Knowledge that Transforms

We investigate the revenue impact of a new Price Setting Method (PSM) and compare it with the industry standard Bid Price Method (BPM). This comparison is performed via a simulation that was validated by a major hotel chain. In 27 out of the 32 cases, the PSM outperformed the BPM based on statistically significant tests. The PSM produces an average revenue increase of 34%, which can be thought of as an upper bound on the realistic revenue increase.

This paper presents a theoretical framework for measuring volume flexibility and relating these measures to firm performance. We develop four metrics using the principle that a volume flexible firm can handle similar levels of uncertainty (as measured by sales variability) with smaller fluctuations in inputs (as measured by variability in cost of goods sold and variability in inventory levels). Then, using 20 years of Compustat data on 550 firms in the capital goods industry, we find that on three of four process‐based measures, small firms are more volume flexible. However, when we incorporate financial performance into our fourth metric, we find that large firms are more volume flexible. We conclude that, to be volume flexible is one thing, but to benefit from this flexibility, firms need to focus on the cost of being flexible.

The successful development of breakthrough products with environmental attributes can not only create competitive advantage through operations excellence but also benefit the environment. This paper proposes a comprehensive scenario‐driven method with detailed implementation steps for planning and developing breakthrough products with environmental attributes. A case study based on the development process of biotechnology products is presented to show the applications of the method and the resulting importance of flexibility as a key ingredient in operations strategy. The paper also discusses various operational, marketing, technological, economic, and environmental issues concerning the development of biotechnology products, an area that could have a significant impact on both human health and the natural environment.

Many telephone call centers that experience cyclic and random customer demand adjust their staffing over the day in an attempt to provide a consistent target level of customer service. The standard and widely used staffing method, which we call the stationary independent period by period (SIPP) approach, divides the workday into planning periods and uses a series of stationary independent Erlang‐c queuing models—one for each planning period—to estimate minimum staffing needs. Our research evaluates and improves upon this commonly used heuristic for those telephone call centers with limited hours of operation during the workday. We show that the SIPP approach often suggests staffing that is substantially too low to achieve the targeted customer service levels (probability of customer delay) during critical periods. The major reasons for SIPP‘ s shortfall are as follows: (1) SIPP's failure to account for the time lag between the peak in customer demand and when system congestion actually peaks; and (2) SIPP’ s use of the planning period average arrival rate, thereby assuming that the arrival rate is constant during the period. We identify specific domains for which SIPP tends to suggest inadequate staffing. Based on an analysis of the factors that influence the magnitude of the lag in infinite server systems that start empty and idle, we propose and test two simple “lagged” SIPP modifications that, in most situations, consistently achieve the service target with only modest increases in staffing.

In this paper we review the literature on appointment policies, specifically in terms of the objective function commonly used and the assumptions made about the behavior of demand. First, we provide an economic framework to analyze the problem. Based on this framework we make a critical analysis of the objective functions used in the literature. We also question the validity of the assumption made throughout the literature that demand is exogenous and independent of customers' waiting times. We conclude that the objective functions used in the literature are appropriate only in the case of a central planner facing a demand that is unresponsive to waiting time. For other scenarios, such as a private server facing a demand that does react to waiting time, these objective functions are only shortcuts for the real objective functions that must be used. A more general model is then proposed that fits these scenarios well. Finally, we determine the impact of using the literature's objective functions on optimal appointment policies.

Several approaches to the widely recognized challenge of managing product variety rely on the pooling effect. Pooling can be accomplished through the reduction of the number of products or stock‐keeping units (SKUs), through postponement of differentiation, or in other ways. These approaches are well known and becoming widely applied in practice. However, theoretical analyses of the pooling effect assume an optimal inventory policy before pooling and after pooling, and, in most cases, that demand is normally distributed. In this article, we address the effect of nonoptimal inventory policies and the effect of nonnormally distributed demand on the value of pooling. First, we show that there is always a range of current inventory levels within which pooling is better and beyond which optimizing inventory policy is better. We also find that the value of pooling may be negative when the inventory policy in use is suboptimal. Second, we use extensive Monte Carlo simulation to examine the value of pooling for nonnormal demand distributions. We find that the value of pooling varies relatively little across the distributions we used, but that it varies considerably with the concentration of uncertainty. We also find that the ranges within which pooling is preferred over optimizing inventory policy generally are quite wide but vary considerably across distributions. Together, this indicates that the value of pooling under an optimal inventory policy is robust across distributions, but that its sensitivity to suboptimal policies is not. Third, we use a set of real (and highly erratic) demand data to analyze the benefits of pooling under optimal and suboptimal policies and nonnormal demand with a high number of SKUs. With our specific but highly nonnormal demand data, we find that pooling is beneficial and robust to suboptimal policies. Altogether, this study provides deeper theoretical, numerical, and empirical understanding of the value of pooling.

We study how an updated demand forecast affects a manufacturer's choice in ordering raw materials. With demand forecast updates, we develop a model where raw materials are ordered from two suppliers—one fast but expensive and the other cheap but slow—and further provide an explicit solution to the resulting dynamic optimization problem. Under some mild conditions, we demonstrate that the cost function is convex and twice‐differentiable with respect to order quantity. With this model, we are able to evaluate the benefit of demand information updating which leads to the identification of directions for further improvement. We further demonstrate that the model applies to multiple‐period problems provided that some demand regularity conditions are satisfied. Data collected from a manufacturer support the structure and conclusion of the model. Although the model is described in the context of in‐bound logistics, it can be applied to production and out‐bound logistics decisions as well.

ISO 14001 constitutes a major dilemma for many American firms. This new standard holds the promise of waste reduction and better process management, but the benefits and costs are very difficult to predict. This study attempts to identify and explain antecedents impacting the decision to pursue certification for some of the first plants certified in the United States. Using data from a large survey of U.S. managers and a Logit analysis, we find the factors influencing management decisions to actively pursue ISO 14001 certification to be distinctly different from those factors influencing management's decision not to pursue certification. For the latter, the decision is economically based; for the former, it is driven by other, more qualitative considerations.

The ability of telecommunication operators to focus successfully on the customer has proven to be one of the most competitive issues toward the end of the 20th century. The services management literature is short of theoretical and empirical studies on customer satisfaction measurement in the telecommunications industry. This, however, is contrary to the industry practice since almost all major telecommunications companies around the world gather information about customer satisfaction and other related information about the quality of their services. Our research focuses on the customer satisfaction function of residential customers of a major European telecommunications company. Customer satisfaction is seen as the overall performance of the telecommunications company stemming from adequate service provision, value for money, loyalty, and relationship management. The antecedents of the performance of the organization are obtained from the contact points between the customers and the service points of the telecommunications company.

In this paper we consider the problem of designing a mixed assembly‐disassembly line for remanufacturing. That is, parts from the disassembly and repair of used products can be used to build “new” products. This is a problem common to many OEM remanufacturers, such as Xerox or Kodak. We study two main configurations, under the assumption that the disassembly sequence is exactly the reverse of the assembly sequence. Under a parallel configuration, there exist two separate dedicated lines, one for assembly and one for disassembly, which are decoupled by buffers—from both disassembly operations, which have preference, as well as parts from an outside, perfectly reliable supplier. Under a mixed configuration, the same station is used for both disassembly and assembly of a specific part. The problem is studied using GI/G/c networks, as well as simulation. Due to a loss of pooling, we conclude that the parallel configuration outperforms the mixed line only when the variability of both arrivals and processing time are significantly higher for disassembly and remanufacturing than for assembly. Via a simulation, we explore the impact of having advanced yield information for the remanufacturing parts. We find that advanced yield information generally improves flow times; however, there are some instances where it lengthens flow times.