Knowledge that Transforms

We focus on the principal-agent relationship in a distribution channel. In a services context (insurance), we examine how two facets of performance, from the point of view of both the principal and the agent, are influenced by the perceiver's belief that it is more committed to the relationship than is the other party. Using primary data from 255 insurance agent-insurance provider dyads, we show that each side's assessment of how much it benefits from the dyad is related in a potentially dysfunctional manner to its perception of asymmetric commitment. Perceivers rate their performance outcomes from the dyad (i.e., harmony and profit) highest when they believe they are less committed than their counterpart. Conversely, they rate their own performance outcomes lowest when they believe they are more committed than the other party. We explain this finding in terms of suspected opportunism and offer a partial test of this explanation compared with explanations from theories of equity and power/dependence. Further, we demonstrate that each party's perception of asymmetric commitment partially reflects actual asymmetry, as measured by confidential data collected from both sides. Perceived asymmetric commitment is also shown to be related to levels of communication and dependence in the dyad. Managerial implications for reducing perceived asymmetric commitment and improving the performance outcomes of each dyad member are discussed.

This paper empirically estimates the impact of not meeting promised new product introduction dates on the market value of the firm. We estimate the average “abnormal” change in the market value for a sample of 101 firms around the date when information about delaying the introduction of new products is publicly announced. On average, delay announcements decrease the market value of the firm by 5.25%. The average dollar change in the market value in 1991 dollars is $−119.3 million. The evidence suggests that there are significant penalties for not introducing new products on time. To provide further insight, regression analyses are used to identify factors that influence the direction and magnitude of the change in market value. We find that the competitiveness of the industry in which the firm operates, the size of the firm, and the firm's degree of diversification are statistically significant predictors for the change in the market value of firms that announce delays in the introduction of new products.

We define a high volume factory to be a connected network of workstations, at which assigned workers process work-in-progress that flows at high rates through the workstations. A high rate usually implies that each worker processes many pieces per hour, enough so that work can be described as a deterministic hourly flow rate rather than, say, a stochastic number of discrete entities. Examples include mail processing and sorting, check processing, telephoned order processing, and inspecting and packaging of certain foods. Exogenous work may enter the factory at any workstation according to any time-of-day profile. Work-in-progress flows through the factory in discrete time according to Markovian routings. Workers, who in general are cross-trained, may work part time or full time shifts, may start work only at designated shift starting times, and may change job assignments at mid shift. In order to smooth the flow of work-in-progress through the service factory, work-in-progress may be temporarily inventoried (in buffers) at work stations. The objective is to schedule the workers (and correspondingly, the workflow) in a manner that minimizes labor costs subject to a variety of service-level, contractual and physical constraints. Motivated in part by analysis techniques of discrete time linear time-invariant (LTI) systems, an object-oriented linear programming (OOLP) model is developed. Using exogenous input work profiles typical of large U.S. mail processing facilities, illustrative computational results are included.

Using the Lanchester model to describe the dynamics of the market where two firms compete for customers by advertising, we solve the problem of determining an optimal advertising strategy for maximum discounted profits. We develop both open- and closed-loop strategies and explain the relationship between them. Using a new mathematical approach, we prove that our closed-loop solution is a global Nash equilibrium. The closed-loop strategy is time-variant and depends linearly on the actual market share. The time-variant coefficient incorporates the discount factor, its computation requires the solution of a backward differential equation and a set of two nonlinear differential equations for an initial value problem. The closed-loop advertising expenditures are proportional to the open-loop advertising expenditures and to the square of the competitor's actual market share. This provides a very practical adaptive control rule that allows the manager to adjust the actual advertising expenditure and to deviate from budget. We illustrate the use of our control rule, using data for the period 1968–1984 of the Cola War Marketing implications of the results are provided.

In this paper we study how performance requirements may improve the working of a distribution channel when the retailer is better informed about demand conditions than the manufacturer. Performance requirements means that the manufacturer and retailer agree to (1) have the manufacturer set requirements on retail price or service or both, and (2) jointly invest in the information systems required to monitor the retailer’s compliance with the requirements. We show that performance requirements on price and service will improve channel performance. But if requirements cannot be set on both performance dimensions, the choice among the remaining options is not straightforward. Price requirements may be worse than no requirements, and service requirements no better. The central problem with setting requirements on only one dimension is that the retailer then behaves suboptimally on the other. Between the two partial options, service requirements are better than price requirements in aligning the interests of the manufacturer and the retailer, whereas price requirements are better at inducing the retailer to reveal his demand.

This paper analyzes Japanese manufacturing firms' export behavior and their performance. In a slow growth era, leading firms' and minor firms' export ratio tended to be less than that of follower (medium market share) firms in the same industry; there appears to be an inverted-U shape between export ratio and relative size of firms. An affiliation with a large industrial group has no positive relationship with export ratio, while other firm-specific factors do not show consistent relationships with it in the years 1971 to 1985. Exports and firm performance do not have a positive relationship. Competitive environment in the domestic market is related to the export strategy of Japanese firms.

Several branch-and-bound algorithms for the exact solution of the asymmetric traveling salesman problem (ATSP), based on the assignment problem (AP) relaxation, have been proposed in the literature. These algorithms perform very well for some instances (e.g., those with uniformly random integer costs), but very poorly for others. The aim of this paper is to evaluate the effectiveness of a branch-and-cut algorithm exploiting ATSP-specific facet-defining cuts, to be used to attack hard instances that cannot be solved by the AP-based procedures from the literature. We present new separation algorithms for some classes of facet-defining cuts, and a new variable-pricing technique for dealing with highly degenerate primal LP problems. A branch-and-cut algorithm based on these new results is designed and evaluated through computational analysis on several classes of both random and real-world instances. The outcome of the research is that, on hard instances, the branch-and-cut algorithm clearly outperforms the best AP-based algorithms from the literature.

The global markets of today offer to the “style goods” producer more selling opportunities and pose new challenges in production planning and coordination. From a production management standpoint the opportunity to exploit the difference in timing of the selling season of geographically dispersed markets for “style goods” is important for improving the firm’s profitability. In this paper we examine the above issue with an insightful model of a producer of “style goods” selling the goods to two markets (a primary and a secondary market) with nonoverlapping selling seasons. We refer to this problem as the “global newsvendor” problem. For the above two market stochastic inventory systems we first develop optimal centralized control policies. Then we demonstrate the suboptimality of decentralized production control policies, with the production centers at each market treated as independent profit centers and a constant transfer price being used to coordinate their production. We propose as an effective alternative a decentralized production control structure with a nonlinear pricing scheme for production coordination among centers administered through an intermediate organizational unit. In our modeling, we explicitly consider the effects of exchange rate uncertainty on the production planning decisions.

As manufacturing technology moves toward more computerized automation, statistical process control (SPC) techniques must adapt to keep pace with the new environment and take advantage of the development in automated on-line sensors. In this paper, a two-phase procedure is proposed for combining an on-line sensor and a control chart to improve statistical process control decisions. In phase 1 of this procedure, a production process is monitored continually by a sensor. When a sensor warning signal is observed, phase 2 takes place: A sample of items is drawn from the process and inspected. If the sample mean is outside the predetermined control limits, the process is stopped, and a search is initiated to determine the actual process status for possible necessary adjustment. If the sample mean is within the control limits, the process continues. A mathematical model is formulated for jointly determining the sample size and the control limit of the control chart and a decision rule for sending out sensor warning signals. The model is based on the assumption that there is only a weak relationship between the sensor measurement and the process condition. A solution algorithm based on a numerical search is developed. A numerical example is used to show the advantage of the proposed model over the models based separately on the sensor and the control chart, and a sensitivity analysis is used to show the effects of several important model parameters on the optimal solution.

We address an assembly problem, motivated by flat panel display manufacturing, where the quality (or performance) of the final product depends upon characteristics of the components to be assembled, which are not constant from component to component. We analyze the tradeoff between the increase in the potential value of products gained by putting off the “mating” of components exhibiting various characteristic “types,” and the inventory costs caused by this delay in mating. We formulate this dynamic type mating problem as a Markov Decision Process and characterize the structure of the optimal policy for special cases. We then present a heuristic policy for a more general case and compare its performance against the optimal policy. Computational results indicate that the heuristic is effective for a wide variety of cases.