert-sourced and AI-powered information portals, along with the risks and opportunities of misinformation mitigation and beyond. © 2023 Owner/Author.
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Supply chains have been severely disrupted globally due to the COVID-19 pandemic. The paper examined the strategic responses of automobile firms for meeting supply chain challenges they face post-pandemic. Data were collected using a specifically designed structured questionnaire from supply chain experts working with leading automobile manufacturing firms in India. The fuzzy analytic hierarchy process (FAHP), as a part of a multi-criteria decision-making model using R programming, was applied to identify and rank the choice of supply strategies using various criteria, such as lead time, logistics cost (holding cost, carrying cost, warehousing cost, handling cost), and the need of products. Two-wheeler and four-wheeler manufacturing firms were selected for the study. Logistics cost was found to be a dominant criterion, followed by a demand for products and lead time, which helped select an appropriate supply chain strategy. Buffering was observed to be the best strategic choice, and automation and robotics applications were the least preferred ones both for two-wheelers and four-wheeler manufacturing companies. The findings would be helpful to both practitioners and researchers in evaluating diverse strategic choices, especially under the risk and disruptions faced by business firms in the supply chain. © 2023, Associated Management Consultants Pvt. Ltd.. All rights reserved.
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Infectious diseases create a significant health and social burden globally and can lead to outbreaks and epidemics. Timely surveillance for infectious diseases is required to inform both short and long term public responses and health policies. Novel data inputs for infectious disease surveillance and public health decision making are emerging, accelerated by the COVID-19 pandemic. These include the use of technology-enabled physiological measurements, crowd sourcing, field experiments, and artificial intelligence (AI). These technologies may provide benefits in relation to improved timeliness and reduced resource requirements in comparison to traditional methods. In this review paper, we describe current and emerging data inputs being used for infectious disease surveillance and summarize key benefits and limitations.
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As the world opens up from the clutches of the pandemic to heightened demand for goods and services, businesses inextricably interconnected globally are coping to meet this demand due to worker shortages. In honor of Peter Keen, this editorial offers insight into how the quest for global talent can be addressed. Our work on how knowledge networking enables innovation through the creation of talent pools and the Global Capability Sourcing (GCS) model are combined to offer a view into addressing this challenge. The GCS explains why wages are declining for some skills while rising for others and asks: what role does a company most effectively play in the global sourcing economy? When workers are free to choose where and when they offer their services, the development imperative comes into effect. The development imperative is freedom of choice and can occur through innovation in talent pools stimulated through knowledge networking. When people have greater freedom and capabilities to improve their knowledge and skills, their incomes increase along with the range of choices and capabilities enjoyed by their households and governments. The papers in this issue add to what is known about how digital competency can be stimulated through investments in ICT training programs, how innovations take place in the development context and insights into conducting context-sensitive research. (PsycInfo Database Record (c) 2023 APA, all rights reserved)
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PurposeIn this paper, the authors introduce supply disruption ambiguity as the inability of a sourcing firm to attach probability point estimates to the occurrence of and to the magnitude of loss from supply disruptions. The authors drew on the "ambiguity in decision-making” literature to define this concept formally, connected it to relevant supply disruption information deficit, positioned it relative to supply chain risk assessment and hypothesized and tested its negative associations with both supply base ties and inventory turnover.Design/methodology/approachThe authors analysed survey data from 171 North American manufacturers and archival data for a subset (88 publicly listed) of these manufacturers via Ordinary Least Squares (OLS) estimation after ensuring that methodological concerns with survey research have been addressed. They used appropriate controls and employed the heteroskedasticity-based instrumental variable (HBIV) approach to ensure that inferences from our results are not unduly influenced by endogeneity.FindingsStrong supply base ties decrease supply disruption ambiguity, which, in turn, increases inventory turnover. Moreover, strong supply base ties and data integration with the supply base have indirect and positive effects on inventory turnover. As sourcing firms strengthen ties and integrate data exchange with their supply base, their inventory turnover improves from access to information relevant to detect and diagnose supply disruptions effectively.Originality/valueResearch on supply disruption management has paid more attention to the "disruption recovery” stage than to the "disruption discovery” stage. In this paper, the authors add novel insights regarding the recognition and diagnosis aspects of the "disruption discovery” stage. These novel insights reveal how and why sourcing firms reduce their overall ambiguity associated with detecting and assessing losses from supply disruptions through establishing strong ties with their supply base and how and why reducing such ambiguity improves inventory turnover performance.
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Over the past two decades, crowdsourcing activities have expanded considerably. More recently, the COVID-19 pandemic has radically changed the way people live and work, and the way organizations do business. So far, not many studies have analyzed if and to what extent trustworthiness can influence the admiration to practice crowdsourcing and could reward financial benefits in the COVID-19 period. Against this background, in this article, the aim is to investigate the influence of crowdfunding trustworthiness and financial rewards on the success of crowdsourcing activities. The analysis is made more complete by including technology leadership support as a moderator. With the help of the existing literature and theories, a research model has been developed conceptually, which was later validated using the partial least square-structural equation modeling technique on a sample of 319 responses from participants based in Europe and Asia. The study found that lucidity, gamification, exposure, and coordination along with financial rewards positively influence admiration for crowdsourcing, which, in turn, positively impacts successful crowdsourcing practices in the COVID-19 period. The study also shows that there is a significant moderating impact of technological leadership support on successful crowdsourcing practices in the COVID-19 period. IEEE
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In addition to equipment maintenance decisions, spare parts ordering decisions from different suppliers play a key role in reducing related costs (e.g., maintenance, inventory and ordering costs). Since suppliers may use different production technologies and materials, spare parts (or products) from different suppliers can be different in quality. Nevertheless, in recent studies, the quality of spare parts is rarely considered to incorporate both equipment maintenance and spare parts ordering. In this paper, we investigate the joint optimization of condition-based maintenance and spare parts provisioning policy under two suppliers with different product quality. We formulate a sequential-decision problem with a Markov decision process and consequently obtain an optimal maintenance and ordering policy by an exact value iteration algorithm. To improve computation efficiency, based on the principle of sequential optimization, we develop heuristic methods. Extensive numerical experiments are conducted to assess the overall performance of the developed heuristic methods. Compared to the optimal method, results showed that the average cost gap is about 2% and computation time is reduced by 94% on average under the proposed heuristic method. Note to Practitioners—This paper is motivated by the observation that automobile industries tried to integrate emergency suppliers from which spare parts have different quality into maintenance schedules to avoid stockout and reduce equipment failure during the Covid-19 pandemic. Specifically, the article focuses on balancing the trade-offs between condition-based maintenance and inventory management from two suppliers with different lead times and spare parts quality for multi-unit systems. On the one hand, effective maintenance scheduling relies on spare parts for replacement to ensure the stability of production. On the other hand, inventory management needs to select the supplier with appropriate lead time and product quality to reduce the ordering cost and avoid stockout based on the degradation states of equipment. The joint optimization of these two aspects serves to reduce the total maintenance and ordering cost. Nevertheless, most existing research aims to optimize them separately. In this paper, we formulate the joint decision problem considering the two aspects based on a Markov decision process. We obtain an optimal maintenance and ordering policy by an exact value iteration algorithm and present heuristics to improve the computation efficiency when the system contains multiple machines. Practitioners can implement the proposed methodology to make condition-based maintenance and inventory management when spare parts with different qualities are ordered from two suppliers. To balance cost and computational efficiency, it is suggested to implement the optimal policy by an exact value iteration algorithm when the number of machines is small in the system and use the heuristic methods when the number of machines is large (i.e., usually larger than 3). IEEE
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PurposeThis study aims to explore the challenges in implementing and sustaining lean in garment supplier factories and the buyer-supplier role in mitigating lean barriers in a typical situation and pandemic. Design/methodology/approachFollowing a qualitative research approach and multiple embedded case study method, data were collected through in-depth interviews with senior managers of one lead buyer and their four key garment supplier factories in Bangladesh. Within and cross-case analysis, techniques were applied to understand the context-oriented lean challenges and buyer-supplier role in mitigating the challenges. FindingsThe study findings demonstrate that garment suppliers are less prepared and unsystematic in lean implementation having limited capabilities and less preparation. Moreover, they have limited support from buyers, less commitment from top management and employee resistance to implementing lean. Lean challenges become more intense because of the COVID-19 pandemic. However, buyer-supplier responsible, cooperative and collaborative behaviour can mitigate lean challenges. Research limitations/implicationsWhereas many stakeholders may be responsible for lean challenges, this study explores dyadic role between buyer and supplier only based on a single lead buyer and their four suppliers. Hence future studies could consider more buyers and suppliers for a holistic understanding. Practical implicationsThis study could help buyers and suppliers understand the underlying causes of lean implementation challenges in garment supplier factories and their role in sustaining lean reducing the challenges, particularly in a pandemic. Originality/valueTo the best of the authors' knowledge, for the first time, this study depicts how buyer and supplier can play their due roles to mitigate lean challenges in garment supplier factories in a pandemic situation.
ABSTRACT
Recently, an increasing number of companies have encountered random production disruptions due to the COVID-19 pandemic. In this study, we investigate a two-stage supply chain in which a retailer can order products from a low-price ("cheap”) unreliable supplier (who may be subject to an uncertain production disruption and partially deliver the order) and an "expensive” reliable supplier at Stage 1 and a more "expensive” backup supplier at Stage 2. If the disruption happens, only the products that were produced before the disruption time can be obtained from the unreliable supplier. It is found that in the case with imperfect demand information updating, the unreliable supplier is always used while the reliable supplier can be abandoned. The time-dependent supply property of the unreliable supplier reduces the retailer's willingness of adopting the dual sourcing strategy at Stage 1, compared with the scenario with all-or-nothing supply. Different from the case with imperfect demand information updating, either the reliable or unreliable supplier can be abandoned in the case with perfect demand information updating. We derive the optimal ordering decisions and the conditions where single sourcing or dual sourcing is adopted at Stage 1. We conduct numerical experiments motivated by the sourcing problem of 3M Company in the US during the COVID-19 and observe that the unreliable supplier is more preferable when the demand uncertainty before or after the emergency order is higher. Interestingly, the retailer tends to order more from the unreliable supplier when the production disruption probability is larger in some cases. © 2022 The Author(s)
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The article provides an overview of the main steps in the development and the follow-up of the ISTROX pilot project developed within the Faculty of Linguistics, Philology, and Phonetics at the University of Oxford. Planned for 2018–2020, and extended to July 2021 in the context of the Covid pandemic, ISTROX aimed to prepare the ground for a larger envisaged project exploring the history of the Istro-Romanian language (vlaški and žejanski) and community. At the core of ISTROX is a previously unpublished body of sound recordings of IstroRomanian made in Istria during the 1960s by the Oxford linguist Tony Hurren and donated to the University in the 2000s by his wife, Vera Hurren. Part of the approach of ISTROX entailed initiating the online sourcing of linguistic information from the very small community of remaining speakers of ‘Istro-Romanian' worldwide. As the development of the project overlapped with the Covid pandemic, the ISTROX team had to redesign the relationship between the offline and the online elements of the project – a process which is being reoriented towards the offline in post-pandemic context. © 2022, Publishing House of the Romanian Academy. All rights reserved.
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Motivated by the trend of overseas/cross-regional firms returning to domestic/local and the background of COVID-19 normalization, a sourcing decision model is proposed based on the cost-signal game under the demand uncertainty and forecast inaccuracy. We explore the trade-off between the efficient cross-regional sourcing and responsive local sourcing. The results show that the sourcing decision depends on the linkage performances of cost and information. Cross-regional sourcing always brings mighty cost performance, while the local sourcing can not always give full play to information performance advantage. Because if both firms choose local sourcing, the correlation effect between forecast information will hedge signal accuracy effect. Greater demand uncertainty and more accurate cross-regional sourcing forecast are driving films to return. Interestingly, this return may benefit all the firms, and break the Prisoner's Dilemma of symmetric cross-regional sourcing. The reason is that the returning can alleviate competition by inducing a new equilibrium sourcing structure. In response, this mixed equilibrium endows firms with "follower advantage” to realize local-Pareto improvement. With the increase of demand uncertainty and forecast inaccuracy, this mixed equilibrium will turn to the symmetric local sourcing, which temporarily reaches the overall Pareto-optimum. However, it will eventually fall into the Prisoner's Dilemma of lose-lose situation. In addition, it is also found that the poor local sourcing forecast will endow firms with "mover advantage”, which will lead to the mover becoming better while the follower becoming worse. © 2022 Systems Engineering Society of China. All rights reserved.
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We evaluate an annotation schema for labeling logical fallacy types, originally developed for a crowd-sourcing annotation paradigm, now using an annotation paradigm of two trained linguist annotators. We apply the schema to a variety of different genres of text relating to the COVID-19 pandemic. Our linguist (as opposed to crowd-sourced) annotation of logical fallacies allows us to evaluate whether the annotation schema category labels are sufficiently clear and non-overlapping for both manual and, later, system assignment. We report inter-annotator agreement results over two annotation phases as well as a preliminary assessment of the corpus for training and testing a machine learning algorithm (Pattern-Exploiting Training) for fallacy detection and recognition. The agreement results and system performance underscore the challenging nature of this annotation task and suggest that the annotation schema and paradigm must be iteratively evaluated and refined in order to arrive at a set of annotation labels that can be reproduced by human annotators and, in turn, provide reliable training data for automatic detection and recognition systems. © European Language Resources Association (ELRA), licensed under CC-BY-NC-4.0.
ABSTRACT
Recently, an increasing number of companies have encountered random production disruptions due to the COVID-19 pandemic. In this study, we investigate a two-stage supply chain in which a retailer can order products from a low-price (“cheap”) unreliable supplier (who may be subject to an uncertain production disruption and partially deliver the order) and an “expensive” reliable supplier at Stage 1 and a more “expensive” backup supplier at Stage 2. If the disruption happens, only the products that were produced before the disruption time can be obtained from the unreliable supplier. It is found that in the case with imperfect demand information updating, the unreliable supplier is always used while the reliable supplier can be abandoned. The time-dependent supply property of the unreliable supplier reduces the retailer's willingness of adopting the dual sourcing strategy at Stage 1, compared with the scenario with all-or-nothing supply. Different from the case with imperfect demand information updating, either the reliable or unreliable supplier can be abandoned in the case with perfect demand information updating. We derive the optimal ordering decisions and the conditions where single sourcing or dual sourcing is adopted at Stage 1. We conduct numerical experiments motivated by the sourcing problem of 3M Company in the US during the COVID-19 and observe that the unreliable supplier is more preferable when the demand uncertainty before or after the emergency order is higher. Interestingly, the retailer tends to order more from the unreliable supplier when the production disruption probability is larger in some cases.
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Floods are the most commonly occurring natural disaster, with the Centre for Research on the Epidemiology of Disasters 2021 report on “The Non-COVID Year in Disasters” estimating economic losses worth over USD 51 million and over 6000 fatalities in 2020. The hydrodynamic models which are used for flood forecasting need to be evaluated and constrained using observations of water depth and extent. While remotely sensed estimates of these variables have already facilitated model evaluation, citizen sensing is emerging as a popular technique to complement real-time flood observations. However, its value for hydraulic model evaluation has not yet been demonstrated. This paper tests the use of crowd-sourced flood observations to quantitatively assess model performance for the first time. The observation set used for performance assessment consists of 32 distributed high water marks and wrack marks provided by the Clarence Valley Council for the 2013 flood event, whose timings of acquisition were unknown. Assuming that these provide information on the peak flow, maximum simulated water levels were compared at observation locations, to calibrate the channel roughness for the hydraulic model LISFLOOD-FP. For each realization of the model, absolute and relative simulation errors were quantified through the root mean squared error (RMSE) and the mean percentage difference (MPD). Similar information was extracted from 11 hydrometric gauges along the Clarence River and used to constrain the roughness parameter. The calibrated parameter values were identical for both data types and a mean RMSE value of ∼50 cm for peak flow simulation was obtained across all gauges. Results indicate that integrating uncertain flood observations from crowd-sourcing can indeed generate a useful dataset for hydraulic model calibration in ungauged catchments, despite the lack of associated timing information.
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This study attempts to present a contribution of Blockchain Technology (BC-T) in managing disruptions, and risk caused by the COVID-19 outbreaks and extending profound support in developing resilient Food Supply Chains (FSCs). The effects of the pandemic can be witnessed on global supply chains in their demand & supply side disruptions and in the changing patterns of consumer buying in the food industry. The assessment of the disruptive factors is required to explore the present issues and promising resilient strategies to impart robustness to the FSCs for mitigating disruptions in the future. An integrated approach of Fuzzy Analytic Hierarchy Process (FAHP) and Weighted Assessment Sum Product Assessment (WASPAS) is employed to assess the factors related to sourcing, lean, workforce, and flexibility, as well as evaluation of the BC-T enabled FSCs resilient strategies that mitigate the effect of disruption during the pandemic. The findings exhibit that ‘Sourcing related’ is the most affecting disruptive factor causing distress in the FSCs and ‘flexibility resilient strategy’ is the most relevant resilient strategy for BC-T enabled FSCs. The BC-T acts as a catalyst in enhancing the flexibility, traceability, and shorter supply chain network structure that may help the FSCs to mitigate risk and disruption in the pandemic situation. The BC-T helps the FSCs to control the demand and supply shocks, and supports the organization with real-time monitoring and sharing information. This study provides insights to the decision-makers, managers, and other stakeholders to take significant decisions during an emergency.
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Non-technical summary. As we consider a transition to a low-carbon future, there is a need to examine the mineral needs for this transformation at a scale reminiscent of the Green Revolution. The efficiency gains of the agrarian transition came at ecological and social costs that should provide important lessons about future metal sourcing. We present three options for a Mineral Revolution: status quo, incremental adaption and revolutionary change. We argue that a sustainable Mineral Revolution requires a paradigm shift that considers wellbeing as a purpose and focuses on preserving natural capital.Technical summary. As we consider a transition to a low-carbon future, there is a need to examine the mineral needs for this transformation at a scale reminiscent of the Green Revolution. The efficiency gains of the agrarian transition came at ecological and social costs that can also provide important lessons about the Mineral Revolution. We lay out some of the key ways in which such a mineral revolution can be delineated over temporal scales in a paradigm shift that considers wellbeing as a purpose and focuses on preserving natural capital. These prospects are conceptually presented as three pathways that consider the status quo, incremental adaption and revolutionary change as a means of planning more effectively for a low-carbon transition.Social media summary. Sourcing metals sustainably will require to consider wellbeing as a purpose and to preserve natural capital.
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The main aim of this paper is to explore sourcing as a business model that can be used by companies for obtaining competitive advantage over their rivals in a global environment. The strategic approach of sourcing has become an important capability for firms over the last 20 years as the international competition has intensified and given also the limited internal resources. This analysis approaches the worldwide necessity of identifying strategic sourcing relationships for creating new capabilities. A developed international sourcing based on partners/ suppliers was paramount for some companies to overpass the Covid-19's disruptions in production and supply of different products and to overcome their competitors. Although these companies were affected on short run, they showed a high shock absorption capacity and ability to recover quickly after the shock. In a nutshell, they were more resilient to external shocks, and they succeeded to overcome the difficulties through an agile business reaction. Based on available theoretical data on sourcing, this paper takes a step forward by sketching a practical guide allowing companies to understand if they need to source totally or partially their portfolio of products. Furthermore, for those companies to which the sourcing solution becomes a necessary strategic move, this paper provides a view on the process they should follow to obtain a competitive advantage.