Endogenous Disruption Research Articles

EOQ with supply disruptions under different advance information regimes

In this paper, we consider the impact of advanced delivery information on the performance of supply chains facing endogenous disruptions. We study a single-echelon EOQ-based inventory model with backorders where the supplier could fail to deliver shipments on time following a Bernoulli process, a measure of the supplier service quality. Two extreme advance information regimes are analyzed: (1) full delivery information (FDI), where the timing of the next delivery is always known, and (2) partial delivery information (PDI), where the timing of the next delivery is known if it coincides with the next planned delivery. For both regimes, we use a natural adaptation of the base-stock policy, having multiple order up-to levels, each corresponding to the level of available information when ordering. We then model the long-run average cost and determine the policy variables that minimize this cost. While the analysis of the FDI model proved straightforward, the PDI model involved the solution of a mixed-integer nonlinear optimization problem. We found closed-form solutions for both models. Numerical results show that, by reducing planning uncertainty, advanced information directly reduces operating costs. They also show that the cost of the case of full information is higher than that of the EOQ model, suggesting the importance of finding reliable suppliers for disruption-free operations.

Efficient Solution Methods for a General r-Interdiction Median Problem with Fortification

This study generalizes the r-interdiction median (RIM) problem with fortification to simultaneously consider two types of risks: probabilistic exogenous disruptions and endogenous disruptions caused by intentional attacks. We develop a bilevel programming model that includes a lower-level interdiction problem and a higher-level fortification problem to hedge against such risks. We then prove that the interdiction problem is supermodular and subsequently adopt the cuts associated with supermodularity to develop an efficient cutting-plane algorithm to achieve exact solutions. For the fortification problem, we adopt the logic-based Benders decomposition (LBBD) framework to take advantage of the two-level structure and the property that a facility should not be fortified if it is not attacked at the lower level. Numerical experiments show that the cutting-plane algorithm is more efficient than benchmark methods in the literature, especially when the problem size grows. Specifically, with regard to the solution quality, LBBD outperforms the greedy algorithm in the literature with an up-to 13.2% improvement in the total cost, and it is as good as or better than the tree-search implicit enumeration method. Summary of Contribution: This paper studies an r-interdiction median problem with fortification (RIMF) in a supply chain network that simultaneously considers two types of disruption risks: random disruptions that occur probabilistically and disruptions caused by intentional attacks. The problem is to determine the allocation of limited facility fortification resources to an existing network. It is modeled as a bilevel programming model combining a defender’s problem and an attacker’s problem, which generalizes the r-interdiction median problem with probabilistic fortification. This paper is suitable for IJOC in mainly two aspects: (1) The lower-level attacker’s interdiction problem is a challenging high-degree nonlinear model. In the literature, only a total enumeration method has been applied to solve a special case of this problem. By exploring the special structural property of the problem, namely, the supermodularity of the transportation cost function, we developed an exact cutting-plane method to solve the problem to its optimality. Extensive numerical studies were conducted. Hence, this paper fits in the intersection of operations research and computing. (2) We developed an efficient logic-based Benders decomposition algorithm to solve the higher-level defender’s fortification problem. Overall, this study generalizes several important problems in the literature, such as RIM, RIMF, and RIMF with probabilistic fortification (RIMF-p).

Crisis Map Design Considering Map Cognition

Crisis maps play a significant role in emergency responses. Users are challenged to interpret a map rapidly in emergencies, with limited visual information-processing resources and under time pressure. Therefore, cartographic techniques are required to facilitate their map cognition. In this study, we analyzed the exogenous and endogenous disruptions that users needed to overcome when they were reading maps. The analysis results suggested that cartographers’ taking the stressors into consideration could promote the cognitive fit between cartographers and users, improving map cognition and spatial information supply–demand matching. This paper also elaborates the course of map visual information processing and related graphic variables to visual attention attributes. To improve the users’ map cognition in time-critical emergency situations, crisis map design principles and a methodology were proposed. We developed three fire emergency rescue road maps and performed two evaluations to verify the effectiveness of the principles. Our experiments showed that the principles could effectively facilitate the users’ rapid map perception and proper understanding, by reducing their cognitive load, and could improve the quality of the crisis maps to some extent.

Improved GNSS Localization and Byzantine Detection in UAV Swarms.

Many tasks performed by swarms of unmanned aerial vehicles require localization. In many cases, the sensors that take part in the localization process suffer from inherent measurement errors. This problem is amplified when disruptions are added, either endogenously through Byzantine failures of agents within the swarm, or exogenously by some external source, such as a GNSS jammer. In this paper, we first introduce an improved localization method based on distance observation. Then, we devise schemes for detecting Byzantine agents, in scenarios of endogenous disruptions, and for detecting a disrupted area, in case the source of the problem is exogenous. Finally, we apply pool testing techniques to reduce the communication traffic and the computation time of our schemes. The optimal pool size should be chosen carefully, as very small or very large pools may impair the ability to identify the source/s of disruption. A set of simulated experiments demonstrates the effectiveness of our proposed methods, which enable reliable error estimation even amid disruptions. This work is the first, to the best of our knowledge, that embeds identification of endogenous and exogenous disruptions into the localization process.

Manufacturing in the Time of COVID-19: An Assessment of Barriers and Enablers

Pandemics and other forms of epidemic outbreaks are a unique case of manufacturing risk typified by high uncertainty, increasing propagation, and long-term disruption to manufacturers, supply chain actors as well as the end-users and consumers. For manufacturing the COVID-19 disruption scope has been largely twofold; an endogenous disruption of manufacturing processes and systems as well as extreme shifts in demand and supply caused by exogenous supply chain disruption. Existing literature on disruptions in manufacturing suggests that pandemics are qualitatively different from typical disruptions. There is no literature available to manufacturing practitioners that identify the barriers and enablers of manufacturing resilience, especially with regards to pivoting of the manufacturing sector in response to a pandemic. This article draws on an extensive survey collected during the COVID-19 pandemic. The respondents were employees of manufacturing firms in all regions of the world who had engaged in manufacturing during the pandemic or had opted out from manufacturing due to various identified reasons. By collating their responses, we offer to practitioners and policymakers an analysis for identifying a best-practice framework for pivoting successfully as a response to major manufacturing disruptions.

Identifying the precursors of vulnerability in agricultural value chains: A system dynamics approach

Conventional approaches for assessing supply chain vulnerability do not capture endogenous disruptions emanating from chain actors’ decisions that might increase value chain vulnerability. These approaches adopt a reactive analytical explanation of vulnerability, rather than one that considers issues of feedback effects. To address this issue, this paper adopts a system dynamics modelling approach to identify the precursors of vulnerabilities in Ghana’s cocoa value chain. The paper assesses the vulnerability levels of the cocoa value chain by adjusting the baseline values of several key parameters that can be influenced by chain actors. Results of the sensitivity analyses indicate that the precursors of vulnerability situated upstream of the cocoa value chain have varying impacts on chain vulnerability, but the same magnitude of effect on the vulnerability levels of chain actors. However, precursors of vulnerability that are situated midstream of the cocoa value chain have an unequal magnitude of effect on the vulnerability levels of chain actors. Results suggest that policies governing cocoa trading can become countervailing factors that obstruct the government’s call for upgrading along the cocoa value chain. The system dynamics model presented here enables a proactive assessment of vulnerability which can facilitate collaborative planning among stakeholders in the value chain.

Assessing the Performance of the European Natural Gas Network for Selected Supply Disruption Scenarios Using Open-Source Information

Natural gas covers more than 20% of Europe’s primary energy demand. A potential disruption could lead to supply shortages with severe consequences for the European economy and society. History shows that such a vast and complex network system is prone to exogenous and endogenous disruptions. A dedicated large-scale dataset of the European natural gas network from publicly available information sources is assembled first. The spatial coverage, completeness and resolution allows analyzing the behavior of this geospatial infrastructure network (including consumption) and its components under likely disruptive events, such as earthquakes, and/or technical failures. Using the developed system state simulation engine, the disruption impact is mapped. The results show that storage facilities cannot in all cases compensate for a pipeline disruption. Moreover, critical pipelines, such as the Transitgas pipeline crossing the Alps and the Trans-Mediterranean pipeline bringing natural gas from Northern Africa, are identified. To analyze the pipelines with high impact on the system performance, a detailed scenario analysis using a Monte Carlo simulation resulting in supply grade mapping is conducted and presented for the case of Italy. Overall, it can be concluded that locations with a dead-end, sole supply, and without storage facility nearby, are remarkably exposed to natural gas supply losses.

EOQ with independent endogenous supply disruptions

We consider an inventory installation, controlled by the periodic review base stock (S, T) policy and facing a fixed-rate deterministic demand which, if unsatisfied, is backordered. The supply process is unreliable, so supply deliveries may fail according to an independent Bernoulli process; we refer to such failures reflecting the supply service quality and being internal to the supply chain, as endogenous disruptions. We seek to jointly determine the two policy variables, so to minimize long-run average cost. While an approximate model for this problem was recently analyzed, we present an exact analysis, valid for two common accounting schemes for inventory cost evaluation: continuous and end-of-cycle costing. After developing a unified (and exact) average cost model for both costing schemes, the cost for each scheme is analyzed. In both cases, the optimal policy variables and cost prevail in closed-form, having an identical structure to those of EOQ (with backorders). In fact, under continuous costing, the optimal solution reduces to EOQ for perfect supply. Analytical properties, demonstrating the impact of deteriorating supply quality on the optimal policy, are established. Moreover, computations reveal the cost impact of deploying heuristics that either ignore supply disruptions or rely on inaccurate costing information.

The expansion and contraction of the journalistic field and American online citizen journalism, 2000–2012

While previous research has considered patterns of homogeneity and heterogeneity in the journalistic field, existing literature has largely ignored the factors that contribute to the growth and contraction of the field. Using citizen journalism (CJ) as a case study, we examine how four forces – organizational population dynamics, technological innovations, exogenous political events, and endogenous disruptions elsewhere in the field – shaped the growth of CJ over time and, consequently, the journalistic field. Using a snowball sampling method, we collected a “near-population” of U.S.-based, English-language CJ sites (n=1829) to measure yearly density and rates of foundings and mortalities. The population of CJ sites increased through most of the period, foundings declined after a spike in 2005, and mortalities rose dramatically after 2010. The results provide evidence that organizational population and technological change affected the size of the population of CJ sites, while political upheaval and disruptions within professional journalism held less sway.

Procurement Contracts in the Presence of Endogenous Disruption Risk

ABSTRACTWe consider a manufacturer facing an unreliable supplier with high or low type on initial reliability. The private reliability can be enhanced through process improvement initiated by either manufacturer (manufacturer‐initiated improvement, MI) or supplier (supplier‐initiated improvement, SI). We derive optimal procurement contracts for both mechanisms and find that the moral hazard does not necessarily generate more profit for high‐type supplier. Furthermore, information asymmetry causes a greater possibility of not ordering from low type in SI than MI. For low type, when an upward effort distortion appears in both mechanisms, a decreased (increased) unit penalty should be imposed in MI (SI) compared with symmetric information case. Although possibly efficient effort from the supplier could yield greater channel profit in SI, several scenarios violate this expectation. However, the manufacturer's expected profit in MI is no less than that in SI. When MI is extended to MSI where both manufacturer and supplier can exert effort, the expected profits of two parties are equal to those in SI. We further extend SI to SID, where both process improvement and dual‐sourcing are available. The manufacturer considers the trade‐off between the benefit from diversification and the loss from dual information rent to decide to choose SID or MI. By comparing SID with pure dual‐sourcing, we find that supplier's process improvement could either accelerate or retard the exercise of dual‐sourcing.

The Structure of Contingency

Can we identify and theorize contingency as a property of processes and situations? Applied to social and historical events, contingency denotes a mode of causality characterized by its indeterminate character. Conjunctural causation and period effects lack the specificity required to identify a distinctive class of processes. References to chance happenings offer no clue to analyze endogenous disruptions. Focusing on breaks in patterns of social relations and the role played by individual agency, the author distinguishes four types of impact—pyramidal, pivotal, sequential, and epistemic—and investigates how these relate to the possibility of indeterminacy through an Event Structure Analysis of the night of August 4, 1789, in Versailles. This empirical foray underscores the significance of junctures that are indeterminate with respect to their collective outcomes. The article grounds analytically this class of conjunctures with the concept of mutual uncertainty, gauges the phenomenal scope of this conting...

The improvement and application of piggyBac transposon system in mammals

The piggyBac (PB) transposon system is a useful genomic engineering tool due to its high transposition efficiency, precise excision, semi-random insertion and large cargo capacity. But, it still needs to further improve the transgenic efficiency and reduce the risk of endogenous disruption caused by the random insertion of exogenous gene, especially in transgenic experiments of individual mammals. In recent studies, the PB transposase is fused with a DNA binding protein as a chimeric protein, which can guide the transposon to pre-designed loci. Besides, PB transposases obtained by mutagenesis have dramatically enhanced transposition activity and generated a novel function which is excision competent and integration defective. Furthermore, PB transposon system can carry large exogenous DNA fragments up to 207 kb when combining with the bacterial artificial chromosome vector. So far, these modified transposon systems have been widely applied in genome studies, gene therapy and induced pluripotent stem cells (iPS cells). In this study, we review the latest studies on piggyBac transposon system and its application prospect.

Significant dissociation of expression patterns of the basic helix–loop–helix transcription factors Dec1 and Dec2 in rat kidney

Dec1 and Dec2 are regulators of the mammalian molecular clock that show robust circadian rhythms in the suprachiasmatic nucleus and various peripheral tissues. Although the expression of Dec1 and Dec2 is altered by multiple stimuli in different organs, their transcriptional regulatory mechanisms have not been fully elucidated for the kidney. In the present study, we describe for the first time significant dissociation of expression patterns with arrhythmic expression of Dec1 and rhythmic expression of Dec2 in rat kidney under a normal light-dark (LD) cycle. Daytime restricted feeding (RF) significantly altered the expression patterns of these two clock genes, and even induced circadian expression of Dec1 with an amplitude of 2.2 on day 3 and 4.2 on day 7. However, when a reversed feeding schedule was coupled with a reversed LD cycle, the expression of Dec1 but not Dec2 reverted to being arrhythmic. Moreover, exogenous injection of the glucocorticoid analogue dexamethasone (Dex) at certain times of the day resulted in rhythmic expression of Dec1, which was similar to that seen following RF for 7 days. In contrast, endogenous disruption of glucocorticoids by adrenalectomy abolished RF-induced rhythmic expression of Dec1 in the kidney. These observations suggest the existence of a glucocorticoid gating mechanism in the circadian expression of Dec1 in rat kidney.

Review: Clock genes at the heart of depression

The rhythms of life are ever pervasive, touching almost every aspect of our lives. We are finely tuned to the cycle of light and dark, so that we normally sleep during the night and are active during the day. Physiological rhythms are, however, not just slaves to the solar day, but are actually generated endogenously within the suprachiasmatic nuclei in the hypothalamus and are entrained via the retina. The circadian timing system is organized hierarchically with the suprachiasmatic nuclei providing neural and/or hormonal cues to the various organ systems, allowing them to express their own rhythmic physiological output. There is now a substantial body of evidence emerging that disruption of rhythmicity through altered sleep/wake patterns and exposure to light, or through endogenous disruption of key determinants of endogenous rhythms, can be detrimental to health. Circadian rhythm disturbances have long been associated with mood disorders, especially delayed sleep onset, and evidence is accumulating that alterations to the cellular timing system may underpin some aspects of the disorders. For example, mice carrying mutations in either Clock or per2 spend less time immobile in swim tests, which has been suggested as mimicking mania. In humans, single nucleotide polymorphisms in Clock and other clock genes have been associated with depression. With this increasing knowledge we may predict that new antidepressant drugs will emerge that, as a primary or secondary mechanism of action, target and correct abnormalities in the circadian timing system.

Payment uncertainty, the division of labor, and productivity declines in great depressions

This paper proposes a simple model that formalizes a variant of Ohanian's conjecture explaining the productivity declines observed in the Great Depression [Ohanian, L.E., 2001. Why did productivity fall so much during the Great Depression? American Economic Review 91 (2), 34–38]. If a large payment shock like an asset-price collapse renders many firms insolvent, other economic agents become exposed to a higher risk of not being paid ( payment uncertainty). The payment uncertainty causes endogenous disruptions of the division of labor among firms, thereby lowering macroeconomic productivity. The prediction of the model is that productivity correlates negatively with bankruptcies and positively with the cost share of intermediate inputs, which is consistent with the data from depression episodes. The model implies that the so-called failure of macroeconomic policy in the United States during the early 1930s, when a rash of bankruptcies occurred, could actually have been welfare enhancing, since the quick exit of insolvent agents can resolve payment uncertainty quickly.