On the Diaconis-Gangolli Markov chain for sampling contingency tables with cell-bounded entries

The problems of uniformly sampling and approximately counting contingency tables have been widely studied, but efficient solutions are only known in special cases. One appealing approach is the Diaconis and Gangolli Markov chain which updates the entries of a random 2×2 submatrix. This chain is known to be rapidly mixing for cell-bounded tables only when the cell bounds are all 1 and the row and column sums are regular. We demonstrate that the chain can require exponential time to mix in the cell-bounded case, even if we restrict to instances for which the state space is connected. Moreover, we show the chain can be slowly mixing even if we restrict to natural classes of problem instances, including regular instances with cell bounds of either 0 or 1 everywhere, and dense instances where at least a linear number of cells in each row or column have non-zero cell-bounds.     

An Application of Master Schedule Smoothing and Planned Lead Time Control

Make‐to‐order (MTO) manufacturers must ensure concurrent availability of all parts required for production, as any unavailability may cause a delay in completion time. A major challenge for MTO manufacturers operating under high demand variability is to produce customized parts in time to meet internal production schedules. We present a case study of a producer of MTO offshore oil rigs that highlights the key aspects of the problem. The producer was faced with an increase in both demand and demand variability. Consequently, it had to rely heavily on subcontracting to handle production requirements that were in excess of its capacity. We focused on the manufacture of customized steel panels, which represent the main sub‐assemblies for building an oil rig. We considered two key tactical parameters: the planning window of the master production schedule and the planned lead time of each workstation. Under the constraint of a fixed internal delivery lead time, we determined the optimal planning parameters. This improvement effort reduced the subcontracting cost by implementing several actions: the creation of a master schedule for each sub‐assembly family of the steel panels, the smoothing of the master schedule over its planning window, and the controlling of production at each workstation by its planned lead time. We report our experience in applying the analytical model, the managerial insights gained, and how the application benefits the oil‐rig producer.     

MULTIPLE RATERS IN SURVEY‐BASED OPERATIONS MANAGEMENT RESEARCH: A REVIEW AND TUTORIAL

Research in the area of operations strategy has made significant progress during the past decade in terms of quantity of articles published, as well as the quality of these articles. Recent studies have examined the published literature base and determined that, in general, the field has progressed beyond an exploratory stage to a point where there is a core set of basic terminology and models. Concurrent with the formation and solidification of a core terminology, there is an increasing emphasis on developing and employing a set of reliable, valid, and reproducible methods for conducting research on operations strategy. We provide a review of common methods for assessing the degree of reliability and agreement of the responses provided by multiple raters within a given organization to a set of qualitative questions. In particular, we examine four methods of determining whether there is evidence of disagreement or bias between multiple raters within a single organization in a mail survey.     

Effective Design of Products/Services: An Approach Based on Integration of Marketing and Operations Management Decisions*

This paper presents an integrated framework for designing profit‐maximizing products/ services, which can also be produced at reasonable operating difficulty levels. Operating difficulty is represented as a function of product and process attributes, and measures a firm's relative ease or difficulty in meeting customer demand patterns under specified operating conditions. Earlier optimum product design procedures have not considered. operational difficulty. We show that optimum profit, market share, cost, and product profiles are dependent on operating difficulty level. Empirical results from the pizza delivery industry demonstrate the value of the proposed Effective Product/Service Design approach.     

Supplier‐Switching Inertia and Competitive Asymmetry: A Demand‐Side Perspective*

Building on strategic management, operations strategy, and supplier management literatures, this article presents a framework for supplier selection from the demand‐side perspective. We highlight the role of a purchasing firm's switching inertia in the supplier‐selection process and demonstrate the usefulness of our framework for the industrial automation industry. Empirical data for this study was collected from 171 corporate and plant‐level executives in pharmaceutical, chemical, and paper‐and‐pulp manufacturing industries in the United States. A series of Web‐based individually customized discrete choice experiments asked the respondents to either switch to the new supplier or stay with the existing supplier. Based on the results of these experiments, we demonstrate the existence of switching inertia in the supplier‐selection process and discuss the managerial implications for incumbent and challenger supplier firms.     

Locating social service centres using interactive graphics

The paper explores the feasibility of using interactive graphic based solution procedures in location problems with discrete choices. It compares solutions generated through interactive graphics with those generated through optimization for a problem context where service centres had to be located in rural India. The comparison demonstrates the feasibility of generating near optimal solutions for problems with a certain dimensionality. Broad features of the graphic software are described. The paper also highlights other advantages and limitations of the interactive graphic procedure.     

Surprise,Anticipation, and Sequence Effects in the Design of Experiential Services

The most salient or peak aspect of a service experience often defines customer perceptions of the service. Across two studies, using the same novel form of a scenario‐based experiment, we investigate the design of peak events in a service sequence by testing how anticipated and surprised peaks influence customer perceptions. Study 1 captures the immediate reactions of participants and Study 2 surveys participants a week later. In both studies, we find a main effect for the temporal peak placement, confirming the positive influence of a strong peak ending. When assessing the peak design strategies of surprise and anticipation, we find in Study 1 that surprise and anticipation moderate the temporal peak placement (e.g., early peak vs. late peak) on overall customer perceptions, with the surprise peak at the end of an experience yielding the strongest effect. In Study 2 we see that the remembered experience of a surprise peak positively affects customer perceptions compared to an anticipated peak regardless of the temporal placement of the peak. We also find that the infusion of a surprise peak ending has a lasting effect that amplifies the peak‐end effect of remembered experiences. Drawing on these findings, we discuss the role of surprise, anticipation, and sequence effects in experience design strategy.