In this note, we identify two errors in Greenleaf, Rao, and Sinha's (1993) analysis of negotiation of guarantees in auctions. This note provides a high-level but self-contained summary of the revised results. We find that, in contrast with the earlier claim, guaranteed auctions lead to greater total expected revenue than conventional auctions. The ability to bargain over guarantee values and commissions certainly benefits sellers but may hurt the profits of auction houses. We relate these results to recent events in auction markets.
We analyze the problem faced by companies that rely on TL (Truckload) and LTL (Less than Truckload) carriers for the distribution of products across their supply chain. Our goal is to design simple inventory policies and transportation strategies to satisfy time varying demands over a finite horizon, while minimizing system wide cost by taking advantage of quantity discounts in the transportation cost structures. For this purpose, we study the cost effectiveness of restricting the inventory policies to the class of zero-inventory-ordering (ZIO) policies in a single-warehouse multiretailer scenario in which the warehouse serves as a cross-dock facility. In particular, we demonstrate that there exists a ZIO inventory policy whose total inventory and transportation cost is no more than 4/3 (5.6/4.6 if transportation costs are stationary) times the optimal cost. However, finding the best ZIO policy is an NP hard problem as well. Thus, we propose two algorithms to find an effective ZIO policy: An exact algorithm whose running time is polynomial for any fixed number of retailers, and a linear-programming-based heuristic whose effectiveness is demonstrated in a series of computational experiments. Finally, we extend the worst-case results developed in this paper to systems in which the warehouse does hold inventory.
We consider the optimality of the (s, S) policy for a periodic-review stochastic inventory problem with two types of shortage costs. The problem may arise in a rush-order application at a bank branch where the emergency provision costs during a foreign currency stockout are represented by proportional and lump-sum penalties. Aneja and Noori (1987) analyzed this problem and presented a set of conditions for the convexity of a particular function and made a claim about the K-convexity of another function to prove the optimality of the (s, S) policy. We show that because the function that is claimed to be K-convex is actually concave over a subset of its domain, Aneja and Noori's arguments cannot be used to prove the optimality of the (s, S) policy. However, we argue that Aneja and Noori's problem is equivalent to the typical lost-sales problem, and using this equivalence, we .nd a simple convexity condition that assures the optimality of the (s, S) policy.
It has been suggested in the data envelopment analysis (DEA) literature that it is impossible to obtain a full ranking of decision-making units (DMUs) when infeasible subproblems arise in the so-called super-efficiency DEA models under different returns to scale (RTS) assumptions other than constant returns to scale (CRS) andconsequently the application of the super-efficiency DEA models under different RTS conditions other than CRS should be restricted. The implications of the infeasibility in super-efficiency DEA models with respect to the efficiency ranking of the DMUs is explored. Based on the analysis, we show that it is still possible to obtain the full ranking of the entire observation set when infeasibilities arise in super-efficiency DEA models.
Over the past fifteen years, a number of studies have examined the determinants of firm R&D spending. These studies, however, almost invariably focus on the role of firm or external ownership characteristics in predicting R&D spending while overlooking the attributes of the top managers involved in allocating corporate resources. In this study, we change that focus by empirically examining how R&D spending as compared to industry competitors varies at firms based on the characteristics of their CEOs. Using a sample of publicly traded firms, we find that CEO characteristics explain a significant proportion of the sample variance in firm R&D spending even when corporate strategy, ownership structure, and other firm-level attributes are controlled. In terms of individual CEO characteristics, we find that R&D spending is greater at firms where CEOs are younger, have greater wealth invested in firm stock and signifacant career experience in marketing and/or engineering/R&D. In contrast to existing theory, we find that the amount of a CEO's formal education had no significant association with R&D spending once a CEO has attained a college degree. However, significant R&D spending increases are found at firms where CEOs have advanced science-related degrees. From subgroup analyses, we further find that CEO effects on relative R&D spending increase with longer CEO tenure implying that CEOs, over time, may mold R&D spending to suit their own preferences. From these results, we make implications for both research on determinants of R&D spending and managerial practice.
We address the modeling and analysis of abandonments from a queue that is invisible to its occupants. Such queues arise in remote service systems, notably the Internet and telephone call centers; hence, we refer to them as tele-queues. A basic premise of this paper is that customers adapt their patience (modeled by an abandonment-time distribution) to their service expectations, in particular to their anticipated waiting time. We present empirical support for that hypothesis, and propose an M/M/m-based model that incorporates adaptive customer behavior. In our model, customer patience depends on the mean waiting time in the queue. We characterize the resulting system equilibrium (namely, the operating point in steady state), and establish its existence and uniqueness when changes in customer patience are bounded by the corresponding changes in their anticipated waiting time. The feasibility of multiple system equilibria is illustrated when this condition is violated. Finally, a dynamic learning model is proposed where customer expectations regarding their waiting time are formed through accumulated experience. We demonstrate, via simulation, convergence to the theoretically anticipated equilibrium, while addressing certain issues related to censored-sampling that arise because of abandonments.
This paper proposes a model of how coordinating mechanisms work, and tests it in the context of patient care. Consistent with organization design theory, the performance effects of boundary spanners and team meetings were mediated by relational coordination, a communication- and relationship-intensive form of coordination. Contrary to organization design theory, however, the performance effects of routines were also mediated by relational coordination. Rather than serving as a replacement for interactions, as anticipated by organization design theory, routines work by enhancing interactions among participants. Likewise, all three coordinating mechanisms, including routines, were found to be increasingly effective under conditions of uncertainty.
The Bass diffusion model is a well-known parametric approach to estimating new product demand trajectory over time. This paper generalizes the Bass model by allowing for a supply constraint. In the presence of a supply constraint, potential customers who are not able to obtain the new product join the waiting queue, generating backorders and potentially reversing their adoption decision, resulting in lost sales. Consequently, they do not generate the positive “word-of-mouth” that is typically assumed in the Bass model, leading to significant changes in the new product diffusion dynamics. We study how a firm should manage its supply processes in a new product diffusion environment with backorders and lost sales. We consider a make-to-stock production environment and use optimal control theory to establish that it is never optimal to delay demand fulfillment. This result is interesting because immediate fulfillment may accelerate the diffusion process and thereby result in a greater loss of customers in the future. Using this result, we derive closed-form expressions for the resulting demand and sales dynamics over the product life cycle. We then use these expressions to investigate how the firm should determine the size of its capacity and the time to market its new product. We show that delaying a product launch to build up an initial inventory may be optimal and can be used as a substitute for capacity. Also, the optimal time to market and capacity increase with the coefficients of innovation and imitation in the adoption population. We compare our optimal capacity and time to market policies with those resulting from exogeneous demand forecasts in order to quantify the value of endogenizing demand.
Merger and acquisition activity has increased sharply in the last decade. It seems useful to have models that can help senior managers of bidder firms make informed decisions about the amount of premium, over the target's share prices prevailing prior to merger announcement, that can be justified on the basis of operational synergies. The goal of this article is to capture important parameters from the production side that have a bearing on the valuation of the target's shares. We show that the production characteristics of both the bidder and the target matter in a significant way. For example, if the bidder and target operate in independent markets, the bidder has flexible production facilities but the target's production facilities are inflexible, then an increase in the bidder's demand can make the target less attractive and lower the value of operational synergy.
A two-person game is formulated for a queuing situation involving a pair of exponential servers competing for arriving customers. The servers have identical characteristics except for their service rates. Each server is free to select its own service rate. The objective of each server is to select a service rate that will maximize its own profit. Arrivals are Poisson. The probability that an arriving customer enters the queue is allowed to depend on the queue length at the time of arrival. The proportion of arrivals to a given server is shown to be strictly concave in the server's own service rate and decreasing in the other service rate. Furthermore, we show that when the cost function is convex and increasing, there exists a unique pure strategy Nash equilibrium point for the resulting game.