Inadmissibility of the uncombined two-stage estimator when additional samples are available

Consider the problem of constructing an estimator with a preassigned bound on the risk for a mean of a normal distribution. The paper shows that the usual two-stage estimator is improved on by combined estimators when additional samples taken from distributions with the same mean and different variances are available.     

Information acquisition and transparency in committees

We study an intertemporal model of committee decision-making where members differ in their levels of efficiency. They may acquire costly information that enhances their ability to make a correct decision. We focus on the impact of transparency. We show that the principal’s initial utility is higher under transparency, because members exert more effort, which makes correct decisions more likely. The principal also benefits from transparency later, unless transparency leads to an alignment of the signal qualities of highly efficient and less efficient committee members. In general, committee members are harmed by transparency. Together with the insights from the literature, our results may help to decide when transparency in committees is desirable.     

Endogenous information acquisition in supply chain management

In this paper, we analyze an endogenous determination of efforts put into information acquisition and its impact on supply chain management. More specifically, we consider a supplier who sells a product to a buyer during a single selling season. Prior to placing an order with the supplier, the buyer has an option to acquire additional information about the demand by hiring experts (who are capable of providing forecasts). Because a commission fee must be paid to each hired expert, there exists a tradeoff between the cost and the value of the information, and the buyer needs to determine how much information to acquire. We derive the optimal information-acquisition level in an integrated setting and compare it with that determined in a decentralized setting. We also analyze several types of supply contracts to examine if they can coordinate the supply chain and allow an arbitrary division of system profit between the supplier and the buyer.     

Coalition formation of oligopolistic firms for information exchange

This paper investigates the coalition formation of oligopolistic firms for exchanges of information about their cost functions in a game-theoretical framework. An oligopolistic market under uncertainty is considered in which each firm knows its own cost function but not those of all the others. The following results are shown. It is profitable for each firm to exchange the information about cost functions with other firms. When the uncertainty levels of the cost functions of all firms are symmetric. it is common interest for them to exchange their information by forming the grand coalition. On the other hand, when their uncertainty levels are highly asymmetric, firms possessing less uncertain cost functions come into conflict with one another when exchanging information exclusively with the most uncertain firms. As a result, more than one coalition may be formed among firms.     

A test for additional information in canonical correlation analysis

Summary In canonical correlation analysis a hypothesis concerning the relevance of a subset of variables from each of the two given variable sets is formulated. The likelihood ratio statistic for the hypothesis and an asymptotic expansion for its null distribution are obtained. In discriminant analysis various alternative forms of a hypothesis concerning the relevance of a specified variable subset are also discussed.     

Information acquisition in new product introduction

In the presence of huge losses from unsuccessful new product introductions, companies often seek forecast information from various sources. As the information can be costly, companies need to determine how much effort to put into acquiring the information. Such a decision is strategically important because an insufficient investment may cause lack of knowledge of product profitability, which in turn may lead to introducing a loss-making product or scrapping a potentially profitable one. In this paper, we use decision analytical models to study information acquisition for new product introduction. Specifically, we consider a decision maker (DM) who, prior to introducing a new product, can purchase forecasts and use the information to update his knowledge of the market demand. We analyze and compare two approaches: The first approach is to determine the total amount of forecasts to purchase all at once. The second one is to purchase forecasts sequentially and, based on the purchased forecasts, determine whether those forecasts are informative enough for making an introduction decision or an additional forecast is needed. We present dynamic programming formulations for both approaches and derive the optimal policies. Via a numerical study, we find the second approach, i.e., purchasing forecasts sequentially, can generate a significant profit advantage over the first one when (1) the cost of acquiring forecasts is neither too high nor too low, (2) the precision of the forecasts is of a moderate level, and (3) the profit margin of the new product is small.     

Deterministic state-based information disclosure policies and social welfare maximization in strategic queueing systems

Queueing Systems - Understanding the impact of the queue length information on the behavior of customers is nowadays a hot topic for strategic queueing problems. Particularly, it is important to...     

On Fisher information inequalities in the presence of nuisance parameters

The existence of a generalized Fisher information matrix for a vector parameter of interest is established for the case where nuisance parameters are present under general conditions. A matrix inequality is established for the information in an estimating function for the vector parameter of interest. It is shown that this inequality leads to a sharper lower bound for the variance matrix of unbiased estimators, for any set of functionally independent functions of parameters of interest, than the lower bound provided by the Cramér-Rao inequality in terms of the full parameter.Supported in part by NSF Grant MCS-8806233.Supported in part by NSF Grants RII-8610671, ATM-9108177 and DMS-9204380.     

Information acquisition interactions in two-player quadratic games

This paper considers two-player quadratic games to examine the relation between strategic interactions in actions and in information decisions. We analyze the role of external effects and of the relative intensities with which the players’ actions interact with the uncertain payoff-relevant parameter. We show that, under some conditions on the quadratic preferences, information choices become substitutes when actions are sufficiently complementary. When attention is restricted to beauty contest games, our results contrast qualitatively with the case studied by Hellwig and Veldkamp (Review of Economic Studies, 76(1)223–251, 2009), where the set of players is a continuum.     

Estimating parameters of polynomial models with errors in variables and no additional information

The problem of estimating a polynomial model with a classical error in the input factor is under consideration in the functional case. The nonparametric method recently introduced for estimating structural dependences does not use any additional information, but it is very effortconsuming computationally and needs samples of large size.We propose some easier methods. The first approach is based on a preliminary estimation of the Berkson error variance under assumption of its normal distribution by the maximum likelihood method for a piecewise linearmodel. This estimate of variance is used for recovering the parameters of a polynomial by the methods of general and adjusted least squares. In case the error variance deviates from normal distribution, an adaptive method is developed that is based on the generalized lambda distribution. These approaches were applied for solving the problem of knowledge level evaluation.     

A game-theoretic analysis of information sharing and security investment for complementary firms

This paper investigates information sharing and security investments by two firms provided that their information assets are complementary in the sense that their combined information assets are of significant value, whereas the information asset of a single firm is no value to an attacker. In particular, assuming that each firm chooses its security investment and information sharing individually, we obtain some insights about the optimal choices for the firms and the attacker, which form sharp comparisons with those derived from common (substitutive) firms. We further analyse the effect of a social planner on social total costs by assuming that it can control security investments, information sharing and both of them respectively. We demonstrate that an increase in intervention by the social planner may not necessarily be preferable.     

Balancing congestion and security in the presence of strategic applicants with private information

Concerns on security and congestion appear in security screening which is used to identify and deter potential threats (e.g., attackers, terrorists, smugglers, spies) among normal applicants wishing to enter an organization, location, or facility. Generally, in-depth screening reduces the risk of being attacked, but creates delays that may deter normal applicants and thus, decrease the welfare of the approver (authority, manager, screener). In this paper, we develop a model to determine the optimal screening policy to maximize the reward from admitting normal applicants net of the penalty from admitting bad applicants. We use an M/M/1 queueing system to capture the impact of security screening policies on system congestion and use game theory to model strategic behavior, in which potential applicants with private information can decide whether to apply based on the observed approver’s screening policy and the submission behavior of other potential applicants. We provide analytical solutions for the optimal non-discriminatory screening policy and numerical illustrations for both the discriminatory and non-discriminatory policies. In addition, we discuss more complex scenarios including imperfect screening, abandonment behavior of normal applicants, and non-zero waiting costs of attackers.     

Controlling for supplier switching in the presence of real options and asymmetric information

Applying a real option approach, this paper examines how asymmetric information alters key variables of a firm’s supplier switching process, such as the timing of contracting (hurried versus delayed contracting), transfer payments, set-up, switching, and abandonment decisions. In a symmetric information setting, delayed contracting is unambiguously beneficial. Abandoning the once established relation with the entrant supplier is never an issue. In contrast, under asymmetric information hurried contracting with potentially abandoning the relation can be beneficial. Consistent with adverse selection models, we find that under delayed contracting, in equilibrium, the firm switches less frequently to the entrant supplier (switching inertia). Surprisingly, we also find that under hurried contracting the firm switches more frequently to the entrant supplier (switching acceleration) and may abandon the relation. Finally, we study how these key variables of the supplier switching process change when also the incumbent supplier has private information (two-sided asymmetric information case).     

Proportion estimation in ranked set sampling in the presence of tie information

Ranked set sampling (RSS) is a statistical technique that uses auxiliary ranking information of unmeasured sample units in an attempt to select a more representative sample that provides better estimation of population parameters than simple random sampling. However, the use of RSS can be hampered by the fact that a complete ranking of units in each set must be specified when implementing RSS. Recently, to allow ties declared as needed, Frey (Environ Ecol Stat 19(3):309–326, 2012) proposed a modification of RSS, which is to simply break ties at random so that a standard ranked set sample is obtained, and meanwhile record the tie structure for use in estimation. Under this RSS variation, several mean estimators were developed and their performance was compared via simulation, with focus on continuous outcome variables. We extend the work of Frey (2012) to binary outcomes and investigate three nonparametric and three likelihood-based proportion estimators (with/without utilizing tie information), among which four are directly extended from existing estimators and the other two are novel. Under different tie-generating mechanisms, we compare the performance of these estimators and draw conclusions based on both simulation and a data example about breast cancer prevalence. Suggestions are made about the choice of the proportion estimator in general.     

The power of the likelihood ratio test for additional information in a multivariate linear model

Summary This paper deals with the likelihood ratio test for additional information in a multivariate linear model. It is shown that the power of the likelihood ratio test procedure has a monotonicity property. Asymptotic approximations for the power are also obtained.     

A game-theoretic analysis of information security investment for multiple firms in a network

The application of Internet of Things promotes the cooperation among firms, and it also introduces some information security issues. Due to the vulnerability of the communication network, firms need to invest in information security technologies to protect their confidential information. In this paper, considering the multiple-step propagation of a security breach in a fully connected network, an information security investment game among n firms is investigated. We make meticulous theoretic and experimental analyses on both the Nash equilibrium solution and the optimal solution. The results show that a larger network size (n) or a larger one-step propagation probability (q) has a negative effect on the Nash equilibrium investment. The optimal investment does not necessarily increase in n or q, and its variation trend depends on the concrete conditions. A compensation mechanism is proposed to encourage firms to coordinate their strategies and invest a higher amount equal to the optimal investment when they make decisions individually. At last, our model is extended by considering another direct breach probability function and another network structure, respectively. We find that a higher connection density of the network will result in a greater expected cost for each firm.     

Modelling the probability assessment of system state prognosis using available condition monitoring information

^** Email: w.wang{at}salford.ac.uk This paper reports on a model to assess the current and futurestates of a monitored system based on measured condition monitoringinformation to date. The true state of the system is unobservable,but is assumed to be related to the measured condition monitoringinformation in a stochastic way. We further assume that thetransition of the system state follows a time-dependent Markovchain which has only three states, namely good, defective andfailed. This assumption effectively defines a two-stage failureprocess which is widely used in delay time modelling of maintainedsystems. Three modelling techniques are used to establish themodel. First, we use a hidden Markov model to describe the transitionsbetween system states. Second, the transition matrix is establishedbased on the well-known delay time concept. The last one isthe use of the filtering technique to construct the relationshipbetween measured condition information and the underlying truestate of the system. We also discuss the procedure for modelparameter estimation. A numerical example is presented to demonstratethe modelling ideas.     

Security investment and information sharing in the market of complementary firms: impact of complementarity degree and industry size

We study a differential game of information security investment and information sharing in a market consisting of n complementary firms. Two game approaches, the non-cooperative game and the totally cooperative game, are employed to investigate the steady state strategy of each firm. Under certain conditions, a unique steady state can be obtained for both games. We find that the steady state security investment and information sharing level are not always less in the non-cooperative game than that in the totally cooperative game. In addition, some theoretical analyses are made on the impacts of the complementarity degree and industry size on firms’ steady state strategies for both games. Finally, some numerical experiments are conducted to give some insights related to the instantaneous profit in the steady state. It can be found that a firm will obtain more instantaneous profit in the steady state of the totally cooperative game than that of the non-cooperative game, which emphasizes the importance of coordinating strategies. The effects of the complementarity degree and industry size on the instantaneous profits in the steady state are also obtained through the numerical experiment results.     

Estimation of unknown parameters of linear regression in the presence of prior information

Problems of the best estimation of unknown parameters of a linear regression in the Hilbert space in the presence of various prior information are investigated. Optimal designs for a class of designs often encountered in applications are constructed.Translated from Ukrainskii Matematicheskii Zhurnal, Vol. 43, No. 5, pp. 688–696, May, 1991.