Showing papers on "Service level published in 2016"

Disruption-driven supply chain (re)-planning and performance impact assessment with consideration of pro-active and recovery policies

Abstract: In this study, an approach to re-planning the multi-stage supply chain (SC) subject to disruptions is developed. We analyze seven proactive SC structures, compute recovery policies to re-direct material flows in the case of two disruption scenarios, and assess the performance impact for both service level and costs with the help of a SC (re)planning model containing elements of system dynamics and linear programming. In the result, an explicit connection of performance impact assessment and SC plan reconfiguration issues with consideration of the duration of disruptions and the costs of recovery has been achieved.

Structural quantification of the ripple effect in the supply chain

Abstract: In recent years, remarkable advancements have been achieved in quantitative analysis methods for supply chain design (SCD). Typically, cost or service level optimisation has been included in the objective functions. At the same time, supply chain managers face the ripple effect that arises from vulnerability, instability and disruptions in supply chains. This research aimed to quantify the ripple effect in the supply chain from the structural perspective. The research agenda of this study includes issues of integrating operability objectives as new key performance indicators, e.g. resilience, stability, robustness into SCD decisions. The research is based on a simultaneous consideration of both static structural properties of SCD and execution dynamics subject to uncertainty and disruptions. Due to high dimensionality of real SCD problems, such integration can hardly be implemented in only one model. In this study, an original two-model multi-criteria approach is proposed in order to assess the potential ...

Service channel choice for supply chain: : Who is better off by undertaking the service?

Abstract: In recent years, increasing interests have arisen in adding product value through the provision of service This study considers the problem in which a demand-enhancing service can be provided by different supply chain parties, resulting in four alternative service channels: (a) manufacturer undertaking service, namely M-channel, (b) retailer undertaking service, namely R-channel, (c) manufacturer outsourcing service to third-party (3P), namely M-3P-channel, and (d) retailer outsourcing service to 3P, namely R-3P-channel We quantitatively model these service channels and derive the optimal decisions with the following observations: When the service costs are equal for the different parties, there is a conflict in service channel choice since both the manufacturer and the retailer prefer to undertake the service or hire the 3P by themselves, although M-channel generates the highest market demand and system profit; When the service costs are different among these parties, R-channel and 3P-channels are more preferable if the service cost is less sensitive to the service level and if the market demand is more sensitive to the service level We also conduct an empirical study to test some of the insights developed from the analytical models; our empirical findings support the analytical results

On the risk-averse optimization of service level in a supply chain under disruption risks

Abstract: The worst-case optimization of service level in the presence of supply chain disruption risks is considered for the two different service levels measures: the expected worst-case demand fulfillment rate and the expected worst-case order fulfillment rate. The optimization problem is formulated as a joint selection of suppliers and stochastic scheduling of customer orders under random disruptions of supplies. The suppliers are located in different geographic regions and the supplies are subject to random local and regional disruptions. The obtained combinatorial stochastic optimization problem is formulated as a mixed integer program with conditional service-at-risk as a worst-case service level measure. The risk-averse solutions that optimize the worst-case performance of a supply chain are compared for the two service level measures. In addition, to demonstrate the impact on the cost in the process of optimizing the worst-case service level, a joint optimization of expected cost and conditional service-at...

High availability in clouds: systematic review and research challenges

Abstract: Cloud Computing has been used by different types of clients because it has many advantages, including the minimization of infrastructure resources costs, and its elasticity property, which allows services to be scaled up or down according to the current demand. From the Cloud provider point-of-view, there are many challenges to be overcome in order to deliver Cloud services that meet all requirements defined in Service Level Agreements (SLAs). High availability has been one of the biggest challenges for providers, and many services can be used to improve the availability of a service, such as checkpointing, load balancing, and redundancy. Beyond services, we can also find infrastructure and middleware solutions. This systematic review has as its main goal to present and discuss high available (HA) solutions for Cloud Computing, and to introduce some research challenges in this area. We hope this work can be used as a starting point to understanding and coping with HA problems in Cloud.

Integrated supply, production and distribution scheduling under disruption risks

Abstract: This paper presents a bi-objective stochastic mixed integer programming approach for a joint selection of suppliers and scheduling of production and distribution in a multi-echelon supply chain subject to local and regional disruption risks. Two conflicting problem objectives are minimization of cost and maximization of service level. The three shipping methods are considered for distribution of products: batch shipping with a single shipment of different customer orders, batch shipping with multiple shipments of different customer orders and individual shipping of each customer order immediately after its completion. The stochastic combinatorial optimization problem is formulated as a time-indexed mixed integer program with the weighted-sum aggregation of the two objective functions. The supply portfolio is determined by binary selection and fractional allocation variables while time-indexed assignment variables determine the production and distribution schedules. The problem formulation incorporates supply–production, production–distribution and supply–distribution coordinating constraints to efficiently coordinate supply, production and distribution schedules. Numerical examples modelled after an electronics supply chain and computational results are presented and some managerial insights are reported. The findings indicate that for all shipping methods, the service-oriented supply portfolio is more diversified than the cost-oriented portfolio and the more cost-oriented decision-making, the more delayed the expected supply, production and distribution schedules.

Index numbers for monitoring transit service quality

Abstract: The measurement of transit service quality is very important for guaranteeing a transport supply characterized by satisfactory service levels for the passengers. Even more important is the monitoring of the levels of service quality over time, which can be very useful to determine if the goals established by the transport planners are being met or exceeded. The status and evolution of transit service quality can be monitored through periodic and regular updating of the opinions expressed by the passengers about the service during the well-known Customer Satisfaction Surveys, allowing the effect of policies to be evaluated and specific interventions to be introduced. In this work, just the issue of monitoring service quality based on users’ opinions is approached, and the index numbers usually applied in the economic and industrial field are proposed for this purpose. Index numbers permit to study the fluctuations or variations of a variable or more variables over time, providing a powerful measurement for making comparisons and predictions of the analyzed concept. The index numbers were calculated on the basis of data collected from Customer Satisfaction Surveys addressed to the passengers of the metropolitan public service of Granada (Spain). The analyzed time period has been established from 2007 to 2013. Interesting results derive from the calculation of the index numbers. Since both perceptions and importance rates are considered in this methodology, the results can inform, not only on the satisfaction tendencies but also on the trend on customers’ priorities, which is actually the expected quality. Therefore, policies could more efficiently be designed to adjust the service to the users’ real needs.

Evaluation of e-commerce websites using fuzzy hierarchical TOPSIS based on E-S-QUAL

Abstract: Proposing a fuzzy hierarchical TOPSIS based on E-S-QUAL for evaluating e-commerce.Utilizing fuzzy hierarchical TOPSIS to reflect the hierarchical structure.Applying E-S-QUAL for assessing e-commerce website service quality effectively.Conducting the case study to understand in a better way the evaluation process.Conducting a validation test with other MCDM to verify the robustness of method. In the wake of the rapid emergence of e-commerce, its evaluation is of great theoretical and practical importance. Among the various types of e-commerce, business-to-consumer (B2C) e-commerce has become a key, and especially influential, retailing channel. Its ascendancy raises core issues with respect to how the customer is to be satisfied by, and therefore inclined to trust, e-commerce websites. B2C e-commerce website evaluation, therefore, is an important related issue. First, while a number of studies have studied B2C e-commerce website evaluation using various multiple-criteria-decision-making (MCDM) methods, they have focused only on the perceived service quality of B2C e-commerce websites. In fact, it is generally recognized that service quality is determined by the difference between the expected service level (which expectation is derived from information obtained before the service experience) and the actual, perceived service level; this concept, then, should be also be afforded due consideration in B2C e-commerce website evaluation. Second, among the various MCDM approaches, TOPSIS, which involves the consideration of both the positive-ideal solution (PIS) and the negative-ideal solution (NIS), is especially pertinent to the complex decision-making entailed in the evaluation of B2C e-commerce websites. Third, the human element of subjectivity in the evaluation of B2C e-commerce websites needs to be considered in order to enable modeling of real-life website-evaluation situations. Finally, the hierarchical structure of the evaluation criteria between the main dimensions and their sub-criteria should be considered. To reflect these issues, in this paper, we present a fuzzy hierarchical TOPSIS based on E-SERVQUAL (E-S-QUAL). This approach effectively considers the raised issues and preserves the core concept of E-S-QUAL (the extended version of SERVQUAL) for measurement of electronic service quality in the e-commerce environment. The empirical case study of B2C e-commerce provides the researchers and practitioners to understand in a better way the evaluation process from a practical point of view. In addition, core finding of this study is that the comparison results with other MCDM methods further verify the robustness of the proposed approach. It implies that this method potentially can be applied to performance evaluation of similar service sectors.

Stackelberg Game Approach for Energy-Aware Resource Allocation in Data Centers

Abstract: Data centers hosting distributed computing systems consume huge amounts of electrical energy, contributing to high operational costs, whereas the utilization of data centers continues to be very low. Moreover, a data center generally consists of heterogeneous servers with different performance and energy. Failure to fully consider the heterogeneity of servers will lead to both sub-optimal energy saving and performance. In this study, we employ game theoretic approaches to model the problem of minimizing energy consumption as a Stackelberg game. In our model, the system monitor, who plays the role of the leader, can maximize profit by adjusting resource provisioning, whereas scheduler agents, who act as followers, can select resources to obtain optimal performance. In addition, we model the problem of minimizing average response time of tasks as a noncooperative game among decentralized scheduler agents as they compete with one another in the sharing resources. Several algorithms are presented to implement the game models. Simulation results demonstrate that the proposed technique has immense potential to improve energy efficiency under dynamic work scenarios without compromising service level agreements.

An integrated approach for airline scheduling, aircraft fleeting and routing with cruise speed control

Abstract: To place an emphasis on profound relations among airline schedule planning problems and to mitigate the effect of unexpected delays, we integrate schedule design, fleet assignment and aircraft routing problems within a daily planning horizon while passengers’ connection service levels are ensured via chance constraints. We propose a nonlinear mixed integer programming model due to the nonlinear fuel consumption and CO2 emission cost terms in the objective function, which is handled by second order conic reformulation. The key contribution of this study is to take into account the cruise time control for the first time in an integrated model of these three stages of airline operations. Changing cruise times of flights in an integrated model enables to construct a schedule to increase utilization of fuel efficient aircraft and even to decrease total number of aircraft needed while satisfying the same service level and maintenance requirements for aircraft fleeting and routing. There is a critical tradeoff between the number of aircraft needed to fulfill the required flights and overall operational expenses. We also propose two heuristic methods to solve larger size problems. Finally, computational results using real data obtained from a major U.S. carrier are presented to demonstrate potential profitability in applying the proposed solution methods.

The Impact of Supplier Inventory Service Level on Retailer Demand

Abstract: To set inventory service levels, suppliers must understand how changes in inventory service level affect demand. We build on prior research, which uses analytical models and laboratory experiments to study the impact of a supplier's service level on demand from retailers, by testing this relationship in the field. We analyze a field experiment at the supplier Hugo Boss to deter- mine how the supplier's inventory service level affects demand from its retailer customers. We find increases in historical fill rate to be associated with statistically significant and managerially substantial increases in current retailer orders (i.e., demand, not just sales). Specifically, a one percentage point increase in fill rate, measured over the prior year, is associated with a statistically significant 11% increase in current retailer demand, controlling for other factors that might affect retailer demand. We explore the drivers of this demand increase, including changes in retailer assortment and order frequency. We discuss features of a retail buyer's decision context identified through our field work that may explain the magnitude of the relationship we observe.

To select or to combine? The inventory performance of model and expert forecasts

Abstract: Demand forecasting is a crucial input of any inventory system. The quality of the forecasts should be evaluated not only in terms of forecast accuracy or bias but also with regards to their inventory implications, which include the impact on the total inventory cost, the achieved service levels and the variance of orders and inventory. Forecast selection and combination are two very widely applied forecasting strategies that have shown repeatedly to increase the forecasting performance. However, the inventory performance of these strategies remains unexplored. We empirically examine the effects of forecast selection and combination on inventory when two sources of forecasts are available. We employ a large data-set that contains demands and (statistical and judgmental) forecasts for multiple pharmaceutical stock keeping units. We show that forecast selection and simple combination increase simultaneously the forecasting and inventory performance.

Coordinating a two-echelon supply chain under production disruption when retailers compete with price and service level

Abstract: Business competition among the individual retailers in a supply chain is a common event, and it plays an important role in making supply chain decisions. In a newsvendor setting, this paper investigates a supply chain system with a sole manufacturer who may face a production disruption, and two independent retailers who compete each other with price and service level. The demand at each retailer is random but influenced by the prices and service levels of both the retailers. We formulate the decentralized system as a manufacturer-Stackelberg game and characterize the equilibrium behaviour of the system. We further show that a wholesale price discount scheme can coordinate the supply chain and achieve win–win outcome. A numerical example is given to illustrate the theoretical results and study the impact of production yield due to production disruption on the performance of the supply chain.

Inventory Service Target in Quick Response Fashion Retail Supply Chains

Abstract: Different fashion brands have different inventory service targets. To achieve the desirable inventory service level without the need of holding a lot of inventory, fashion companies commonly adopt the quick response practice. In this paper, we conduct an analytical study on the influence played by the inventory service target on quick response fashion retail supply chains. To be specific, we consider the case when the fashion retailer, who is the channel leader, aims to achieve an inventory service target in its inventory planning. We explore impacts of the inventory service-targeted quick response program, in terms of expected profit, and profit risk on the fashion retailer, the fashion manufacturer, and the fashion supply chain system. We also examine the quick response's impact on social welfare. We show how three practical contracts, namely, the fixed-fee contract, the wholesale pricing contract, and the product variety contract, can be employed to achieve a win-win situation in the fashion retail supply chain system with the adoption of the inventory service-targeted quick response program. Closed-form managerial insights on how the inventory service target affects the expected benefit of quick response, the reduction of profit risk under quick response, the expected gain of social welfare, the achievability of the win-win situation, and the setting of contractual parameters, are derived.

Inventory management, service level and safety stock

Abstract: There are many studies that emphasize as a first objective of inventory management to minimize the value invested in inventory because it has a direct impact on return on assets. This approach is not fully correct. The actual objective is to determine the value and the mix of inventory that support a high service level for customers and that maximizing the companiesi?½ financial performance. Many companies look at their own demand fluctuations and assume that there are too many variables to predict demand variability. Service level is used in inventory management to measure the performance of inventory policies and represents the probability of not being stock-out and not losing sales. Safety stock is inventory that is carried to prevent stock outs. Safety stock determinations are not intended to eliminate all stock outs, just majority of them. Companies choose to keep safety stock level high as a buffer against demand variability resulting in inefficiencies and high working capital requirements. Safety stock optimization enables companies to achieve savings and increase inventory turns.

The Design of Experiential Services with Acclimation and Memory Decay: Optimal Sequence and Duration

Abstract: For many consumer-intensive (i.e., business-to-consumer) services, delivering memorable customer experiences is a source of competitive advantage. Yet there are few guidelines available for designing service encounters with a focus on customer satisfaction. In this paper, we show how experiential services should be sequenced and timed to maximize the satisfaction of customers who are subject to memory decay and acclimation. We find that memory decay favors positioning the highest service level near the end, whereas acclimation favors maximizing the gradient of service level. Together, they maximize the gradient of service level near the end. Although memory decay and acclimation lead to the same design individually, they can act as opposing forces when considered jointly. Overall, our analysis suggests that short experiences should have activities scheduled as a crescendo and duration allocated primarily to the activities with the highest service levels, whereas long experiences should have activities sch...

Understand Your Chains: Towards Performance Profile-Based Network Service Management

Abstract: Allocating resources to virtualized network functions and services to meet service level agreements is a challenging task for NFV management and orchestration systems. This becomes even more challenging when agile development methodologies, like DevOps, are applied. In such scenarios, management and orchestration systems are continuously facing new versions of functions and services which makes it hard to decide how much resources have to be allocated to them to provide the expected service performance. One solution for this problem is to support resource allocation decisions with performance behavior information obtained by profiling techniques applied to such network functions and services. In this position paper, we analyze and discuss the components needed to generate such performance behavior information within the NFV DevOps workflow. We also outline research questions that identify open issues and missing pieces for a fully integrated NFV profiling solution. Further, we introduce a novel profiling mechanism that is able to profile virtualized network functions and entire network service chains under different resource constraints before they are deployed on production infrastructure.

Impact of Individual and Organizational Variables on Quality of Life

Abstract: The general goal of this study consists of analyzing the influence of different types of human services in the quality of life of their nested users. Several multilevel models were proposed to test for significant differences not only in the overall quality of life score, but also in each of the eight core domains. Participants included 11,624 users of social and human services and the assessment quality of life instrument was the GENCAT Scale. Variables that were studied in the different models were gender, age, and diagnostic group (elderly, intellectual disability, physical disability, mental health problems, and chemical dependency) at the individual user level (level 1: individual), while type of services—in terms of the main population addressed by their supports (i.e. the aforementioned groups)—was studied at service level (level 2: organizational). In order to explain differences, individual characteristics were introduced first, types of services were introduced next, and finally joint individual and service variables were introduced in a single model. The main results of this study were that personal and organizational variables exhibited a different level of influence on users’ quality of life; and also that the type of services significantly influenced the quality of life of its users. The results of this study lead to practical implications for services providing support to these diagnostic groups, especially for those interested in managing, assessing, and improving quality of life related personal outcomes at the user level as well as quality enhancement at the organizational level.

The Impact of Supplier Inventory Service Level on Retailer Demand

Abstract: To set inventory service levels, suppliers must understand how changes in inventory service level affect demand. We build on prior research, which uses analytical models and laboratory experiments to study the impact of a supplier's service level on demand from retailers, by testing this relationship in the field. We analyze a field experiment at the supplier Hugo Boss to determine how the supplier's inventory service level affects demand from its retailer customers. We find increases in historical fill rate to be associated with statistically significant and managerially substantial increases in current retailer orders i.e., demand, not just sales. Specifically, a one percentage point increase in fill rate, measured over the prior year, is associated with a statistically significant 11% increase in current retailer demand, controlling for other factors that might affect retailer demand. We explore the drivers of this demand increase, including changes in retailer assortment and order frequency. We discuss features of a retail buyer's decision context identified through our field work that may explain the magnitude of the relationship we observe.