Warehousing in the e-commerce era: A survey Boysen, Nils; de Koster, René; Weidinger, Felix
European journal of operational research,
09/2019, Letnik:
277, Številka:
2
Journal Article
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•We survey the field of warehousing for online retailers.•Suited warehousing systems are described.•The existing literature is surveyed.•Future research challenges are identified.
E-commerce ...retailers face the challenge to assemble large numbers of time-critical picking orders each consisting of just a few order lines with low order quantities. Traditional picker-to-parts warehouses are often ill-suited for these prerequisites, so that automated warehousing systems (e.g., automated picking workstations, robots, and AGV-assisted order picking systems) are applied and organizational adaptions (e.g., mixed-shelves storage, dynamic order processing, and batching, zoning and sorting systems) are made in this branch of industry. This paper is dedicated to these warehousing systems especially suited for e-commerce retailers. We discuss suited systems, survey the relevant literature, and define future research needs.
ENDOGENOUS PRODUCTION NETWORKS Acemoglu, Daron; Azar, Pablo D.
Econometrica,
01/2020, Letnik:
88, Številka:
1
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We develop a tractable model of endogenous production networks. Each one of a number of products can be produced by combining labor and an endogenous subset of the other products as inputs. Different ...combinations of inputs generate (prespecified) levels of productivity and various distortions may affect costs and prices. We establish the existence and uniqueness of an equilibrium and provide comparative static results on how prices and endogenous technology/input choices (and thus the production network) respond to changes in parameters. These results show that improvements in technology (or reductions in distortions) spread throughout the economy via input–output linkages and reduce all prices, and under reasonable restrictions on the menu of production technologies, also lead to a denser production network. Using a dynamic version of the model, we establish that the endogenous evolution of the production network could be a powerful force towards sustained economic growth. At the root of this result is the fact that the arrival of a few new products expands the set of technological possibilities of all existing industries by a large amount—that is, if there are n products, the arrival of one more new product increases the combinations of inputs that each existing product can use from 2n-1 to 2ⁿ, thus enabling significantly more pronounced cost reductions from choice of input combinations. These cost reductions then spread to other industries via lower input prices and incentivize them to also adopt additional inputs.
Industry 4.0 has been considered a new industrial stage in which several emerging technologies are converging to provide digital solutions. However, there is a lack of understanding of how companies ...implement these technologies. Thus, we aim to understand the adoption patterns of Industry 4.0 technologies in manufacturing firms. We propose a conceptual framework for these technologies, which we divided into front-end and base technologies. Front-end technologies consider four dimensions: Smart Manufacturing, Smart Products, Smart Supply Chain and Smart Working, while base technologies consider four elements: internet of things, cloud services, big data and analytics. We performed a survey in 92 manufacturing companies to study the implementation of these technologies. Our findings show that Industry 4.0 is related to a systemic adoption of the front-end technologies, in which Smart Manufacturing plays a central role. Our results also show that the implementation of the base technologies is challenging companies, since big data and analytics are still low implemented in the sample studied. We propose a structure of Industry 4.0 technology layers and we show levels of adoption of these technologies and their implication for manufacturing companies.
•We study Industry 4.0 technology patterns in 92 manufacturing companies.•We propose a framework with front-end and base technologies of Industry 4.0•Our method is based on cluster analysis and independence tests.•The main contribution is a maturity model showing technology patterns.•Big Data, analytics and the implementation of flexibilization are the main challenges.
This study investigates the role of supply chain risk management (SCRM) in mitigating the effects of disruptions impacts on supply chain resilience and robustness in the context of COVID-19 outbreak. ...Using structural equation modeling on a survey data from 470 French firms, the results confirm the basic tenets of resource-based view and organizational information processing theories regarding the combination of dynamic resources to face disruptions’ uncertainty. Furthermore, the findings reveal the mediating role of SCRM practices and the prominent role they play in fostering supply chain resilience and robustness. Overall, by providing empirical assessment of a comprehensive SCRM framework, this research contributes to the extant literature and suggests further avenues for research.
•Supply chain risk management practices mitigation role during COVID-19 is examined.•Resources-Based View and organizational information processing theory inform study.•Supply chain risk management practices foster Supply Chain resilience and robustness.•Research discussion provide guidance for further investigation.
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.
This research uses sensemaking theory to explore how emerging blockchain technology may transform supply chains. We investigate three research questions (RQs): What are blockchain technology's ...perceived benefits to supply chains, where are disruptions mostly likely to occur and what are the potential challenges to further blockchain diffusion? We conducted in-depth interviews with 14 supply chain experts. Cognitive mapping and narrative analysis were deployed as the two main data analysis techniques to aid our understanding and evaluation of people's cognitive complexity in making sense of blockchain technology. We found that individual experts developed different cognitive structures within their own sensemaking processes. After merging individual cognitive maps into a strategic map, we identified several themes and central concepts that then allowed us to explore potential answers to the three RQs. Our study is among the very few to date to explicitly explore how blockchains may transform supply chain practices. Using the sensemaking approach afforded a deeper understanding of how senior executives diagnose the symptoms evident from blockchains and develop assumptions, expectations and knowledge of the technology, which will then shape their future actions regarding its utilisation. We demonstrate the usefulness of sensemaking theory as an alternative lens in investigating contemporary supply chain phenomena such as blockchains. Bringing sensemaking theory to this discipline in particular enriches emerging behavioural operations research. Our contributions also lie in extending the theories of prospective sensemaking and adding further insights to the stream of technology adoption studies.
•We investigate how blockchains may transform supply chains.•We adopt sensemaking theory to gauge foresights via expert interviews.•We identify the perceived benefits of blockchains to supply chains.•We establish potential areas where blockchains may penetrate supply chains.•We elucidate the challenges of blockchain technology's further diffusion into supply chains.
The importance of big data analytics–enabled dynamic capability has been at the forefront of research for information systems management, operations management, and strategic management community. ...Prior studies have reported on the influence of big data analytics–enabled dynamic capability (BDA) for improved organizational agility and organizational performance, but there has been a paucity of literature regarding the role of big data analytics–enabled dynamic capability in untangling the supply chain ambidexterity dilemma and organizational performance. To address these research gaps, this paper draws on the dynamic capability view of the organization under the contingent effect of environmental dynamism. We tested our research hypotheses using 281 surveys, gathered using a pre-tested questionnaire. Our results suggest that BDA has positive effects on improving supply chain agility (SCAG), supply chain adaptability (SCAD) and performance measures (cost performance and operational performance). However, we noted that hypotheses regarding the moderating effect of environmental dynamism (ED) on the paths joining BDA and SCAG/SCAD were not supported. To address these unexpected results, we conducted post hoc analysis to explain the rationale behind the insignificant moderating effects of ED on the paths joining BDA and SCAG/SCAD. We found that the effects of BDA on SCAG/SCAD were higher under intermediate levels of environmental dynamism but comparatively weak when the environmental dynamism is low or high. Hence, we can argue that big data analytics can help enhance supply chain agility, supply chain adaptability, and organizational performance, but these effects are contingent upon the level of environmental dynamism. Moreover, a non-linear, inverse U-shaped moderating effect of environmental dynamism exists. Collectively, these findings provide a theory-based understanding of the organizational level of usage of big data analytics and its effects on supply chain agility, supply chain adaptability, and organizational performance. Moreover, they further shape our understanding of how big data analytics–enabled dynamic capabilities yield differential results under the moderating effect of environmental dynamism. Hence, we believe that our results will be useful for managers who are highly optimistic about the usage of these emerging technologies and their effects on supply chain characteristics. Finally, we have outlined our study limitations and offered numerous research directions.
•Epidemic outbreaks are a special case of supply chain (SC) risks.•We articulate the specific features of epidemic outbreaks in SCs.•We demonstrate a simulation model for epidemic outbreak ...analysis.•We use an example of coronavirus COVID-19 outbreak.
Epidemic outbreaks are a special case of supply chain (SC) risks which is distinctively characterized by a long-term disruption existence, disruption propagations (i.e., the ripple effect), and high uncertainty. We present the results of a simulation study that opens some new research tensions on the impact of COVID-19 (SARS-CoV-2) on the global SCs. First, we articulate the specific features that frame epidemic outbreaks as a unique type of SC disruption risks. Second, we demonstrate how simulation-based methodology can be used to examine and predict the impacts of epidemic outbreaks on the SC performance using the example of coronavirus COVID-19 and anyLogistix simulation and optimization software. We offer an analysis for observing and predicting both short-term and long-term impacts of epidemic outbreaks on the SCs along with managerial insights. A set of sensitivity experiments for different scenarios allows illustrating the model’s behavior and its value for decision-makers. The major observation from the simulation experiments is that the timing of the closing and opening of the facilities at different echelons might become a major factor that determines the epidemic outbreak impact on the SC performance rather than an upstream disruption duration or the speed of epidemic propagation. Other important factors are lead-time, speed of epidemic propagation, and the upstream and downstream disruption durations in the SC. The outcomes of this research can be used by decision-makers to predict the operative and long-term impacts of epidemic outbreaks on the SCs and develop pandemic SC plans. Our approach can also help to identify the successful and wrong elements of risk mitigation/preparedness and recovery policies in case of epidemic outbreaks. The paper is concluded by summarizing the most important insights and outlining future research agenda.
•We define autonomous mobile robots in intralogistics.•We explain the evolution from automated guided vehicles to autonomous mobile robots.•We identify the technological advances affecting the ...planning and control decisions.•We provide guidance and methods to plan and control autonomous mobile robots.•We identify a research agenda for planning and control of autonomous mobile robots.
Autonomous mobile robots (AMR) are currently being introduced in many intralogistics operations, like manufacturing, warehousing, cross-docks, terminals, and hospitals. Their advanced hardware and control software allow autonomous operations in dynamic environments. Compared to an automated guided vehicle (AGV) system in which a central unit takes control of scheduling, routing, and dispatching decisions for all AGVs, AMRs can communicate and negotiate independently with other resources like machines and systems and thus decentralize the decision-making process. Decentralized decision-making allows the system to react dynamically to changes in the system state and environment. These developments have influenced the traditional methods and decision-making processes for planning and control. This study identifies and classifies research related to the planning and control of AMRs in intralogistics. We provide an extended literature review that highlights how AMR technological advances affect planning and control decisions. We contribute to the literature by introducing an AMR planning and control framework to guide managers in the decision-making process, thereby supporting them to achieve optimal performance. Finally, we propose an agenda for future research within this field.
•We examine the disruption propagation in supply chains.•We use agent-based modeling to delineate disruption propagation behavior.•We explore the effects of forward and backward disruption ...propagation.•We propose management strategies based on modeling results.•We analyze investment strategies in a dual-focal supply network.
A local disruption can propagate to forward and downward through the material flow and eventually influence the entire supply chain network (SCN). This phenomenon of ripple effect, immensely existing in practice, has received great interest in recent years. Moreover, forward and backward disruption propagations became major stressors for SCNs during the COVID-19 pandemic triggered by simultaneous and sequential supply and demand disruptions. However, current literature has paid less attention to the different impacts of the directions of disruption propagation. This study examines the disruption propagation through simulating simple interaction rules of firms inside the SCN. Specifically, an agent-based computational model is developed to delineate the supply chain disruption propagation behavior. Then, we conduct multi-level quantitative analysis to explore the effects of forward and backward disruption propagation, moderated by network structure, network-level health and node-level vulnerability. Our results demonstrate that it is practically important to differentiate between forward and backward disruption propagation, as they are distinctive in the associated mitigation strategies and in the effects on network and individual firm performance. Forward disruption propagation generally can be mitigated by substitute and backup supply and has greater impact on firms serving the assembly role and on the supply/assembly networks, whereas backward disruption propagation is normally mitigated by flexible operation and distribution and has bigger impact on firms serving the distribution role and on distribution networks. We further analyze the investment strategies in a dual-focal supply network under disruption propagation. We provide propositions to facilitate decision-making and summarize important managerial implications.
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