Bargaining power and supply base diversification

In this paper, the authors examine a supply base diversification problem faced by a buyer who periodically holds auctions to award short term supply contracts among a cohort of suppliers (i.e., the supply base). To mitigate significant cost shocks to procurement, the buyer can diversify her supply base by selecting suppliers from different regions. The authors find that the optimal degree of supply base diversification depends on the buyer’s bargaining power, i.e., the buyer’s ability to choose the auction mechanism. At one extreme, when the buyer has full bargaining power and thus can dictatorially implement the optimal mechanism, she prefers to fully diversify. At the other extreme, when the buyer uses a reverse English auction with no reserve price due to her lack of bargaining power, she may consider protecting herself against potential price escalation from cost-advantaged suppliers by using a less diversified supply base. The authors find that in general the more bargaining power the buyer has to control price escalation from cost-advantaged suppliers the more she prefers a diversified supply base. This insight is shown to be robust to correlation between regional costs, asymmetry across regions, and intermediate levels of bargaining power.supply base diversification; supplier; buyer; procurement; bargaining

Supply Disruptions, Asymmetric Information and a Backup Production Option

We study a manufacturer that faces a supplier privileged with private information about supply disruptions. We investigate how risk-management strategies of the manufacturer change, and examine whether risk-management tools are more, or less, valuable, in the presence of such asymmetric information. We model a supply chain with one manufacturer and one supplier, in which the supplier's reliability is either high or low and is the supplier's private information. Upon disruption the supplier chooses between paying a penalty to the manufacturer for the shortfall and using backup production to fill the manufacturer's order. Using mechanism design theory, we derive the optimal contract menu offered by the manufacturer. We find that information asymmetry may cause the less reliable supplier type to stop using backup production while the more reliable supplier type continues to use it. Additionally, the manufacturer may stop ordering from the less reliable supplier type altogether. The value of backup production for the manufacturer is not necessarily larger under symmetric information and, for the more reliable supplier type, it could be negative . The manufacturer is willing to pay the most for information when backup production is moderately expensive. The value of information may increase as supplier types become uniformly more reliable. Thus, higher reliability need not be a substitute for better information.http://deepblue.lib.umich.edu/bitstream/2027.42/58722/1/1110-Damian.pd

Bargaining Power and Supply Base Diversification

We examine a supply base diversification problem faced by a buyer who periodically holds auctions to award short term supply contracts among a cohort of suppliers (i.e., the supply base). To mitigate significant cost shocks to procurement, the buyer can diversify her supply base by selecting suppliers from different regions. We find that the optimal degree of supply base diversification depends on the buyer’s bargaining power, i.e., the buyer’s ability to choose the auction mechanism. At one extreme, when the buyer has full bargaining power and thus can dictatorially implement the optimal mechanism, she prefers to fully diversify. At the other extreme, when the buyer uses a reverse English auction with no reserve price due to her lack of bargaining power, she may consider protecting herself against potential price escalation from cost-advantaged suppliers by using a less diversified supply base. We find that in general the more bargaining power the buyer has to control price escalation from cost-advantaged suppliers the more she prefers a diversified supply base. This insight is shown to be robust to correlation between regional costs, asymmetry across regions, and intermediate levels of bargaining power.http://deepblue.lib.umich.edu/bitstream/2027.42/61192/1/1118_Beil.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/61192/4/1118r_Beil.pd

The Role of Problem Specification in Crowdsourcing Contests for Design Problems: A Theoretical and Empirical Analysis

This paper studies the role of seekers' problem specification in crowdsourcing contests for design problems. Platforms hosting design contests offer detailed guidance for seekers to specify their design problems when launching a contest. Yet, problem specification in such crowdsourcing contests is something the theoretical and empirical literature has largely overlooked. We aim to fill this gap by offering an empirically-validated model to generate insights for the provision of information at contest launch. We develop a game-theoretic model featuring different types of information (categorized as “conceptual objectives” or “execution guidelines”) conveyed in problem specifications, and assess their impact on design processes. Real-world data is used to empirically test hypotheses generated from the model, and a quasi-natural experiment provides further empirical evidence for our predictions and recommendations. We show theoretically and verify empirically that, with more conceptual objectives disclosed in the problem specification, the number of participants in a contest decreases, but the trial effort provision by each participant does not change; with more execution guidelines disclosed in the problem specification, the trial effort provision by each participant increases, but the number of participants in a contest does not change. With that knowledge, we are able to formulate seekers' optimal decisions on problem specifications, and find that, to maximize the expected quality of the best solution to crowdsourced design problems, seekers should always provide more execution guidelines, and only a moderate number of conceptual objectives.https://deepblue.lib.umich.edu/bitstream/2027.42/146143/1/1388_Jiang.pd

Simplified Bidding and Solution Mechanisms for VCG Combinatorial Auctions

Combinatorial auctions are very useful in theory, but their applicability in practice has been limited by the need for bidders to bid on an exponential number of bundles and for the auctioneer to solve an exponentially large winner-determination problem. We present a new auction mechanism to eliminate these challenges for a broad class of VCG combinatorial auctions. This mechanism, which yields equivalent results to a fully-enumerated combinatorial auction, eliminates the need for the bidder to explicitly compute and communicate bids on each bundle by exploiting the fact that true-cost bidding is a dominant strategy for these auctions. It also eliminates the need for the auctioneer to solve an exponentially large combinatorial optimization problem to select the optimal bids. Instead, the bidders' true-cost types are explicitly incorporated within a mathematical program that is used to solve the winner- and payment- determination problems. A detailed example based on truckload procurement auctions is provided and several other applicable classes of problems are discussed as well.http://deepblue.lib.umich.edu/bitstream/2027.42/41222/1/1034.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/41222/4/1034-Beil.pd

The Role of Feedback in Dynamic Crowdsourcing Contests: A Structural Empirical Analysis

In this paper, we empirically examine the impact of performance feedback on the outcome of crowdsourcing contests. We develop a dynamic structural model to capture the economic processes that drive contest participants' behavior, and estimate the model using a rich data set collected from a major online crowdsourcing design platform. The model captures key features of the crowdsourcing context, including a large participant pool, entries by new participants throughout the contest, exploitation (revision of previous submissions) and exploration (radically novel submissions) behaviors by contest incumbents, and the participants' strategic choice among these entry, exploration, and exploitation decisions in a dynamic game. We find that the cost associated with exploratory actions is higher than the cost associated with exploitative actions. High-performers prefer the exploitative strategy, while low-performers tend to make fewer follow-up submissions and prefer the exploratory strategy. Using counter-factual simulations, we compare the outcome of crowdsourcing contests under alternative feedback disclosure policies and award levels. Our simulation results suggest that the full feedback policy (providing feedback throughout the cohttp://deepblue.lib.umich.edu/bitstream/2027.42/134692/1/1334_YHuang.pd

RFQ Auctions with Supplier Qualification Screening

We consider a manufacturer using a Request For Quotes reverse auction in combination with supplier qualification screening to determine which qualified supplier will be awarded a contract. Supplier qualification screening is costly for the manufacturer, for example involving reference checks, financial audits, and on-site visits. The manufacturer seeks to minimize its total procurement costs, i.e. the contract payment plus qualification costs. While suppliers can be qualified prior to the auction (pre-qualification), we allow the manufacturer to delay all or part of the qualification until after the auction (post-qualification). Using an optimal mechanism analysis we analytically explore the tradeoffs between varying levels of pre- and post-qualification. While using post-qualification causes the expected contract payment to increase (bids from unqualified suppliers are discarded) we find that standard industrial practices of pre-qualification only can be improved upon by judicious use of post-qualification, particularly when supplier qualification screening is moderately expensive relative to the value of the contract to the buyer

An inverse-optimization-based auction mechanism to support a multiattribute RFQ process. Mgmt Sci

We consider a manufacturer who uses a reverse, or procurement, auction to determine which supplier will be awarded a contract. Each bid consists of a price and a set of non-price attributes (e.g., quality, lead time). The manufacturer is assumed to know the parametric form of the suppliers’cost functions (in terms of the non-price attributes), but has no prior information on the parameter values. We construct a multi-round open-ascending auction mechanism, where the manufacturer announces a slightly different scoring rule (i.e., a function that ranks the bids in terms of the price and non-price attributes) in each round. Via inverse optimization, the manufacturer uses the bids from the first several rounds to learn the suppliers’cost functions, and then in the final round chooses a scoring rule that attempts to maximize his own utility. Under the assumption that suppliers submit their myopic best-response bids in the last round, and do not distort their bids in the earlier rounds (i.e., they choose their minimum-cost bid to achieve any given score), our mechanism indeed maximizes the manufacturer’s utility within the open-ascending format. We also discuss several enhancements that improve the robustness of our mechanism with respect to the model’s informational and behavioral assumptions. Decembe