Showing papers on "Service level published in 2020"

Strategies for Managing the Impacts of Disruptions During COVID-19: an Example of Toilet Paper

Abstract: Due to the recent pandemic of coronavirus, known as the COVID-19 outbreak, the supply chains have been impacted most significantly. Manufacturers of certain items have experienced a substantial increase in demand, and on the other hand, raw materials supply, to produce those items, has reduced because of supply failure. To overcome these challenges, this paper proposes some strategies to improve service level during an extraordinary pandemic outbreak, such as COVID-19, for the most wanted products such as toilet paper. This study considers meeting the increased demand of the customers for an essential product of daily life like toilet paper during a pandemic is beyond the traditional economic objective, i.e., increase profit, of the manufacturers. Instead, this should be more about the social responsibility of all the manufactures to ensure that they can serve more customers. Motivated by this and taking toilet paper as an example of the product, we first analyzed the current scenario of the manufacturing and the demand for the product and then proposed some strategies to deal with this unprecedented risk and analyzed the results. We have compared the results, using hypothetical data, between the current scenario and proposed strategies. The result shows that sharing information and resources from all manufacturers to produce under a single brand, emergency sourcing, producing basic quality items, and packing in the smallest sizes have a significant positive impact on the service level. This paper first investigates the strategies for a high-demand and essential item during a pandemic situation and proposes strategies to deal with this unique, extraordinary disruption.

The strategic analysis of logistics service sharing in an e-commerce platform

Abstract: In e-commerce, the success of hybrid online platforms is well documented where the platform not only works as a retailer but also offers online marketplace services to sellers. Logistics service is one of the most expensive operations for e-commerce and plays a critical role in promoting online purchases. In most cases, the platform builds a self-supporting logistics service system to deliver its own products, and the seller outsources the logistics service to third-party logistics service providers (TPLPs). Recently, the e-commerce market has emerged with a new trend of business-to-business logistics service sharing—the platform shares its logistics service system with the seller. In this paper, we first analyze the strategic and economic impacts of logistics service sharing. Our analysis shows that whereas logistics service sharing will lead to a lose-win situation for the platform and the seller when the TPLP's logistics service level and the market potential are low, it will lead to a win-lose situation when the TPLP's logistics service level or the market potential is very high. Furthermore, a win-win situation can be achieved when the TPLP's logistics service level and the market potential are in the middle regions. Then, we examine the equilibrium mode by considering the strategic interactions between the platform and the seller. We find that when the TPLP's logistics service level and the market potential are relatively low, the equilibrium mode is No-Service-Sharing. As the TPLP's logistics service level, the market potential, or both increase, the equilibrium mode will evolve from No-Service-Sharing to Service-Sharing.

Coordination of production and ordering policies under capacity disruption and product write-off risk: an analytical study with real-data based simulations of a fast moving consumer goods company

Abstract: Performance impacts of ordering and production control policies in the presence of capacity disruptions are studied on the real-life example of a retail supply chain with product perishability considerations. Constraints on product perishability typically result in reductions in safety stock and increases in transportation frequency. Consideration of the production capacity disruption risks may lead to safety stock increases. This trade-off is approached with the help of a simulation model that is used to compare supply chain performance impacts with regard to coordinated and non-coordinated ordering and production control policies. Real data of a fast moving consumer goods company is used to perform simulations and to derive novel managerial insights and practical recommendations on inventory, on-time delivery and service level control. In particular, for the first time, the effect of ‘postponed redundancy’ has been observed. Moreover, a coordinated production–ordering contingency policy in the supply chain within and after the disruption period has been developed and tested to reduce the negative impacts of the ‘postponed redundancy’. The lessons learned from experiments provide evidence that a coordinated policy is advantageous for inventory dynamics stabilization, improvement in on-time delivery, and variation reduction in customer service level.

Adaptive Computing-Plus-Communication Optimization Framework for Multimedia Processing in Cloud Systems

Abstract: A clear trend in the evolution of network-based services is the ever-increasing amount of multimedia data involved. This trend towards big-data multimedia processing finds its natural placement together with the adoption of the cloud computing paradigm, that seems the best solution to cope with the demands of a highly fluctuating workload that characterizes this type of services. However, as cloud data centers become more and more powerful, energy consumption becomes a major challenge both for environmental concerns and for economic reasons. An effective approach to improve energy efficiency in cloud data centers is to rely on traffic engineering techniques to dynamically adapt the number of active servers to the current workload. Towards this aim, we propose a joint computing-plus-communication optimization framework exploiting virtualization technologies, called MMGreen . Our proposal specifically addresses the typical scenario of multimedia data processing with computationally intensive tasks and exchange of a big volume of data. The proposed framework not only ensures users the Quality of Service (through Service Level Agreements), but also achieves maximum energy saving and attains green cloud computing goals in a fully distributed fashion by utilizing the DVFS-based CPU frequencies. To evaluate the actual effectiveness of the proposed framework, we conduct experiments with MMGreen under real-world and synthetic workload traces. The results of the experiments show that MMGreen may significantly reduce the energy cost for computing, communication and reconfiguration with respect to the previous resource provisioning strategies, respecting the SLA constraints.

COVID- 19: outcomes for Global Supply Chains

Abstract: The COVID-19 crisis exposed the vulnerability and poor resilience of the global supply chains The objective of this research is to reflect on the possible impacts of the Coronavirus crisis in the global supply chains and provide some recommendations to overcome the present situation, offering suggestions for future research: (1) What are the contingency factors affecting Supply Chains in the complex COVID-19 operating environment? (2) How do these factors affect post-COVID-19 operating performance? After a contextualization of the COVID-19 pandemic crisis and its impacts, theoretical background on Supply Chains and Supply Chain Management are presented, and a summary of the main scenarios for the post-COVID-19 crisis are discussed The propositions regarding the contingency factors and their impact on the Supply Chain operating performance in post-COVID-19 suggest that successful companies will focus on creating a new kind of operational performance and minimize risks To that end, companies will aim to improve their operations' resilience (ability to resist, hold on, and recover from shocks) and accelerate the end-to-end digital transformation Consumers will have to adapt to the contact-free economy, less low-cost supply chains, and put additional emphasis on service levels Governments will reinforce the focus in the health sector supply chain and increase spending in the health and social care sectors Furthermore, the longer, the more concentrated, the less transparent, and the more price sensitivity is the supply chain, the more challenging the adaptation to the new pos pandemic realities Suggestions for future research are also provided

Manufacturer Strategy on Service Provision in Competitive Channels

Abstract: A manufacturer commonly distributes through a set of retailers who are authorized to sell its product; demand‐enhancing services may also be provided by the manufacturer. These services may be granted to all authorized retailers (uniform service provision) or to a favored few authorized retailers (differential service provision). To determine when a manufacturer does—or does not—bestow equal service levels, we develop a model of one manufacturer selling through two competing retailers. We find manufacturer optimality to entail uniform service at some parametric values, while differential service is optimal at other values. Counterintuitively, with differential service, the recipient of lower service may be better off than it would be with higher service. Equally surprisingly, there are conditions for which the high‐service retailer prefers its rival to also receive a high level of service—but only if its rival is sufficiently small. While the three channel members often have different service‐provision preferences, there are also parametric values that place them in harmony with either differential or uniform service provision. Retailers sharing the cost of manufacturer‐provided service need not lessen firms’ preference confliction over the preferred service provision but can improve channel efficiency when the cost‐sharing rate is relatively low. We also investigate the effect of retailer‐provided services and the impact of service asymmetry level.

Home healthcare integrated staffing and scheduling

Abstract: Workforce planning for home healthcare represents an important and challenging task involving complex factors associated with labor regulations, caregivers’ preferences, and demand uncertainties. This task is done manually by most home care agencies, resulting in long planning times and suboptimal decisions that usually fail to meet the health needs of the population, to minimize operating costs, and to retain current caregivers. Motivated by these challenges, we present a two-stage stochastic programming model for employee staffing and scheduling in home healthcare. In this model, first-stage decisions correspond to the staffing and scheduling of caregivers in geographic districts. Second-stage decisions are related to the temporary reallocation of caregivers to neighboring districts, to contact caregivers to work on a day-off, and to allow under- and over-covering of demand. The proposed model is tested on real-world instances, where we evaluate the impact on costs, caregiver utilization, and service level by using different recourse actions. Results show that when compared with a deterministic model, the two-stage stochastic model leads to significant cost savings as staff dimensioning and scheduling decisions are more robust to accommodate changes in demand. Moreover, these results suggest that flexibility in terms of use of recourse actions is highly valuable as it helps to further improve costs, service level, and caregiver utilization.

Zoning a Service Area of Unmanned Aerial Vehicles for Package Delivery Services

Abstract: Package delivery services by deploying Unmanned Aerial Vehicles (UAVs) have received considerable attention due to their significant potential benefits. One of the scenarios making the concept more attractive is to deploy large numbers of UAVs to properly handle increasing demands for the service by the units. However, it is challenging because it increases the difficulty of UAV control as well as the complexity of the scheduling problems involved in the service. To tackle the issues, we propose a systematic approach that decomposes a service area into several disjoint zones. Within a zone, a single UAV at most can be operated. To verify the advantages and performance of the proposed approach, we first optimize the zoning, i.e. a service area decomposition, applying Genetic Algorithm (GA). We then evaluate the service level of the package deliveries by UAVs under the proposed approach using a simulation model.

Mitigating transportation disruptions in a supply chain: a cost-effective strategy

Abstract: Transportation disruptions can be damaging to a supply chain because goods may not arrive on time and this jeopardises the service level to the customers. While supply chain disruptions have gained...

Network Management 2030: Operations and Control of Network 2030 Services

Abstract: The networking landscape is expected to undergo profound changes over the course of the next decade. New network services are expected to emerge that will enable new applications such as the Tactile Internet, Holographic-Type Communications, or Tele-Driving. Many of these services will be characterized by very high degrees of precision with which end-to-end service levels must be supported. This will have profound implications on the management of those networks and services, from the need to support new methods for assurance of ultra-high-precision services to the need for new network programming models that will allow the industry to move beyond DevOps and SDN towards User-Defined Networking. This article analyzes those implications and provides an overview of challenges along with possible solution approaches and opportunities for research.

Research on supply chain partner selection method based on BP neural network

Abstract: In the process of establishing supply chain partnership, partner selection is the key and main step. If the enterprise selects the appropriate supply chain partner, in the material equipment unit price, the material equipment production and the supply ability, the product quality appraisal, the brand meets the demand, the new product development ability, has the bad record, the historical project performance, management system and management level, service level, human resource level, internal information processing level, historical cooperation situation, cooperation will, corporate culture and strategic fit degree, financing support ability, information transmission ability, Enterprise green idea propaganda, product energy consumption or energy consumption ratio, green building project participation in construction, environmental protection and energy-saving product development investment, toxic and harmful raw materials use, green matter The use of flowing green packaging, the use of recycled materials/product recycling, and the treatment of industrial “three wastes” will all produce a series of advantages that cannot be matched by traditional relationships. Then, the whole supply chain competitiveness will be improved. This paper studies the selection and evaluation of the partners in the supply chain environment from the point of view of the current research situation of the cooperative relationship in the supply chain environment at home and abroad. Based on the relevant research results at home and abroad, according to certain principles and methods, combined with experts’ evaluation of the future trend of qualitative indicators, a set of evaluation index system of supply chain partners is constructed. The standardized treatment of evaluation index is given. By comparing and analyzing the advantages and disadvantages of the common evaluation methods, the mature BP neural network is applied to the artificial neural network by using the artificial neural network evaluation method. MATLAB software is used to construct neural network. BP neural network is used for training and the trained neural network is used to evaluate an example. The results show that this method can solve the problem of partner selection and evaluation in supply chain environment, and improve the evaluation efficiency.

Smart Contracts for Service-Level Agreements in Edge-to-Cloud Computing

Abstract: The management of Service-Level Agreements (SLAs) in Edge-to-Cloud computing is a complex task due to the great heterogeneity of computing infrastructures and networks and their varying runtime conditions, which influences the resulting Quality of Service (QoS). SLA-management should be supported by formal assurances, ranking and verification of various microservice deployment options. This work introduces a novel Smart Contract (SC) based architecture that provides for SLA management among relevant entities and actors in a decentralised computing environment: Virtual Machines (VMs), Cloud service consumers and Cloud providers. Its key components are especially designed SC functions, a trustless Smart Oracle (Chainlink) and a probabilistic Markov Decision Process. The novel architecture is implemented on Ethereum ledger (testnet). The results show its feasibility for SLA management including low costs operation within dynamic and decentralised Edge-to-Cloud federations.

Design of Modern Supply Chain Networks Using Fuzzy Bargaining Game and Data Envelopment Analysis

Abstract: This article proposes a novel methodology for multistage, multiproduct, multi-item, and closed-loop Supply Chain Network (SCN) design under uncertainty. The method considers that multiple products are manufactured by the SCN, each composed by multiple items, and that some of the sold products may require repair, refurbishing, or remanufacturing activities. We solve the two main decisions that take place in the medium-/short-term planning horizon, namely partners’ selection and allocation of the received orders among them. The partners’ selection problem is solved by a cross-efficiency fuzzy Data Envelopment Analysis technique, which allows evaluating the efficiency of each SCN member and ranking them against multiple conflicting objectives under uncertain data on their performance. Then, according to the estimated customers’ demand, the order allocation problem is solved by a fuzzy bargaining game problem, where each SCN actor behaves to simultaneously maximize both its own profit and the service level of the overall SCN in terms of efficiency, costs, and lead time. An illustrative example from the literature is finally presented. Note to Practitioners —We present a decision tool to address the optimal design, performance evaluation, and continuous improvement of modern cooperative SCNs. We propose an effective method to jointly solve the members’ selection and the orders’ allocation, considering the complex structure of modern SCNs, the multiobjective nature of the problems, and the uncertainty characterizing economic markets. Competition within SCNs stages and cooperation along the chain are considered, with the aim to improve both financial and environmental sustainability, while ensuring the highest service levels to customers.

Intelligent decision model of road maintenance based on improved weight random forest algorithm

Abstract: The routine maintenance and rehabilitation of road pavement is vital to keep up with the service level and bearing capacity However, the current problem is that, with the continuous increase of th

Influence of logistic service level on multichannel decision of a two-echelon supply chain

Abstract: This paper investigates the channel structure and pricing problem of a two-echelon supply chain consisting of a manufacturer and a retailer. There are four common channel structures: (1) traditiona...

The value of information sharing for platform-based collaborative vehicle routing

Abstract: Cooperation is important in order to find efficient vehicle routing solutions for the growing transportation market. Increasingly, platforms emerge as facilitators for this kind of collaborative transportation. However, individual actors connected to a platform might refuse to share (parts of) their information due to reasons of competition. Though the need for realistic information sharing models is widely acknowledged by transportation researchers and practitioners, the precise value of such information is mostly unknown. We investigate the quality of solutions that can be obtained when different types and levels of carrier data are available. We consider an auction-based Multi-Agent System to solve large-scale, dynamic pickup and delivery problems, and vary whether carriers’ positions or route plans are available, and whether carriers are fully cooperative or more competitive in placing their bids by sharing or hiding their marginal costs. In total, we evaluate 9 different information sharing policies. The availability of vehicle position and route plan information turns out to be important for decreasing total route costs, and sharing marginal costs has a positive impact on service level. We provide detailed insights into trade-offs of carriers’ confidentiality concerns and a range of system performance objectives (service level, travel costs, and carrier profits) under different circumstances (various numbers of auctions, penalties for rejected orders, emission or congestion fees, and different problem characteristics). Based on these results, platform providers can stimulate sharing of certain information to improve the total system efficiency.