This paper investigates the capacity investment decision of a supplier who solicits private forecast information from a manufacturer. To ensure abundant supply, the manufacturer has an incentive to inflate her forecast in a costless, nonbinding, and nonverifiable type of communication known as "cheap talk." According to standard game theory, parties do not cooperate and the only equilibrium is uninformative--the manufacturer's report is independent of her forecast and the supplier does not use the report to determine capacity. However, we observe in controlled laboratory experiments that parties cooperate even in the absence of reputation-building mechanisms and complex contracts. We argue that the underlying reason for cooperation is trust and trustworthiness. The extant literature on forecast sharing and supply chain coordination implicitly assumes that supply chain members either absolutely trust each other and cooperate when sharing forecast information, or do not trust each other at all. Contrary to this all-or-nothing view, we determine that a continuum exists between these two extremes. In addition, we determine (i) when trust is important in forecast information sharing, (ii) how trust is affected by changes in the supply chain environment, and (iii) how trust affects related operational decisions. To explain and better understand the observed behavioral regularities, we also develop an analytical model of trust to incorporate both pecuniary and nonpecuniary incentives in the game-theoretic analysis of cheap-talk forecast communication. The model identifies and quantifies how trust and trustworthiness induce effective cheap-talk forecast sharing under the wholesale price contract. We also determine the impact of repeated interactions and information feedback on trust and cooperation in forecast sharing. We conclude with a discussion on the implications of our results for developing effective forecast management policies. This paper was accepted by Ananth Iyer, operations and supply chain management.trust, trustworthiness, cheap talk, asymmetric forecast information, wholesale price contract, behavioral economics, experimental economics
We study a manufacturer's problem of managing his direct online sales channel together with an independently owned bricks-and-mortar retail channel, when the channels compete in service. We incorporate a detailed consumer channel choice model in which the demand faced in each channel depends on the service levels of both channels as well as the consumers' valuation of the product and shopping experience. The direct channel's service is measured by the delivery lead time for the product; the retail channel's service is measured by product availability. We identify optimal dual channel strategies that depend on the channel environment described by factors such as the cost of managing a direct channel, retailer inconvenience, and some product characteristics. We also determine when the manufacturer should establish a direct channel or a retail channel if he is already selling through one of these channels. Finally, we conduct a sequence of controlled experiments with human subjects to investigate whether our model makes reasonable predictions of human behavior. We determine that the model accurately predicts the direction of changes in the subjects' decisions, as well as their channel strategies in response to the changes in the channel environment. These observations suggest that the model can be used in designing channel strategies for an actual dual channel environment. 1dual channels, direct channel, service competition, product availability, supply chain contracting, experimental economics
Exploring the tension between theory and practice regarding complexity and performance in contract design is especially relevant. The goal of this paper is to understand why simpler contracts may commonly be preferred in practice despite being theoretically suboptimal. We study a two-tier supply chain with a single supplier and a single buyer to characterize the impact of contract complexity and asymmetric information on performance and to compare theoretical predictions to actual behavior in human subject experiments. In the experiments, the computerized buyer faces a newsvendor setting and has better information on end-consumer demand than the human supplier. The supplier offers either a quantity discount contract (with two or three price blocks) or a price-only contract, contracts that are commonplace in practice, yet different in complexity. Results show that, contrary to theoretical predictions, quantity discounts do not necessarily increase the supplier's profits. We also observe a more equitable distribution of profits between the supplier and the buyer than what theory predicts. These observations can be described with three decision biases (the probabilistic choice bias, the reinforcement bias, and the memory bias) and can be modeled using the experience-weighted attraction learning model. Our results demonstrate that simpler contracts, such as a price-only contract or a quantity discount contract with a low number of price blocks, are sufficient for a supplier designing contracts under asymmetric demand information. This paper was accepted by Christian Terwiesch, operations and supply chain management.behavioral operations management, all-unit quantity discount contracts, price-only contracts, complex contracts, contract performance, supply chain efficiency, asymmetric demand information, experience-weighted attraction learning model
Despite being theoretically suboptimal, simpler contracts (such as price‐only contracts and quantity discount contracts with limited number of price blocks) are commonly preferred in practice. Thus, exploring the tension between theory and practice regarding complexity and performance in contract design is especially relevant. Using human subject experiments, Kalkancı et al. (2011) showed that such simpler contracts perform effectively for a supplier interacting with a computerized buyer under asymmetric demand information. We use a similar set of experiments with the modification that a human supplier interacts with a human buyer. We show that human interactions strengthen the supplier's preference for simpler contracts. We find that suppliers have fairness concerns even when they interact with computerized buyers. These fairness concerns tend to be even stronger when suppliers interact with human buyers, particularly when the complexity of the contract is low. We also find that suppliers are more prone to random decision errors (i.e., bounded rationality) when interacting with human buyers. In the absence of social preferences, Kalkancı et al. identified reinforcement and bounded rationality as key biases that impact suppliers' decisions. In human‐to‐human experiments, we find evidence for social preference effects. However, these effects may be secondary to bounded rationality.
The extent to which the behavior of people is consistent with game theoretic principles is investigated in a first price sealed bid auction environment Three linear rules of thwnb with increasing complexity are used as benchmarks to gauge the accuracy of the Constant Relative Risk Aversion Model (CRRAM). In addition, the CRRAM is tested against the relaxation of the rational expectation hypothesis.Existing competitive bidding experiments cannot clearly distinguish between game theoretic models and linear markdown rules on an individual level. Within the parametric environments studied and reported in the experimental literature, game theoretic solutions are linear over the range of private values in which bid functions are estimated. In this study, agents drew values from nonuniform distributions. As a result, the game theoretic bidding behavior is nonlinear.Due to the nonlinearity, special econometric and nwnerical techniques are applied to solve the model and obtain the estimates. The CRRAM exhibits good fit of the data. The pseudo R2 is greater than 0.8 in 90 percent of the subjects. The CRRAM is more accurate than the Markdown Model (MM) and the Simple Ad hoc Model (SIMAM) but not as accurate as the Sophisticated Ad hoc Model (SOP AM). The data also suppons the relaxation of the rational expectation hypothesis and suggests that substantial increases in the predictive power of game theoretic models can be gained from improvements in the theory of belief formation.
We present a quantum auction protocol using superpositions to represent bids and distributed search to identify the winner(s). Measuring the final quantum state gives the auction outcome while simultaneously destroying the superposition. Thus, non-winning bids are never revealed. Participants can use entanglement to arrange for correlations among their bids, with the assurance that this entanglement is not observable by others. This protocol is useful for information hiding applications, such as partnership bidding with allocative externality or concerns about revealing bidding preferences. The protocol applies to a variety of auction types, e.g. first or second price, and to auctions involving either a single item or arbitrary bundles of items (i.e. combinatorial auctions). We analyze the game-theoretical behavior of the quantum protocol for the simple case of a sealed-bid quantum, and show how a suitably designed adiabatic search reduces the possibilities for bidders to game the auction. This design illustrates how incentive rather that computational constraints affect quantum algorithm choices.
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