Desired Service Level Research Articles

Targeting Service to Your Cusomr

Most hoteliers will answer "service" when asked what makes them better than their competition. But focusing on service is not the same as focusing on the customer. Service must be defined relative to the customers' needs, and the price of a room must reflect the guests' expectations regarding the desired level of service. Most customers are unwilling to pay for amenities they don't want and will avoid those properties where high rates aren't clearly related to value. To develop a service strategy, first identify the markets to be served, identify what it is your customers want and what they expect, and choose the optimal mix and level of service for those markets. Next, evaluate your current service performance and make any adjustments that ensure you're offering the right service at the right price. Finally, make it easy for your guests to give you feedback.

Network security issues

Increasingly, distributed processing is used to achieve the availability and processing power required by today's information technology systems. Networks are an important element in this drive towards more responsive systems. These systems can vary in size from a few desk top machines connected together in a single office to a complex of mainframes, controllers and terminals owned by a variety of organizations worldwide. It is shown that much work has been done to establish the security services that can be provided to users of these networks. If these services are to achieve their desired level of service, however, careful attention must be paid to the way they are planned, implemented and, in particular, the way in which they are managed.

A Customer Satisfaction Approach to Introducing Physical Distribution in the Principles of Marketing Course

Traditional presentations of physical distribution in a principles of marketing course commonly focus on the activities of distribution without effectively integrating them into the marketing mix. This article offers instructors an integrative framework for presenting physical distribution activities as a means of achieving desired levels of customer service and ultimately customer satisfaction.

The Importance of Retirement Community Characteristics: Viewpoint of a Maturing Population

This study delineates the relative importance of retirement community characteristics among a preretirement population. The data were collected from an independent, random, age-stratified sample of employees from nine land-grant universities. Respondents were asked to identify the degree of importance that each of twelve community characteristics would have in determining their community-of-choice for the first ten years of retirement. The characteristics deemed more important by respondents included: medical facilities, low utility rates, low cost of living, library facilities, and recreational facilities. Medical facilities were important to 96 percent of respondents. Chi-square and gamma analyses were used to determine how income, age, and self-reported health affected the desired level of medical service. Those with higher incomes, those who were older, and those in poorer health wanted higher levels of medical service. Eighty-six percent required that a hospital be within a 20 to 30 minute drive. Discriminant analyses were used to identify variables which could predict the importance of a community characteristic to a respondent. The desired age mix in a prospective retirement community was the most predictive in five functions: libraries, educational opportunities, malls, medical facilities, and volunteer opportunities. Other factors that proved useful predictors were income, age, education, and spouse’s education. Communities who wish to attract and retain retirees need to consider the specific characteristics of the retirement group they want to attract.

Estimation of Inventory Re-Order Levels Using the Bootstrap Statistical Procedure

It can be difficult to set the reorder point in an inventory system because often one does not have much knowledge of the lead-time demand (LTD)distribution. A frequent practice is to assume a “standard” distribution, such as the Normal. The reorder point is then taken as the p-th fractile of that standard distribution, where (1 −p) is the specified probability of stockout during a replenishment cycle. When the desired service level p is high and the “true” LTD distribution is skewed, previous research has shown that the reorder point and inventory costs are strongly affected by the shape of the assumed LTD distribution. Ideally, no assumptions about this distribution should be necessary. One such “distribution-free” approach is the bootstrap procedure. Beginning with a single sample W = {x1x2,…,xn} of lead-time demand, the bootstrap repeatedly samples with replacement from W, A family of bootstrap samples of size n is thereby created, each sample furnishing an estimate Xp∗ of the p-th fractile of the LTD distribution. The probability mass function of these values yields the bootstrap estimate of the reorder point [[Xcirc]p = E(Xp)]. We employ the bootstrap procedure to determine the reorder point s in an (s,Q) system for desired service levels p = 0.8, 0.9 and 0.95. The bootstrap and normal approaches are compared using LTD data simulated from a number of populations with varying tail shapes. Analyses of variance are performed to compare the estimated reorder points across various levels of distribution form, coefficient of variation, sample size and service level. The relative performance of the bootstrap and normal approaches is also discussed in terms of a cost model. We found it preferable to use the bootstrap procedure in any situation where a “non-standard’ LTD distribution, e.g. a bimodal one, is suspected. If the distribution actually is a standard shape, such as normal or lognormal, the bootstrap estimate is often as good as the normal. Situations are also identified where the bootstrap procedure should not be used, and suggestions are made for further research.

A model for use in the rationing of inventory during lead time

While the traditional solution to the problem of meeting stochastically variable demands for inventory during procurement lead time is through the use of some level of safety stock, several authors have suggested that a decision be made to employ some form of rationing so as to protect certain classes of demands against stockout by restricting issues to other classes. Nahmias and Demmy [10] derived an approximate continuous review model of systems with two demand classes which would permit an inventory manager to calculate the expected fill rates per order cycle for high-priority, low-priority, and total system demands for a variety of parameters. The manager would then choose the rationing policy that most closely approximated his fill-rate objectives. This article describes a periodic review model that permits the manager to establish a discrete time rationing policy during lead time by prescribing a desired service level for high-priority demands. The reserve levels necessary to meet this level of service can then be calculated based upon the assumed probability distributions of high- and low-priority demands over lead time. The derived reserve levels vary with the amount of lead time remaining. Simulation tests of the model indicate they are more effective than the single reserve level policy studied by Nahmias and Demmy.

Component Inventory Costs in an Assembly Problem with Uncertain Supplier Lead-Times

We present a generic study of inventory costs in a factory stockroom that supplies component parts to an assembly line. Specifically, we are concerned with the increase in component inventories due to uncertainty in supplier lead-times, and the fact that several different components must be present before assembly can begin. It is assumed that the suppliers of the various components are independent, that the suppliers' operations are in statistical equilibrium, and that the same amount of each type of component is demanded by the assembly line each time a new assembly cycle is scheduled to begin. We use, as a measure of inventory cost, the expected time for which an order of components must be held in the stockroom from the time it is delivered until the time it is consumed by the assembly line. Our work reveals the effects of supplier lead-time variability, the number of different types of components, and their desired service levels, on the inventory cost. In addition, under the assumptions that inventory holding costs and the cost of delaying assembly are linear in time, we study optimal ordering policies and present an interesting characterization that is independent of the supplier lead-time distributions.

Location of Inventories in an MRP Environment

ABSTRACTPrevious research on MRP systems has rarely considered at what level in a modular sub‐assembly product structure to hold inventories. Based on a simulation study of an MRP environment, we show that the correct decision concerning where to hold inventory depends on the variance in end‐item demand, the amount of inventory investment, and concomitantly, the desired level of customer service. In particular, for small investment in inventories and moderate end‐item demand variance, it is equally effective to hold inventories at the subassembly level or the end‐item level. But when end‐item demand variance is high, subassembly level inventories are better. As inventory investment grows, however, it is best to use a diversified approach of holding both subassembly and end‐item inventories, irrespective of end‐item demand variance. The robustness of these conclusions is validated by simulating a hypothetical firm that also uses safety time to hedge against uncertainties.

Equitable transit charges for multiadministration telecommunications networks

We study a multi-administration telecommunications network that is an abstraction of an international network. The nodes represent separate telecommunications administrations that are linked such that alternately-routed calls go through one tandem administration. The cost of the group of circuits between a pair of administrations is borne by them; and when a call between the pair is alternately routed through the tandem node, then the two administrations share the call revenue and pay transit fees to the tandem administration. The numbers of circuits between the administrations are selected to yield a least-cost network that provides a desired level of service, in terms of blocking probabilities, over an entire day. We address the problem of determining transit charges for the alternately-routed calls that are equitable for all of the administrations. Our approach is to derive such charges by equating the system-optimal circuit group sizes to certain hypothetical administration-optimal circuit group sizes. This approach may be of use in other system design problems involving cost sharing among several companies.

Interaction between frequency of rescheduling and the role of safety stock in material requirements planning systems

We describe how the frequency of rescheduling permitted in Material Requirements Planning (MBP) systems influences the impact of safety stock on system costs, and its effectiveness in maintaining desired levels of customer service. The results are obtained from approximate analytical models and simulation studies of a single product with stochastic demand and a two-level product structure. The results indicate that in some cases it may be more economical to reschedule infrequently and use safety stock as protection against demand variations. They also indicate that the effect of changing safety stock levels is much more predictable when rescheduling is infrequent, and that increasing safety stock may actually result in degraded performance when rescheduling is frequent.

Staffing and equipment decisions for services: An experimental analysis

AbstractMany service‐oriented firms face demand/work load variations that occur both within and between days, and seasonally during the year. These service firms tend to develop staffing plans based on peak periods, resulting in substantial idle time during low demand periods. To counter this, some firms hire part‐time employees to work peak periods to improve productivity. In this way, the cost per customer/transaction (unit) can be reduced.However, the staffing decision is more complex than just determining the number and timing of the work force. The development of good staffing plans must consider the impact of available work stations like telephone consoles and data entry terminals. To use effectively more personnel during peak periods, the firm must have sufficient work stations to assign this work force. Effective staff scheduling must consider simultaneously the work load variations, employ capabilities, and equipment requirements. This article presents a model that incorporates these factors into the decision‐making process and examines their interaction.The model analysis illustrates how uncertainty in work load forecasts and staffing flexibility influence expected cost performance and equipment requirements. A set of computer simulation experiments are conducted using operating data from the proof and encoding departments for Ohio National Bank and Chemical Bank. The results suggest that increased staffing flexibility reduces the needed equipment investment, since part time staff can be scheduled more conveniently to meet varying work loads. Also, basing capital equipment decisions on peak work load levels can substantially increase total operating costs. With these costs explicitly estimated, managers can weigh them against desired service level goals to determine the appropriate balance.

A Survey of Pedestrian Behaviour to determine Sidewalk Width under desirable Service Level

It has been considered that the minimum requirement of effective sidewalk width is 1. 5m. But it is not ideal under some conditions.This paper aims at a method to decide the sidewalk width considering three traffic conditions which often happen (pedestrian walks 1.with umbrella, 2. with fellows, 3. with baggages).The survey results are as follows: a. the width of one pedestrian with umbrella is 1.0m. b. in urban area, the rate of pedestrian who walk with fellows is about 20-50%. c. the with of one pedestrian carrying baggages is about 0.85m. d. on the sidewalk of 1.5-1.9m width, pedestrians are often forced to go into carrigeway to avoid conflicts with other pedestrians.After consideration of these behavior of pedestrians, we propose that 2.25m should be the desirable service level as the minimum width for sidewalks.

Chemical inventory and its relationship with the service level in an analytical lab

inventory of chemicals in an analytical laboratory is dependent upon the number of samples brought in and the types of analyses performed. Different analyses use different amount and kind of chemicals. The service level of an in-house analytical laboratory is very important to a company. If chemicals are not in stock and analyses not performed, it may cause loss of customers or products in the process development stages. With growing competition, proper control over the chemical inventories is absolutely essential. This paper discusses inventory policies for chemicals designed to maintain a desired service level in an analytical laboratory.

MRP with high uncertain yield losses

AbstractCertain manufacturing systems, notably those in high technology precision casting and integrated circuit production suffer from process yield losses which are both significant in quantity terms and are also highly unpredictable. This poses special problems for the provisioning of materials to support a manufacturing program and for the detailed scheduling necessary to update the priorities of work in process batches as losses occur. This paper establishes a framework of analysis to handle this problem in MRP logic. It describes the mechanisms available and discusses their relevance to the market environments in which the company is operating.The key conclusion of this paper is that different solutions are required for different market circumstances. The four key strategies developed are: A: For continuous schedules, make‐for‐stock: Use mean yield rate and fixed buffer stocks. B: For continuous schedules, make‐to‐order: Use mean yield rate, fixed buffers and a yield to finish monitoring system. C1: For single batch production make‐to‐order: As for B but using a desired service level yield rate. C2: For multiple batch production, make‐to‐order: As B but using a variable yield rate by batch.The implementation of each of these is described in relation to the business objectives of cost effectiveness and customer satisfaction.

Goal Programming and Financial Planning Models for Highway Rehabilitation

This paper examines the problem of capital budgeting in the area of highway maintenance. Emphasis is placed on specific, real-world user concerns relating to standard capital budgeting models, and suggestions are made for improving planning in this area. A two-phase approach to capital budgeting is suggested as a mechanism for resolving some of these concerns. In phase 1 a financial planning model is used as a means of determining appropriate budget levels. In phase 2 a goal programming model for achieving desired levels of service is given. A brief description is given of such a two-phase system currently being implemented in a Canadian transport ministry.

Inventory Control Using A Service Constraint on the Expected Duration of Stockouts

Abstract This paper addresses the selection of a reorder point under a management-specified, maximum expected duration of stockout during a replenishment lead time. The cases of normal and Poisson demand are considered. In both cases graphical aids are developed, allowing easy determination of the reorder point so as to achieve a desired service level. The entire probability distribution of the durations of stockouts is also developed in each case.

Determining Reorder Points When Demand is Lumpy

Lumpy or sporadic demand patterns with highly skewed distributions are common in parts and supplies types of stockholdings, and much of available inventory control methodology is not appropriate for such items. This paper presents a simple, easily used regression model to calculate order points for lumpy items from knowledge of demand parameters and the desired service level. It is derived from the particular compound Poisson distribution commonly called “stuttering Poisson.” Results are derived and presented in the following framework, though application is not limited to these conditions. The control discipline is the order quantity, order point (Q, R) approach with continuous review. Lead time is assumed to be known and constant. An assigned service level is assumed based on fraction of demand supplied without backorder. Joint optimization of Q and R is not addressed, but rather order point is based on an independently calculated order quantity. Forecasting methods are not addressed, but the mean and variance of lead time demand forecasts are assumed available.

Stockout Cost Models: Empirical Tests in a Retail Situation

DISPLAY space and merchandise inventories are two of the most important assets a retail firm possesses. A body of research literature on methods of optimizing the use of display space and optimizing inventory levels for particular items has developed over time.' These studies have typically assumed the objectives of optimizing profits from display space or minimizing the costs of acquiring and carrying inventory, given a desired level of customer service.

Municipal Water Planning—Mixed Integer Approach

The mixed integer programming approach to selection of municipal water source-facility combinations overcomes many of the limitations of linear programming. The mixed integer concept allows separation of capital investment and operating costs for detailed analysis of the least cost of insuring desired level of service. Standard of pipe and equipment require discrete, not continuous variables. Chance constrained programming allows uncertainty in both supply and demand to be considered in the model. An optimizing algorithm based upon the Branch Bound concept of mixed integer programming selects the optimum combination of source-facilities from all possible alternatives. The procedure is demonstrated by developing a model for an example problem and the optimum solution is given.

Bayesian Determination of the Reorder Point of a Slow Moving Item

Consider an inventory item for which the procurement (or production setup) lead time is nonzero. One of the commonly used methods of determining the reorder point of such an item is to specify the probability of a stockout or a desired service level (fraction of demand that is to be instantaneously satisfied) and then select the reorder level that will provide such service. However, such an approach has assumed that the probability distribution of demand during the lead time is exactly known. In many inventory situations this assumption is not justified, particularly in the case of a slow moving item with limited available sales history. For such a situation this paper explores the use of a Bayesian approach to selecting a reorder point.