A Service Provider's Elicitation of Its Customers’ Demand Distributions by a Price Mechanism

In a service environment a service provider needs to determine the amount and kinds of capacity to meet customers’ needs over many periods. To make good decisions, she needs to know the probability distribution of her customers’ demand in each period. We study a situation in which customers’ demand for a given service is random in each period, but inelastic, or modeled well by this assumption, and cannot be delayed to the next period. This article presents a mechanism that allows a service provider to learn the distribution of a customer's demand by offering him a set of contracts through which he can partially prepay for future service for a reduced cost for units of service based on anticipated needs. We describe the form of a set of contracts that will cause the customer to reveal his demand distribution as he minimizes his expected costs. To justify the effort of organizing and offering contracts, we present an application that demonstrates the cost savings to the service provider with better capacity planning using the truthfully elicited distribution.     

Complex Questionnaires

We study a principal–agent model in which the agent is boundedly rational in his ability to understand the principal's decision rule. The principal wishes to elicit an agent's true profile so as to determine whether or not to grant him a certain request. The principal designs a questionnaire and commits himself to accepting certain responses. In designing such a questionnaire, the principal takes into account the bounded rationality of the agent and wishes to reduce the success probability of a dishonest agent who is trying to game the system. It is shown that the principal can construct a sufficiently complex questionnaire that will allow him to respond optimally to agents who tell the truth and at the same time to almost eliminate the probability that a dishonest agent will succeed in cheating.     

Producer's and Consumer's Risk When Proportion Defective Is a Random Variable

In acceptance sampling, producer's and consumer's risk are traditionally based on assumed fixed values of p, the proportion of the lot which is defective. A more useful definition of producer's risk would be the probability of rejecting a lot in which the proportion defective falls within some range of acceptable values. Similarly, a more useful definition of consumer's risk would be the probability of accepting a lot in which the proportion defective falls within some range of unacceptable values. In this paper, we construct measures of these more useful definitions of risk by assuming that p follows either a uniform or triangular probability distribution. The proposed measure yields consumer's risk values, β', which are smaller than the traditionally computed values by a factor of up to twenty times. The proposed measure of producer's risk, α', gives values smaller than traditional values by a factor of two to four times. Decision makers who adopt the proposed measures may be able to reduce sample sizes substantially while maintaining given risk levels.     

A BRIDGE FOR TWO CULTURES C. JACKSON GRAYSON,JR., CHAIRMAN,PRICE COMMISSION

C. Jackson Grayson, Jr. was the invited speaker at the President's Luncheon of the Fourth Annual Meeting of the American Institute for Decision Sciences. His remarks dwelt on the relation of his experience as a scientist and academician to the tasks he faced in his assignment with the Price Commission. Dr. Grayson is currently on leave from his post as Dean of the School of Business Administration at Southern Methodist University.     

Subjective Probabilities on Subjectively Unambiguous Events

This paper suggests a behavioral definition of (subjective) ambiguity in an abstract setting where objects of choice are Savage‐style acts. Then axioms are described that deliver probabilistic sophistication of preference on the set of unambiguous acts. In particular, both the domain and the values of the decision‐maker's probability measure are derived from preference. It is argued that the noted result also provides a decision‐theoretic foundation for the Knightian distinction between risk and ambiguity.     

Social Indeterminacy

An extension of Condorcet's paradox by McGarvey (1953) asserts that for every asymmetric relation R on a finite set of candidates there is a strict‐preferences voter profile that has the relation R as its strict simple majority relation. We prove that McGarvey's theorem can be extended to arbitrary neutral monotone social welfare functions that can be described by a strong simple game G if the voting power of each individual, measured by the Shapley–Shubik power index, is sufficiently small. Our proof is based on an extension to another classic result concerning the majority rule. Condorcet studied an election between two candidates in which the voters' choices are random and independent and the probability of a voter choosing the first candidate is p>1/2. Condorcet's jury theorem asserts that if the number of voters tends to infinity then the probability that the first candidate will be elected tends to one. We prove that this assertion extends to a sequence of arbitrary monotone strong simple games if and only if the maximum voting power for all individuals tends to zero.     

Large Matching Markets as Two‐Sided Demand Systems

This paper studies two‐sided matching markets with non‐transferable utility when the number of market participants grows large. We consider a model in which each agent has a random preference ordering over individual potential matching partners, and agents' types are only partially observed by the econometrician. We show that in a large market, the inclusive value is a sufficient statistic for an agent's endogenous choice set with respect to the probability of being matched to a spouse of a given observable type. Furthermore, while the number of pairwise stable matchings for a typical realization of random utilities grows at a fast rate as the number of market participants increases, the inclusive values resulting from any stable matching converge to a unique deterministic limit. We can therefore characterize the limiting distribution of the matching market as the unique solution to a fixed‐point condition on the inclusive values. Finally we analyze identification and estimation of payoff parameters from the asymptotic distribution of observable characteristics at the level of pairs resulting from a stable matching.     

A case-based distance method for screening in multiple-criteria decision aid

Screening is a process of multiple-criteria decision aid (MCDA) in which a large set of alternatives is reduced to a smaller set that most likely contains the best choice. We propose screening using a distance model calibrated on the basis of the decision-maker's own judgement. Viewing MCDA as preference aggregation based on consequence data, we define consequence and preference expressions (values and weights) and describe how they are aggregated. Then we define screening and explain some of its properties. Using an appropriate definition of distance, our case-based distance method screens a set of alternatives using criterion weights and a distance threshold obtained by quadratic optimization using the decision-maker's selection of alternatives from a test set. This case-based method can elicit the decision maker's preferences more expeditiously and accurately than direct inquiry. An application in water supply planning is used to demonstrate the procedure.     

Inductive Risk,Science, and Values: A Reply to MacGillivray

The argument from inductive risk (AIR) is perhaps the most common argument against the value-free ideal of science. Brian MacGillivray rejects the AIR (at least as it would apply to risk assessment) and embraces the value-free ideal. We clarify the issues at stake and argue that MacGillivray's criticisms, although effective against some formulations of the AIR, fail to overcome the essential concerns that motivate the AIR. There are inevitable trade-offs in scientific enquiry that cannot be resolved with any formal methods or general rules. Choices must be made, and values will be involved. It is best to recognize this explicitly. Even so, there is more work to be done developing methods and institutional support for these choices.     

An Efficient Dynamic Mechanism

This paper constructs an efficient, budget‐balanced, Bayesian incentive‐compatible mechanism for a general dynamic environment with quasilinear payoffs in which agents observe private information and decisions are made over countably many periods. First, under the assumption of “private values” (other agents' private information does not directly affect an agent's payoffs), we construct an efficient, ex post incentive‐compatible mechanism, which is not budget‐balanced. Second, under the assumption of “independent types” (the distribution of each agent's private information is not directly affected by other agents' private information), we show how the budget can be balanced without compromising agents' incentives. Finally, we show that the mechanism can be made self‐enforcing when agents are sufficiently patient and the induced stochastic process over types is an ergodic finite Markov chain.     

社会保险与家庭金融风险资产投资

社会保险是否影响家庭在金融风险资产中的投资决策呢?本文使用两期家庭最优决策模型得到的理论分析结果表明,社会保险不仅能够提高家庭在风险资产中的投资广度和深度,而且对于不确定性更大、风险承受更强家庭的影响更为显著.基于省级层面得到的宏观实证检验结果和基于2011年家庭金融调查数据得到家庭层面的微观实证检验结果都支持了上述理论结论.本文的发现对于协调社会保险发展和建立多层级金融市场具有很强的政策意义.     

An Auction Mechanism for Pricing and Capacity Allocation with Multiple Products

We consider a pricing and short‐term capacity allocation problem in the presence of buyers with orders for bundles of products. The supplier's objective is to maximize her net profit, computed as the difference between the revenue generated through sales of products and the production and inventory holding costs. The objective of each buyer is similarly profit maximization, where a buyer's profit is computed as the difference between the time‐dependent utility of the product bundle he plans to buy, expressed in monetary terms, and the price of the bundle. We assume that bundles' utilities are buyers' private information and address the problem of allocating the facility's output. We directly consider the products that constitute the supplier's output as market goods. We study the case where the supplier follows an anonymous and linear pricing strategy, with extensions that include quantity discounts and time‐dependent product and delivery prices. In this setting, the winner determination problem integrates the capacity allocation and scheduling decisions. We propose an iterative auction mechanism with non‐decreasing prices to solve this complex problem, and present a computational analysis to investigate the efficiency of the proposed method under supplier's different pricing strategies. Our analysis shows that the problem with private information can be effectively solved with the proposed auction mechanism. Furthermore, the results indicate that the auction mechanism achieves more than 80% of the system's profit, and the supplier receives a higher percentage of profit especially when the ratio of demand to available capacity is high.     

Stock screening with use of multiple criteria decision making and optimization

A new method for the stock ranking based on the multiple criterion decision making and optimization is proposed. Two general criteria are used in the analysis. The first of them is based on the financial indices and may be treated as the criterion of firm's “health” or its financial performance. The second one is the two-criteria performance of firm based on the stock prices. It represents the firm's market success. The method rests on the selection of the stocks with a great correlation of the firm's financial performance and its market success. The local criteria are built in the form of the membership function of corresponding fuzzy subsets. Two different strategies for stock ranking and three most popular methods for local criteria aggregation are compared. As the example the values of financial rations and prices from database comprising the data of 162 firms from subsector of the biotechnology of US economy were used. It is shown that the proposed method makes it possible to select a small group of “good” stocks characterized by a great coincidence of firm's financial performance and its market success. The method rejects from the consideration all the “unsafe” firms, i.e., such ones that their market success is based rather on the public relations, rumors and other rather unreliable information. The method is addressed to those who prefer to select for a portfolio only the firms which demonstrate the closeness of their overall financial performance in the past year and success in the Stock Exchange in the following year.     

公平感对供应链成员定价决策影响的研究

本文研究公平感对由一个供应商和一个零售商组成的二级供应链中的定价决策的影响,其中供应商决定批发价格,零售商在接受供应商批发价格合同之后决定零售价格,市场需求受到零售价格的线性影响.采用管理实验方法得出,首先,供应商的批发价格和零售商的零售价格均分别低于完全理性假设下的均衡解;供应商是利他性的,即,乐于看到零售商收益的增加,并且,供应商认为零售商是完全理性的,即零售商的决策目标是最大化自身收益;然而,零售商却是刻毒性的,即乐于看到供应商收益的减少.其次,批发价格的变异度大于零售价格的,即供应商决策的难度大于零售商的.给管理者的启示是:供应商应考虑零售商的刻毒性的特征,降低批发价格,以提高零售商接受供应商所提批发价格的概率;此外,还应该为供应商提供辅助决策手段,以降低批发价格的变异度,提高决策的准确性     

Optimal Procurement Design of an Assembly Supply Chain with Information Asymmetry

We study a decentralized assembly supply chain in which an assembler (she) assembles a set of n components, each produced by a different supplier (he), into a final product to satisfy an uncertain market demand. Each supplier holds private cost information to himself, for which the assembler only has a subjective estimate. Furthermore, the assembler believes that the suppliers' costs follow a joint discrete probability distribution. The assembler aims to design an optimal menu of contracts to maximize her own expected profit. The assembler's problem is a complex multi‐dimensional constrained optimization problem. We prove that there exists a unique optimal menu of contracts for the assembler, and we further develop an efficient algorithm with a complexity of O(n) to compute the optimal contract. In addition, we conduct a comprehensive sensitivity analysis to analyze how environmental parameters affect individual firm's performance and the value of information to the assembler, to each supplier, and to the supply chain. Our results suggest that each supplier's private cost information becomes more valuable to the assembler and each supplier when the average market demand increases or when the final product unit revenue increases. Surprisingly, when a supplier's cost volatility increases and its mean remains the same, the value of information to the assembler or to each supplier does not necessarily increase. Furthermore, we show that when the suppliers' cost distributions become more positively correlated, the suppliers are always worse off, but the assembler is better off. However, the value of information for the assembler might increase or decrease.     

The annual planning cycle

The practical business man, be he the boss or an employee, usually accepts that systematic planning of some sort is almost certain to be of benefit to his company, and he can usually agree with many of the planning techniques put forward. What often worries him though, is how to actually operate a planning system in his company day by day: what instructions to give, systems to use, how to make it really work. In this article, the author describes an Annual Planning and Budget Cycle Chart which was developed at the Avon Rubber Company. This chart goes a long way to solving the practical businessman's dilemma referred to above, it gives set dates during the year for completion of specific planning and budgeting jobs and it explains how they are interconnected to make up a coherent and workable corporate planning system.     

Clarifying the Dominant Logic Construct by Disentangling and Reassembling its Dimensions

Since its introduction, Prahalad and Bettis's concept of dominant logic has informed a variety of scholarly conversations in management and strategy research. However, scholars have interpreted dominant logic in different ways, emphasizing different aspects, such as managerial mindsets, administrative tools and management functions, as defining elements. Similarly, empirical studies have captured various aspects, such as meanings of entrepreneurs, observable strategic decisions and business model similarity, as indicators of dominant logic. Consequently, the concept lacks analytical clarity, and it is difficult to compare or generalize findings from this diverse set of studies. The aim of this review is to improve conceptual clarity by analysing, comparing and evaluating the existing interpretations and assessments of dominant logic in 94 studies. In the first part of the review, by disentangling the interpretations of the concept, we show that dominant logic consists of four defining dimensions: (i) shared mental models; (ii) values and premises; (iii) organizational practices; and (iv) organizing structures. In the second part, we reassemble dominant logic into an integrative model and theorize about how these dimensions operate in concert to produce a firm's dominant logic. Thus, our main contribution is a clarification and synthesis of the literature, which comes with implications on how future research can conceptualize and operationalize dominant logic more consistently.     

A Smooth Model of Decision Making under Ambiguity

We propose and characterize a model of preferences over acts such that the decision maker prefers act f to act g if and only if 𝔼_μφ(𝔼_πu○f) 𝔼_μφ(𝔼_πu○g), where 𝔼 is the expectation operator, u is a von Neumann–Morgenstern utility function, φis an increasing transformation, and μis a subjective probability over the set Πof probability measures πthat the decision maker thinks are relevant given his subjective information. A key feature of our model is that it achieves a separation between ambiguity, identified as a characteristic of the decision maker's subjective beliefs, and ambiguity attitude, a characteristic of the decision maker's tastes. We show that attitudes toward pure risk are characterized by the shape of u, as usual, while attitudes toward ambiguity are characterized by the shape of φ. Ambiguity itself is defined behaviorally and is shown to be characterized by properties of the subjective set of measures Π. One advantage of this model is that the well‐developed machinery for dealing with risk attitudes can be applied as well to ambiguity attitudes. The model is also distinct from many in the literature on ambiguity in that it allows smooth, rather than kinked, indifference curves. This leads to different behavior and improved tractability, while still sharing the main features (e.g., Ellsberg's paradox). The maxmin expected utility model (e.g., Gilboa and Schmeidler (1989)) with a given set of measures may be seen as a limiting case of our model with infinite ambiguity aversion. Two illustrative portfolio choice examples are offered.     

MULTICRITERIA OPTIMIZATION: A GENERAL CHARACTERIZATION OF EFFICIENT SOLUTIONS*

In the context of deterministic multicriteria maximization, a Pareto optimal, nondominated, or efficient solution is a feasible solution for which an increase in value of any one criterion can only be achieved at the expense of a decrease in value of at least one other criterion. Without restrictions of convexity or continuity, it is shown that a solution is efficient if and only if it solves an optimization problem that bounds the various criteria values from below and maximizes a strictly increasing function of these several criteria values. Also included are discussions of previous work concerned with generating or characterizing the set of efficient solutions, and of the interactive approach for resolving multicriteria optimization problems. The final section argues that the paper's main result should not actually be used to generate the set of efficient solutions, relates this result to Simon's theory of satisficing, and then indicates why and how it can be used as the basis for interactive procedures with desirable characteristics.     

INSIGHTS ON SERVICE SYSTEM DESIGN FROM A NORMAL APPROXIMATION TO ERLANG'S DELAY FORMULA

We show how a simple normal approximation to Erlang's delay formula can be used to analyze capacity and staffing problems in service systems that can be modeled as M/M/s queues. The numbers of servers, s, needed in an M/M/s queueing system to assure a probability of delay of, at most, p can be well approximated by s ≅ p + z_***I-p+, where z_1-p, is the (1 - p)th percentile of the standard normal distribution and ρ, the presented load on the system, is the ratio of Λ, the customer arrival rate, to μ, the service rate. We examine the accuracy of this approximation over a set of parameters typical of service operations ranging from police patrol, through telemarketing to automatic teller machines, and we demonstrate that it tends to slightly underestimate the number of servers actually needed to hit the delay probability target—adding one server to the number suggested by the above formula typically gives the exact result. More importantly, the structure of the approximation promotes operational insight by explicitly linking the number of servers with server utilization and the customer service level. Using a scenario based on an actual teleservicing operation, we show how operations managers and designers can quickly obtain insights about the trade-offs between system size, system utilization and customer service. We argue that this little used approach deserves a prominent role in the operations analyst's and operations manager's toolbags.