Optimal transfer pricing schemes for work averse division managers with private information

This paper models a decentralized firm under information asymmetry and effort disutility on the part of managers. We assume that managers choose efforts before observing some private information. However, after the effort choice managers receive private information on their cost parameters which they report to the headquarters. There exist many situations in which managers need to take efforts before obtaining private information; for example, the regular maintenance effort on the machine, the effort on R&D for reducing costs and the effort taken to build relationships with the supplier. Two models are considered in this paper based on the timing of acquisition of private information by the managers. We derive optimal coordination mechanisms to facilitate internal transactions for the models. The equilibrium outcome of this paper suggests that: 1) regardless of the timing of managers' information acquisition, the optimal output level under asymmetric information can have overproduction or underproduction when compared with the full information optimal output; 2) under certain demand conditions managers cannot receive any information rent benefit for their private information even if they have the option to renege on the contract after obtaining their private information.     

Optimal spot market inventory strategies in the presence of cost and price risk

We consider a firm facing random demand at the end of a single period of random length. At any time during the period, the firm can either increase or decrease inventory by buying or selling on a spot market where price fluctuates randomly over time. The firm’s goal is to maximize expected discounted profit over the period, where profit consists of the revenue from selling goods to meet demand, on the spot market, or in salvage, minus the cost of buying goods, and transaction, penalty, and holding costs. We first show that this optimization problem is equivalent to a two-dimensional singular control problem. We then use a recently developed control-theoretic approach to show that the optimal policy is completely characterized by a simple price-dependent two-threshold policy. In a series of computational experiments, we explore the value of actively managing inventory during the period rather than making a purchase decision at the start of the period, and then passively waiting for demand. In these experiments, we observe that as price volatility increases, the value of actively managing inventory increases until some limit is reached.     

On sequential and simultaneous contributions under incomplete information

When contributors to a common cause (or public good) are uncertain about each others’ valuations, early contributors are likely to be cautious in free-riding on future contributors. Contrary to the case of complete information, when contributors have independent private valuations for the public good, the expected total contribution generated in a sequential move game may be higher than in a simultaneous move game. This is established in a conventional framework with quasi-linear utility where agents care only about the total provision of the public good (rather than individual contribution levels) and there is no non-convexity in the provision of the public good. We allow for arbitrary number of agents and fairly general distribution of types.     

Optimizing product service system by franchise fee contracts under information asymmetry

This paper studies the problem of how to effectively provide product service system (PSS) in a service-oriented manufacturing supply chain under asymmetric private demand information. The PSS in the supply chain is operated heterogeneously and complementarily, in which the manufacturer provides the product while the retailer who possesses private demand information is responsible for adding the necessary value-added service on the basic product. We address the issue of how different contracts affect the decisions and profitability of the supply chain members. Three types of contracts are developed to help supply chain partners to make decisions and enhance the supply chain’s efficiency. The first is the franchise fee (FF) contract, under which the manufacturer provides a two-part tariff contract (wholesale price and franchise fee) to influence the retailer’s decision and to detect her private demand information. The second is the franchise fee with service requirement (FFS) contract, under which the manufacturer specifies the service level required in addition to the two-part tariff contract terms. The third is the franchise fee with centralized service requirement (FFCS) contract, which is similar to the FFS contract but that the service level specified by the manufacturer is the system optimal solution. Our analytical results show that all three contracts enable the manufacturer to detect the retailer’s private demand information, with the FFCS contract achieving the greatest channel profit. Finally, numerical examples are presented, and sensitivity analysis of service level and profit are conducted to compare the performance of the three contracts under different settings. The paper provides managerial guidelines for the manufacturer in contract offering under different conditions.     

Endogenous effort in communication networks under strategic complementarity

This article examines individual incentives to produce information on communication networks. In our setting, efforts are strategic complements along communication paths with convex decay. We analyze the relationship between efforts and centrality on a set of networks which are unambiguous in terms of ordinal centrality. We first show that in both dominant and dominated equilibria central agents exert more effort. Second, we explore the issue of social coordination induced by our game.     

Single-vendor multi-buyer inventory coordination under private information

This paper considers the problem of coordinating a single-vendor multi-buyer inventory system when there are privacy restrictions in the information required to solve the problem. The objective function and cost parameters of each facility are regarded as private information that no other facilities in the system have access to. Moreover, each facility is responsible to specify its own replenishment policy. The objective is to minimize the total average setup/ordering and inventory-related cost. Solution methodologies under private and global information are developed to find two types of nested power-of-two stationary policies. The first policy assumes all the buyers must replenish simultaneously. The second policy is a more general case where the common replenishment assumption is relaxed. A simple form of information exchange is uncovered that allows the solution methodologies for private and global information yield the same results. The experimental results suggest that the performance of the proposed heuristics is comparable or better than an existing method.     

Micro-level reserving for general insurance claims using a long short-term memory network

Detailed information about individual claims are completely ignored when insurance claims data are aggregated and structured in development triangles for loss reserving. In the hope of extracting predictive power from the individual claims characteristics, researchers have recently proposed to use micro-level loss reserving approaches. We introduce a discrete-time individual reserving framework incorporating granular information in a deep learning approach named Long Short-Term Memory (LSTM) neural network. At each time period, the network has two tasks: first, classifying whether there is a payment or a recovery, and second, predicting the corresponding non-zero amount, if any. Based on a generalized Pareto model for excess payments over a threshold, we adjust the LSTM reserve prediction to account for extreme payments. We illustrate the estimation procedure on a simulated and a real general insurance dataset. We compare our approach with the chain-ladder aggregate method using the predictive outstanding loss estimates and their actual values.     

A principal–agent problem with heterogeneous demand distributions for a carbon capture and storage system

Mechanism design problems optimize contract offerings from a principal to different types of agents who have private information about their demands for a product or a service. We study the implications of uncertainty in agents’ demands on the principal’s contracts. Specifically, we consider the setting where agents’ demands follow heterogeneous distributions and the principal offers a menu of contracts stipulating quantities and transfer payments for each demand distribution. We present analytical solutions for the special case when there are two distributions each taking two discrete values, as well as a method for deriving analytical solutions from numerical solutions. We describe one application of the model in carbon capture and storage systems to demonstrate various types of optimal solutions and to obtain managerial insights.     

Protests and reputation

Protests take place for a variety of reasons. In this paper we focus on protests that have a well defined objective that is in conflict with the objectives of the government. Hence the success or failure of a protest movement depends crucially on how the government responds. We assume that government types are private information so that governments have an interest in building a reputation to deter protestors. We extend the standard reputation framework to one where potential protesters in the domestic jurisdiction are competing in a common market with protestors of a foreign jurisdiction, resulting in a situation where domestic governments care about the decisions of foreign governments. We derive conditions under which an equilibrium with “contagion” in protests might exist: protests that start in one jurisdiction spread to others. Finally we use our results to interpret the Fuel tax protests in France and England that took place in 2000 as well as the three successive pro-democracy revolutions in Georgia, Ukraine and Kyrgyzstan.     

Dominant strategy mechanisms for contract auctions with risk aversion and moral hazard

Within the class dominant strategy incentive compatible mechanisms, we show that there exists an optimal contracting mechanism for the principal for a version of the incomplete information principal-agent problem in which several agents compete for a contract and the principal selects an agent via a contract auction. In our auction model, we assume that the principal and the agents are risk averse, and we allow for uncountably many agent types. We also assume that the principal's probability measure over type profiles in such that correlation between agent's types is possible. Thus, we do not require that agents' types be independently distributed. Finally, we impose limited liability constraints upon the set of contracts. Due to the nature of the individual rationality and incentive compatibility constraints, the existence problem is nonstandard and novel existence arguments are required. We prove existence using a measurable selection result and a new notion of compactness called K-compactness.     

Committees,sequential voting and transparency

We propose a model of sequential voting in committees, where members use their individual votes to signal high efficiency in their bid to become re-appointed. Transparency precludes efficient information aggregation, and thus decreases the utility of the principal in the first period; it may be beneficial to her in the second period. Under transparency, equilibria under sequential voting always differ from those under simultaneous voting and may lead to more or less efficient information aggregation.     

Modeling secrecy and deception in a multiple-period attacker–defender signaling game

In this paper, we apply game theory to model strategies of secrecy and deception in a multiple-period attacker–defender resource-allocation and signaling game with incomplete information. At each period, we allow one of the three possible types of defender signals—truthful disclosure, secrecy, and deception. We also allow two types of information updating—the attacker updates his knowledge about the defender type after observing the defender’s signals, and also after observing the result of a contest (if one occurs in any given time period). Our multiple-period model provides insights into the balance between capital and expense for defensive investments (and the effects of defender private information, such as defense effectiveness, target valuations, and costs), and also shows that defenders can achieve more cost-effective security through secrecy and deception (possibly lasting more than one period), in a multiple-period game.     

Distributed multi-agent optimization with state-dependent communication

We study distributed algorithms for solving global optimization problems in which the objective function is the sum of local objective functions of agents and the constraint set is given by the intersection of local constraint sets of agents. We assume that each agent knows only his own local objective function and constraint set, and exchanges information with the other agents over a randomly varying network topology to update his information state. We assume a state-dependent communication model over this topology: communication is Markovian with respect to the states of the agents and the probability with which the links are available depends on the states of the agents. We study a projected multi-agent subgradient algorithm under state-dependent communication. The state-dependence of the communication introduces significant challenges and couples the study of information exchange with the analysis of subgradient steps and projection errors. We first show that the multi-agent subgradient algorithm when used with a constant stepsize may result in the agent estimates to diverge with probability one. Under some assumptions on the stepsize sequence, we provide convergence rate bounds on a “disagreement metric” between the agent estimates. Our bounds are time-nonhomogeneous in the sense that they depend on the initial starting time. Despite this, we show that agent estimates reach an almost sure consensus and converge to the same optimal solution of the global optimization problem with probability one under different assumptions on the local constraint sets and the stepsize sequence.     

Response time and vendor–assembler relationship in a supply chain

Relationships between an assembler and a vendor in a supply chain are investigated in two-period models when the assembler wants to reduce response time by incentive systems. The assembler may offer myopic or farsighted incentive contracts to the vendor, under short-term or long-term relationships. Incentive schemes, effort levels, and expected payoffs under different perspectives and relationships are examined. We find that a farsighted assembler provides the vendor with a higher incentive than a myopic assembler in the first period. A long (short)-term relationship is preferred if the value of farsightedness under a long-term relationship is greater (less) than the switching option value under a short-term relationship. We propose several sufficient conditions regarding which perspectives and relationships are preferred.     

Supplier switching decisions

In order to maximize profit, a buying firm should continuously search for and access sources which offer more favorable prices. While the literature is replete with works on the formation and development of buyer–supplier relationships, there is surprisingly only scarce research on the termination of such relationships and supplier switching. Using the concept of switching costs in a principal-agent framework, we at first analyze whether a firm switches the entire or a partial quantity to an alternative supplier when there is either symmetric or asymmetric information about the alternative supplier’s cost structure. Information asymmetry results in inert supplier switching decisions. Subsequently, we extend our model and take competitive reactions of the incumbent supplier and economies of scale effects into consideration. We find conditions under which ‘no’, ‘partial’ and ‘complete’ switching occurs, which depend on the buying firm’s beliefs about the alternative supplier’s unit costs, switching costs, the price offered by the incumbent supplier, and refinements of the price offered by the incumbent supplier due to competitive reactions and economies of scale. Broader implications for supplier relationship management and sourcing strategy decisions are also provided.     

Staffing decisions for heterogeneous workers with turnover

In this paper we consider a firm that employs heterogeneous workers to meet demand for its product or service. Workers differ in their skills, speed, and/or quality, and they randomly leave, or turn over. Each period the firm must decide how many workers of each type to hire or fire in order to meet randomly changing demand forecasts at minimal expense. When the number of workers of each type can by continuously varied, the operational cost is jointly convex in the number of workers of each type, hiring and firing costs are linear, and a random fraction of workers of each type leave in each period, the optimal policy has a simple hire- up-to/fire-down-to structure. However, under the more realistic assumption that the number of workers of each type is discrete, the optimal policy is much more difficult to characterize, and depends on the particular notion of discrete convexity used for the cost function. We explore several different notions of discrete convexity and their impact on structural results for the optimal policy.     

Groupstrategyproofness of the egalitarian mechanism for constrained rationing problems

Motivated by applications in many economic environments, Bochet et al. (2010) generalize the classic rationing model (Sprumont 1991) as follows: there is a moneyless market, in which a non-storable, homogeneous commodity is reallocated between agents with single-peaked preferences. Agents are either suppliers or demanders. Transfers between a supplier and a demander are feasible only if they are linked, and the links form an arbitrary bipartite graph. Information about individual preferences is private, and so is information about feasible links: an agent may unilaterally close one of her links if it is in her interest to do so. For this problem they propose the egalitarian transfer solution, which equalizes the net transfers of rationed agents as much as permitted by the bilateral constraints. Furthermore, they show that the egalitarian mechanism elicits a truthful report of both preferences and links. In the variant where demanders are not strategic but demands need to be exactly met Bochet et al. (2013), they propose a similar mechanism for which truthfully reporting the peaks is a dominant strategy, but truthful reporting of links is not.The key contribution of the paper is a comprehensive study of the egalitarian mechanism with respect to manipulation by a coalition of agents. Our main result is that the egalitarian mechanism is group strategyproof : no coalition of agents can (weakly) benefit from jointly misreporting their peaks. Furthermore, we show that the egalitarian mechanism cannot be manipulated – by misreporting links or by misreporting peaks – by any coalition of suppliers (or any coalition of demanders) in the model where both the suppliers and demanders are agents. Our proofs shed light on the structure of the two models and simplify some of the earlier proofs of strategyproofness. An implication of our results is that the well known algorithm of Megiddo (1977) to compute a lexicographically optimal flow in a network is group strategyproof with respect to the source capacities and sink capacities.     

How behaviors spread in dynamic social networks

In this paper, we explore how decentralized local interactions of autonomous agents in a network relate to collective behaviors. Earlier work in this area has modeled social networks with fixed agent relations. We instead focus on dynamic social networks in which agents can rationally adjust their neighborhoods based on their individual interests. We propose a new connection evaluation theory, the Highest Weighted Reward (HWR) rule: agents dynamically choose their neighbors in order to maximize their own utilities based on rewards from previous interactions. We prove that, in the two-action pure coordination game, our system would stabilize to a clustering state in which all relationships in the network are rewarded with an optimal payoff. Our experiments verify this theory and also reveal additional interesting patterns in the network.     

Optimal consumption and investment strategies with partial and private information in a multi-asset setting

Information is crucial for decision makers. The more and the better information one possesses, the more qualified a decision one is able to make. In a framework with partial information about the expected returns of n stocks, the effect of having either non-anticipative or anticipative private information is studied. Optimal consumption and investment strategies for investors exhibiting constant relative risk aversion are derived analytically and an economically intuitive condition for an investor to be indifferent between the two types of private information is given. Moreover, a detailed numerical study including the value of private information is carried out to obtain a better economic understanding of the interplay between partial and private information. One novel result is that intertemporal consumption motives decrease the incentive of an investor to acquire private information.     

Updating beliefs about variables given new information on how those variables relate

Bayesian techniques specify how to update beliefs about a variable given information on that variable or related variables. In many cases, statistical analyses also provide information about the relationship between variables, but the Borel Paradox prohibits many natural ways of updating beliefs conditioned on information about a relationship. This paper presents a method by which beliefs can be updated without violating the Borel Paradox under certain circumstances. We apply our approach to relationships specified by a statistical model (i.e., regression), and relationships described by statistical simulation.