零售商的风险规避特性和公平偏好对绿色供应链运作的影响

针对市场需求的不确定性,本文通过建立风险规避型零售商与风险中性供应商的Stackelberg博弈模型,供应商为主导者,综合考虑零售商风险规避特性和公平偏好心理对该供应链运作产生的影响。研究发现,当风险规避型零售商不具有公平意识时,零售商的风险规避程度与供应商的批发价、绿色创新投入水平以及供应商和供应链整体的效用正相关;供应商的绿色成本系数的大小可影响风险规避程度对产品售价以及零售商效用的影响。当风险规避型零售商具有公平偏好时,零售商的公平偏好负向影响产品售价、批发价以及供应商绿色投入水平和供应商效用;零售商公平偏好对零售商以及供应链效用产生的影响受到零售商风险规避程度的影响。     

Collusion Under Risk Aversion and Fixed Costs

We analyze collusion under demand uncertainty by risk‐averse cartels that care about the utility derived from profits. With sufficient risk aversion and non‐trivial fixed operating costs, it becomes difficult for cartels to collusively restrict output both when demand is low and marginal dollars are highly valued, and when demand is high and potential defection profits are high: output relative to monopoly levels becomes a U‐shaped function of demand. Greater risk aversion or higher fixed operating costs make collusion more difficult to support in recessions, but easier to support in booms.     

Optimal pricing and quality choice of a monopolist under Knightian uncertainty

This paper analyzes a simple vertical product differentiation model with demand uncertainty and derives a risk neutral monopolist's optimal market entry timing, her optimal pricing and optimal quality choice by incorporating Knightian uncertainty, irreversibility, and flexibility in quality-enhancing investment into a continuous-time stochastic model. It is shown that an increase in Knightian uncertainty induces decreases in the optimal price, the optimal quality, and the value of undertaking the quality-enhancing investment by the monopolist. The social optimal entry timing, pricing and quality are also analyzed.     

Customer and retailer rebates under risk aversion

In a supply chain setting, we analyze a manufacturer's customer and retailer rebates, which are sales incentives offered to the end buyers and retailers, respectively. The performance of both rebates is influenced by the retailer's objective and response to the promotion due to his intermediary position in the channel. Earlier studies investigating rebates in distribution channels have traditionally assumed that the retailer is risk neutral with the objective of maximizing expected profits. In our paper, we consider a risk-averse retailer. We formally model risk aversion by adopting the Conditional-Value-at-Risk (CVaR) decision criterion. Using a stochastic and (effective) price dependent demand, we analyze the manufacturer's rebate amount decisions and the retailer's joint inventory and pricing decisions in a game theoretical framework. We provide several structural properties of the objective functions and show monotonicity of the retailer's decisions in the degree of risk aversion. For the case of retailer rebates, we characterize the unique equilibrium, and for the case of customer rebates, we prove the existence of an equilibrium. Using numerical examples, we provide further insights on the impact of risk aversion. For example, given an exogenous wholesale price, we observe a threshold value on the retailer's risk-aversion parameter below (above) which the manufacturer is better off with retailer rebates (customer rebates); implying that the manufacturer's preferred rebate type can be different depending on whether the retailer is risk neutral or sufficiently risk averse.     

Optimal Capacity,Product Substitution,Linear Demand Models,and Uncertainty

We study the capacity, pricing, and production decisions of a monopolist producing two substitutable products with flexible capacity. Although the capacity decision needs to be made ex ante, under demand uncertainty, pricing and production decisions can be postponed until after uncertainty is resolved. We show how key demand parameters (the nature of uncertainty, market size, and market risk) impact the optimal capacity decision under the linear demand function. In particular, we show that if the demand shock is multiplicative, then in terms of the “invest or not” decision, the firm will be immune to forecast errors in parameters of the underlying demand distribution. Furthermore, incorrectly modeling the demand shock as additive, when, in fact, it is multiplicative, may lead to overinvestment. On the other hand, although the concept of a growth in market size leads to similar conclusions under both additive and multiplicative demand shocks, how market risk affects the optimal capacity decision depends critically on the form of the demand shock as well as its correlation structure. Our analysis provides insights and principles on the optimal capacity investment decision under various demand settings.     

On the strategic value of risk management

This article examines how firms facing volatile input prices and holding some degree of market power in their product market link their risk management and their production or pricing strategies. This issue is relevant in many industries ranging from manufacturing to energy retailing, where firms that are rendered “risk averse” by financial frictions decide on and commit to their hedging strategies before their product market strategies. We find that commitment to hedging modifies the pricing and production strategies of firms. This strategic effect is channeled through the risk-adjusted expected cost, i.e., the expected marginal cost under the probability measure induced by shareholders' “risk aversion”. It has opposite effects depending on the nature of product market competition: commitment to hedging toughens quantity competition while it softens price competition. Finally, not committing to the hedging position can never be an equilibrium outcome: committing is always a best response to non-committing. In the Hotelling model, committing is a dominant strategy for all firms.     

Optimal Pricing and Order-Up-To S Inventory Policy with Expected Utility of the Present Value Criterion

The article determines pricing and order-up-to level S inventory decisions over an infinite planning horizon from the point of view of a risk-averse decision maker. The demand is assumed to be stochastic but influenced by the selling price which is a decision variable. Shortages are allowed and backordered partially. We calculate the present value of the cash flow over the entire planning horizon and incorporate the notion of risk aversion into the model using a concave utility function. We numerically demonstrate the model and investigate the impact of different model-parameters on the optimal decisions. It is observed that the optimal selling price for a risk-averse decision maker is not less than the optimal selling price of a risk-neutral decision maker while the optimal order level for the risk-averse decision maker is always less than that of the risk-neutral decision maker.     

Entry,imperfect competition,and futures market for the input

We analyze firms' entry, production and hedging decisions under imperfect competition. We consider an oligopoly industry producing a homogeneous output in which risk-averse firms face an entry cost upon entering the industry, and then compete in Cournot with one another. Each firm faces uncertainty in the input cost when making production decision, and has access to the futures market to hedge the random cost. We provide two sets of results. First, under general assumptions about risk preferences, demand, and uncertainty, we characterize the unique equilibrium. In contrast to previous results in the literature (without entry), both production and output price depend on uncertainty and risk aversion. Specifically, when entry is endogenized and the futures price is not actuarially fair, access to the futures market does not lead to separation. Second, to study the effect of access to the futures market on entry and production, we restrict attention to constant absolute risk aversion (CARA) preferences, a linear demand, and a normal distribution for the spot price. In general, the effect of access to the futures market on the number of firms and production is ambiguous.     

Sustaining Collusion Via a Fuzzy Trigger

Probability theory is the standard economic representation of uncertainty, although it is not always an accurate one. Fuzzy logic is an alternative representation that does not require individual beliefs regarding the explicit functional form of uncertainty. This paper applies fuzzy logic to an oligopoly trigger pricing game. The fuzzy trigger pricing game reverses the standard cyclical price war prediction; collusion-sustaining price wars are most likely to occur during times of high demand. The fuzzy model also predicts that markets with relatively volatile prices are more likely to undergo collusion-sustaining price wars. The predictions are consistent with available empirical evidence.     

Financial and operational decisions in the electricity sector: Contract portfolio optimization with the conditional value-at-risk criterion

The restructuring of electricity markets around the world have caused increased volatility and uncertainty of the price power. As a result, providers of power now face increased uncertainty and risk in the operational and financial decisions related to procurement. Providers must seek optimal ways to deliver the required volume of power to retailers and end users while managing risk. We consider a mixed-integer programming model for a power providing agent that jointly considers the problem of selecting custom electricity contracts and finding the optimal procurement strategy of meeting contract obligations under spot price uncertainty. A two-stage stochastic integer programming (SIP) model with a conditional value-at-risk (CVaR) constraint to incorporate risk aversion is developed. Computational results are presented that demonstrates the CVaR approach and the results are compared with a corresponding expected cost minimization approach. The SIP model with CVaR will allow acceptance of contracts at lower prices compared to an approach based on a corresponding risk-neutral model as a hedge against uncertainty and mis-specified arbitrage.     

Multiproduct Price Regulation Under Asymmetric Information

We discuss the regulation of a multiproduct monopolist when the firm has private information about cost or demand conditions. The regulator offers the firm a set of prices from which to choose. When there is private information only about costs, the firm should always have a degree of discretion over its pricing policy. When uncertainty concerns demand, whether discretion is desirable depends on how demand elasticities vary with the scale of demands. If a positive demand shock is associated with a reduction in the market elasticity, discretion is good for overall welfare; otherwise it is not.     

Price reaction functions and conjectural variations

Price conjectural variations are estimated to measure the degree of price competition in a product differentiated oligopoly. The empirical model is a simultaneous equation system of product demand and price reaction functions. Own and cross price demand elasticities are estimated in conjunction with the price conjectural variations and price reaction function elasticities. The conjectural variations are estimated for pairs of ready-to-eat breakfast cereal products using brand price and quantity data. The empirical results reject competitive brand pricing behavior in favor of independent or collusive pricing. Further, the hypothesis of a unique consistent conjecture is rejected.     

Real Option Pricing and Bounds in Incomplete Markets

This article prices a real option and constructs narrow bounds around the value of real options embedded in capital budgeting decisions by applying the minimax deviations approach to real options in incomplete markets. While it is straightforward to obtain the unique value of a real option with hyperbolic absolute risk aversion (HARA) utility functions, the parameters of risk aversion are often subject to misspecification and raise concerns for practical uses. Recognizing that investors allow deviation from parameter values related to a benchmark pricing kernel, we derive narrow bounds on a real option price. Comparison with the approaches in the literature clarifies advantages of the minimax bounds: simple, consistent, and efficient.     

Loss Aversion and Anchoring in Commercial Real Estate Pricing: Empirical Evidence and Price Index Implications

Loss aversion behavior plays a major role in the pricing of commercial properties, and it varies both across the type of market participants and across the cycle. We find that sophisticated and more experienced investors are at least as loss averse as their counterparts and that loss aversion operated most strongly during the cycle peak in 2007. We also document a possible anchoring effect of the asking price in influencing buyer valuation and subsequent transaction price. We demonstrate the importance of behavioral phenomena in constructing hedonic price indices, and we find that the impact of loss aversion is attenuated at the aggregate market level. This suggests that the pricing and volume cycle during 2001–2009 was little affected by loss aversion.     

Moving beyond intuition—Managing allocation decisions in relationship marketing in business-to-business markets

Developing and estimating structural models is becoming a routine practice in marketing. In this study, the possibilities of applying such models in managerial decision making under uncertainty are investigated. In particular the feasibility of exploiting the inherent probabilistic nature of structural models to buttress decision making is demonstrated. The approach is based on making heavy use of standard simulation routines. The model that is under scrutiny describes the relationships between firms' efforts in three areas (the offer, customer relationships, and market positions) on the success of a new product introduction. Special attention is given to the aspect of risk aversion. Accounting for the risk attitude implies different allocation decisions for risk-averse compared to risk-prone managers, in line with common sense.     

Metaheuristic-based simulation optimization approach to network revenue management with an improved self-adjusting bid price function

Making accurate accept/reject decisions on dynamically arriving customer requests for different combinations of resources is a challenging task under uncertainty of competitors' pricing strategies. Because customer demand may be affected by a competitor's pricing action, changes in customer interarrival times should also be considered in capacity control procedures. In this article, a simulation model is developed for a bid price–based capacity control problem of an airline network revenue management system by considering the uncertain nature of booking cancellations and competitors' pricing strategy. An improved bid price function is proposed by considering competitors' different pricing scenarios that occur with different probabilities and their effects on the customers' demands. The classical deterministic linear program (DLP) is reformulated to determine the initial base bid prices that are utilized as control parameters in the proposed self-adjusting bid price function. Furthermore, a simulation optimization approach is applied in order to determine the appropriate values of the coefficients in the bid price function. Different evolutionary computation techniques such as differential evolution (DE), particle swarm optimization (PSO), and seeker optimization algorithm (SOA), are utilized to determine these coefficients along with comparisons. The computational experiments show that promising results can be obtained by making use of the proposed metaheuristic-based simulation optimization approach.     

Risk aversion and auction design: Theoretical and empirical evidence

Auctions are inherently risky: bidders face uncertainty about their prospects of winning and payments, while sellers are unsure about revenue and chances of a successful sale. Auction rules influence the allocation of risk among agents and the behavior of risk-averse bidders, leading to a breakdown of payoff and revenue equivalence and a heightened significance of auction design decisions by sellers. In this paper, we review the literature on risk aversion in auctions, with an emphasis on what can be learned about auction design from theoretical modeling and empirical studies. We survey theoretical results relating to the behavior of risk-averse agents in auctions, the comparison of standard auction formats in the presence of risk aversion and implications for auction design. We discuss standard and more recent approaches to identifying risk preferences in empirical studies and evidence for the significance of risk aversion in auction applications. Finally, we identify areas where existing evidence is relatively scant and ask what questions empirical research might ask given the theory and where further theoretical research may be beneficial given existing empirical results.     

Resale price maintenance for supply chains distributing products with demand uncertainty

This paper explores the economic roles of resale price maintenance (RPM) in supply chains for a specific product, when consumers have taste heterogeneity and the manufacturer faces demand uncertainty. Two transaction schemes within supply chains are compared: (1) RPM, and (2) decentralized pricing in a competitive market environment. With decentralized pricing, a manufacturer loses the incentive to produce a product in categories where the probability that the manufacturer fails to design the product as suitable to public tastes of consumers is high. However, RPM resolves the problem and induces the manufacturer to supply the good, bringing positive surplus to consumers.     

Investment under Demand Uncertainty,Ex-Ante Pricing,and Oligopoly

This paper considers the capacity choice of duopolists who set price ex-ante under demand uncertainty with risk-neutrality. The duopolists compete for market shares on the basis of availability of supply, rather than by price competition. Collusive pricing coexists with Cournot–Nash capacity choice. A formal model is presented, where the market share of each firm may deviate from the certainty share due to rationing. With shares reflecting different costs, capacity utilisation for the lower cost firm is expected to be substantially lower. The implications for the price-cost margin and capacity formation are also explored.