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Here we celebrate the centennial of Ford Whitman Harris's model for determining economical lot sizes, which was published in the A.W. Shaw Company's magazine Factory, The Magazine of Management in February 1913. The square-root formula derived by Harris has become one of the most cited and applied results in production and operations management. We examine the circumstances under which this result was derived, and explore the probable causes for the later obscurity of Harris's paper, which was forgotten for many years. © 2013 Elsevier B.V. All rights reserved.

The COVID-19 pandemic has illustrated the unprecedented challenges of ensuring the continuity of operations in a supply chain as suppliers' and their suppliers stop producing due the spread of infection, leading to a degradation of downstream customer service levels in a ripple effect. In this paper, we contextualize a dynamic approach and propose an optimal control model for supply chain reconfiguration and ripple effect analysis integrated with an epidemic dynamics model. We provide supply chain managers with the optimal choice over a planning horizon among subsets of interchangeable suppliers and corresponding orders; this will maximize demand satisfaction given their prices, lead times, exposure to infection, and upstream suppliers' risk exposure. Numerical illustrations show that our prescriptive forward-looking model can help reconfigure a supply chain and mitigate the ripple effect due to reduced production because of suppliers' infected workers. A risk aversion factor incorporates a measure of supplier risk exposure at the upstream echelons. We examine three scenarios: (a) infection limits the capacity of suppliers, (b) the pandemic recedes but not at the same pace for all suppliers, and (c) infection waves affect the capacity of some suppliers, while others are in a recovery phase. We illustrate through a case study how our model can be immediately deployed in manufacturing or retail supply chains since the data are readily accessible from suppliers and health authorities. This work opens new avenues for prescriptive models in operations management and the study of viable supply chains by combining optimal control and epidemiological models., (© 2023 Elsevier B.V. All rights reserved.)

This paper provides empirical evidence on the impact of the Covid-19 pandemic on logistics and supply chain processes of five industrial sectors of Italy, namely food & beverage, machine manufacturing, metal mechanical industry, logistics & transport, and textile & fashion. A questionnaire survey, with 82 useful responses, was conducted to investigate various effects of Covid-19 on these businesses, such as the volumes handled and the service performance in the immediate-, short- and medium-term, the countermeasures implemented by companies and the future decision-making strategies. The period of analysis spans from January 2020 to June 2021. Results show that the impact of Covid-19 on volumes and service performance varied across the sectors: the food & beverage and logistics & transport were poorly affected by the pandemic and experienced a general increase in the demand and volumes, while mechanical or textile & fashion industries were mostly affected by a decrease in demand. The positive/negative impacts were particularly evident at the beginning of the pandemics, but, depending on the sector, the effects could cease quite quickly or last in the short-term. The countermeasures adopted against the Covid-19 emergency differ again across sectors; in general, industry fields that were particularly impacted by the pandemic emergency have applied more countermeasures. Typical strategies for risk management (e.g., the diversification in transport modes or the stock increase) turned out to be applied as immediate countermeasures or in plan for the future in few industries only. Differences across sectors were also observed about the sourcing strategies already in use, implemented to counteract the pandemics or expected to be maintained in time. Empirical outcomes offered are expected to help researchers gain a deep understanding of Covid-19 related phenomena, thus inspiring further research activities., (© 2023 Elsevier B.V. All rights reserved.)

The outbreak of COVID-19 has accelerated the building of resilient supply chains, and supply chain digitalization is gradually being recognized as an enabling means to this end. Nevertheless, scholars generally agree that more empirical studies will need to be conducted on how digitalization can facilitate supply chain resilience at various stages and enhance supply chain performance in a highly uncertain environment. To echo the call, this study develops a theoretical influence mechanism of "supply chain digitalization → supply chain resilience → supply chain performance" based on dynamic capability theory. The proposed relationships are validated using survey data collected from 210 Chinese manufacturing companies. The results help identify the paths digitalization and supply chain resilience can take to improve supply chain performance in a turbulent environment. The different roles of three supply chain resilience capabilities, namely absorptive capability (before the disruption), response capability (during the disruption), and recovery capability (after the disruption), which impact on supply chain performance differently, are highlighted. In addition, it is found that digitalization can bring a differential impact on these three supply chain resilience capabilities through different aspects of resource and structural adjustment measures. The findings also confirm the mediating role of absorptive capability, response capability, and recovery capability between digitalization and supply chain performance. During crisis, supply chain digitalization can increase cost-effectiveness, enhance information and communication efficiency, and promote supply chain resilience to achieve better performance. For theoretical contribution, this study enriches the research on supply chain digitalization and resilience by underpinning the relationships between the two with dynamic capability theory. For practical contribution, the research findings provide insights for enterprises to leverage digitalization to strengthen resilience in supply chain., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2023 Elsevier B.V. All rights reserved.)

The COVID-19 pandemic caused significant disruptions to global operations and supply chains. While the huge impact of the pandemic has nurtured important literature over the last couple of years, little is being said about the role of resource orchestration in supporting resilience in highly disruptive contexts. Thus, this study aims to this knowledge gap by proposing an original model to explore supply chain resilience (SCRE) antecedents, considering supply chain alertness (SCAL) as a central point to support resilience. This study focuses on the resource orchestration theory (ROT) to design a conceptual model. The partial least squares structural equation modeling (PLS-SEM) served to validate the model, exploring data from the UK supply chain decision-makers. The study reveals a number of both expected and unexpected findings. These include the evidence that supply chain disruption orientation (SCDO) has a strong positive effect on the SCAL. In addition, SCAL plays a strong positive effect in resource reconfiguration (RREC), supply chain efficiency (SCEF) and SCRE. We further identified a partial mediation effect of RREC on the relationship between SCAL and SCRE. Surprisingly, it appeared that SCAL strongly influences SCEF, while SCEF itself does not create any significant effect on SCRE. For managers and practitioners, the importance of resource orchestration as a decisive approach to adequately respond to huge disruptions is clearly highlighted by our results. Finally, this paper helps to grasp better how important resource orchestration in operations and supply chains remains for appropriate responses to high disruptions such as the COVID-19 impacts., (© 2022 Elsevier B.V. All rights reserved.)

In this paper, we construct the first stochastic Generalized Nash Equilibrium model for the study of competition among countries for limited supplies of medical items (PPEs, ventilators, etc.) in the disaster preparedness and response phases in the Covid-19 pandemic. The government of each country is faced with a two-stage stochastic optimization problem in which the first stage is prior to the pandemic declaration and the second stage is post the pandemic declaration. We provide the theoretical constructs, a qualitative analysis, and an algorithm, accompanied by convergence results. Both illustrative examples are presented as well as algorithmically solved numerical examples, inspired by the need for N95 masks and ventilators. The results reveal that, in addition to the preparedness of countries before the pandemic declaration, their ability to adapt to the conditions in different scenarios has a significant impact on their overall success in the management of the pandemic crisis. The framework can capture competition for other medical supplies, including Covid-19 vaccines and possible treatments, with modifications to handle perishability., (© 2021 Elsevier B.V. All rights reserved.)

In this paper, we respond to the COVID-19 pandemic by constructing supply chain network optimization models, which explicitly include labor as an important variable in the network economic activity links, along with associated capacities. Labor is a critical resource in supply chains from production to transportation, storage, and distribution. In a pandemic, the availability of labor for different supply chain network activities may be disrupted due to illness, fear of contagion, morbidity, necessity of social/physical distancing, etc. The modeling framework considers first elastic demands for a product and then fixed demands, coupled with distinct types of labor capacities in order to capture the availability of this valuable resource in a pandemic, as well as possible flexibility. The supply chain network framework, which includes electronic commerce, is relevant to many different supply chain applications including protective personal and medical equipment, as well as to particular food items. Theoretical results as well as computed numerical examples are presented., Competing Interests: None., (© 2021 Elsevier B.V. All rights reserved.)

Over the years, supply chain reconfiguration decisions have been solely based on operational risk. Simplification strategies, such as horizontal mergers, and networking strategies, such as risk pooling, are conflicting paradigms that have been shown to improve financial performance of supply partners. The implication of this to disruption risk is not fully known, especially as it concerns information security breach (ISB). Analysts have rated ISB as a huge disruption risk, costing businesses millions of dollars. Using a credible and well-established agent-based simulation approach and statistical analysis, we examine the impact of ISB on the simplification and risk pooling strategies respectively under three different order replenishment systems. The effect of reconfiguring the supply chain is first examined in a non-security breach scenario and then in a breached scenario. We find that reconfiguration has no benefit to a supply chain using a parameter based replenishment policy (option I), in both breach and non-breach situations, but leads to significant advantage when batch ordering model (option II) or a combined batch-and-parameter based ordering policy (option III) is used. We also established that batch ordering system favours the risk pooling strategy whereas a combined batch-and-parameter ordering system favours the simplification counterpart especially when the simplification is at the wholesaler tier. This study has significant implications for supply chain design as well as information security priorities. This is one of the first papers to look at how ISB impacts supply chain configuration and the role of ordering decision context., (© 2020 Elsevier B.V. All rights reserved.)

Considered is a retailer (she) facing non-stationary stochastic demand. Demand can be fully observed and backlogged, consequently the retailer can update the initial demand information using a Bayesian approach. To alleviate the demand risk, the retailer may use a secondary opportunity to replenish through an option contract. In addition, the retailer also has access to an immediate loan if she faces capital constraints and to a risk-free investment if she has surplus funds. The paper presents a recourse approach to solve the two-stage optimization problem and derive the optimal inventory/financing policies. The results show that the option procurement policy has a two-threshold base-stock structure depending on the first procurement, demand update and also the retailer's financial state. The initial procurement can be computed subsequently. A sufficiently large initial demand will induce the retailer to seize the secondary procurement opportunity. Finally, a series of numerical examples demonstrate the resulting policy under various inventory/financial situations. This research incorporates the financial and operational decisions into demand updates, and brings new managerial results and insights., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2020 Elsevier B.V. All rights reserved.)

The COVID-19 pandemic unveils unforeseen and unprecedented fragilities in supply chains (SC). A primary stressor of SCs and their subsequent shocks derives from disruption propagation (i.e., the ripple effect) through related networks. In this paper, we conceptualize current state and future research directions on the ripple effect for pandemic context. We scrutinize the existing OR (Operational Research) studies published in international journals dealing with disruption propagation and structural dynamics in SCs. Our study pursues two major contributions in relation to two research questions. First, we collate state-of-the-art research on disruption propagation in SCs and identify a methodical taxonomy along with theories displaying their value and applications for coping with the impacts of pandemics on SCs. Second, we reveal and systemize managerial insights from theory used for operating (adapting) amid a pandemic and during times of recovery, along with becoming more resistant to future pandemics. Streamlining the literature allowed us to reveal several new research tensions and novel categorizations and classifications. The outcomes of our study show that methodical contributions and the resulting managerial insights can be categorized into three levels, i.e., network, process, and control. Our analysis reveals that adaptation capabilities play the most crucial role in managing the SCs under pandemic disruptions. Our findings depict how the existing OR methods can help coping with the ripple effect at five pandemic stages (i.e., Anticipation; Early Detection; Containment; Control and Mitigation; and Elimination) following the WHO classification. The outcomes and findings of our study can be used by industry and researchers alike to progress the decision-support systems guiding SCs amid the COVID-19 pandemic and toward recovery. Suggestions for future research directions are offered and discussed., (© 2020 Elsevier B.V. All rights reserved.)

In recent years, customized bus (CB) is becoming an innovative model of the public transport system (PTS) in China. This service provides an advanced, timely, personalized, and flexible responses to the demand of the PTS, especially of commuters. Obviously, it could have an impact on public transport (PT) service. For instance, CB services influence the customers' variety-seeking behavior, which results in changes of customer options in different periods. Therefore, customers could be divided into different groups of preference. In this paper, we construct a two-period Hotelling game model by variety-seeking behavior and service level. The results show that, in the first stage, the departure frequency of CB and PT is influenced by variety-seeking behavior and service level. In the second stage, departure frequency is influenced by service level only. Next, although the departure frequency of bus impacts the changes of passenger ratios in different stages, service level appreciably impacts passenger number. From customer surplus and social welfare, we find that adjustment of service level can increase social welfare, which means that CB and PT will reach an optimum effect. The present work can provide a valuable reference to policymakers, practitioners, and others., (© 2020 Elsevier B.V. All rights reserved.)

In this editorial piece, we first introduce the theme and objectives of the special issue on new technologies in operations and supply chains as well as their implications for sustainability. The papers comprising the special issue are then summarized, and major findings are briefly presented. Based on our observations on the submissions and the research gaps yet to be addressed, we attempt to offer our views on the directions for future research in the same research agenda, including discussion around research scope, research theory, research methodology, and research findings as well as in-depth studies concerning contemporary and imperative issues confronting operations and supply chain managers., (© 2020 Elsevier B.V. All rights reserved.)

Resilience enables supply chains to reduce their proneness to disruptions and recover faster. Many existing strategies to strengthen the resilience of supply chains are facilitated by the use of digital technology. Blockchain, as one of the promising innovative technologies, enables a transparent, secure, and timely data exchange and automation via smart contracts. In this paper, we discuss the impact of blockchain technology on supply chain risk management and, in particular, on supply chain resilience. We identify potential risk-related blockchain application scenarios and examine their impact on the existing resilience strategies. We explore the impact of the most promising applications with respect to resilience by using an agent-based simulation model of a complex supply network affected by disruptions. The theoretical analysis reveals a promotion of supply chain resilience strategies, especially if smart contracts are used for risk-related collaboration. The simulation study indicates an increase in resilience if the underlying collaboration is based on time-efficient processes: The propagation of disruptions, the network recovery time, and total costs can be substantially reduced. However, depending on the duration of the disruption, negative effects can occur if process efficiency is insufficient. From our investigations, we derive insights for managers who are interested in practical implementation., (© 2020 Elsevier B.V. All rights reserved.)

In recent years, many apparel multinational firms (MNFs) have shifted their production from traditional manufacturing bases (e.g., China) to the emerging ones located in Southeast Asia (e.g., Vietnam and Bengal). The interactions among market sizes, MNF's competition with local rival and the global tax rules play key roles in the MNF's decisions. In this paper, we study the preferences of a MNF and its contract manufacturer (CM) over two manufacturing outsourcing structures and investigate whether their objective conflicts can be reconciled. The MNF relies on the CM for production and sells goods in both Chinese and Southeast Asian markets. It is optional for the MNF to use a CM located in China, but has to suffer from the CM's differential prices because of China's partial value-added tax (VAT) refund policy. It is also optional for the MNF to use a CM located in Southeast Asia, resulting in uniform production fee for the goods sold in two markets. The former is traditional outsourcing structure (TS), and the latter is shifted outsourcing structure (SS). Interestingly, we find that, the MNF may first prefer SS, then prefer TS, and back to prefer SS, as the relative market potential between the Southeast Asian market and the Chinese market increases. The CM's preferences may switch twice, too. We identify the opportunities where the preferences of the MNF and the CM are aligned, which are driven by China's partial VAT refund policy., (© 2020 Published by Elsevier B.V.)

Large manufacturers have been using simulation to support decision-making for design and production. However, with the advancement of technologies and the emergence of big data, simulation can be utilised to perform and support data analytics for associated performance gains. This requires not only significant model development expertise, but also huge data collection and analysis efforts. This paper presents an approach within the frameworks of Design Science Research Methodology and prototyping to address the challenge of increasing the use of modelling, simulation and data analytics in manufacturing via reduction of the development effort. The use of manufacturing simulation models is presented as data analytics applications themselves and for supporting other data analytics applications by serving as data generators and as a tool for validation. The virtual factory concept is presented as the vehicle for manufacturing modelling and simulation. Virtual factory goes beyond traditional simulation models of factories to include multi-resolution modelling capabilities and thus allowing analysis at varying levels of detail. A path is proposed for implementation of the virtual factory concept that builds on developments in technologies and standards. A virtual machine prototype is provided as a demonstration of the use of a virtual representation for manufacturing data analytics., Competing Interests: Disclosure statement No potential conflict of interest was reported by the authors.

In this paper the influence of different dispatching rules on the average production lead time is investigated. Two theorems based on covariance between processing time and production lead time are formulated and proved theoretically. Theorem 1 links the average production lead time to the "processing time weighted production lead time" for the multi-stage production systems analytically. The influence of different dispatching rules on average lead time, which is well known from simulation and empirical studies, can be proved theoretically in Theorem 2 for a single stage production system. A simulation study is conducted to gain more insight into the influence of dispatching rules on average production lead time in a multi-stage production system. We find that the "processing time weighted average production lead time" for a multi-stage production system is not invariant of the applied dispatching rule and can be used as a dispatching rule independent indicator for single-stage production systems.

The logistics services industry will be significantly affected by future developments throughout the world. Therefore, developing future scenarios is an important basis for long-term strategy development. Nevertheless, research exposes that there is a lack of awareness among logistics researchers and practitioners about future scenarios. In this paper, we apply scenario planning and present the findings of an extensive Delphi-based scenario study on the future of the logistics services industry in the year 2025. The major contribution of our research is the development of probable and unforeseen scenarios of the future which may provide a valuable basis for strategy development in the logistics services industry., (Copyright © 2010 Elsevier B.V. All rights reserved.)