Strategic control and interests,its effects on decision outcomes

Application of the model to artificial data shows that actors with strong preferences in the center have more possibilities to realize good outcomes than other actors. On the basis of an empirical application it is shown that a Nash equilibrium does not always arise after a large number of iterations unless actors have learning capabilities or are severely restricted in their strategic behavior.

In political systems and large organizations, ultimate decision makers are usually just a small subset of all actors in the social system. To arrive at acceptable decisions, decision makers have to take into account the preferences of other actors in the system. Typically preferences of more interested and more powerful actors are weighted heavier than those of less interested and powerful actors. This implies that the total leverage of an actor on the decision is determined by the combination of his power (his potential) and his interest (his willingness to mobilize his power). As the exact level of an actor's leverage is difficult to estimate for the other actors in the system, an actor is able to optimize his effects on outcomes of decisions by providing strategic informatioa

In this paper, first an analytic solution is presented for the optimization of strategic leverage in collective decision making by one single actor. In this solution, the actor makes assumptions about the leverage other actors will show in decision making. Subsequently, the actor optimizes the outcomes of decisions by manipulating the distribution of his leverage over a set of issues.

The analytic solution can be theoretically interpreted by decomposing the solution into three terms, the expected external leverage of the other actors on the issue, the evaluation of the deviance of the expected from the preferred outcome of the issue, and the restrictions on the distribution of leverage over the issues. The higher the expectation of the leverages the other actors will allocate to the issue, the less an actor is inclined to allocate leverage to the issue. The higher the evaluation of the deviance, the more an actor is inclined to allocate leverage to the issue. This is restricted, however, by the required distribution of leverages over the issues. The researcher is able to manipulate these restrictions to investigate its consequences for the outcomes.

In the next step, we investigate whether we can find a Nash equilibrium if all actors optimize their leverage simultaneously. Under certain conditions, a Nash equilibrium can be found by an iterative process in which actors update their estimates oh each other's leverages on the basis of what the other actors have shown in previous iterations.     

Contending “signals” in coalition choice 1

During negotiations for coalitions, each actor presumably searches his decision environment for organizing principles—signals—which, if present, would turn the negotiations in his favor. With only one prominent signal, we expect it to determine the nature of agreements, but things may be different with multiple signals. Data from four studies of a weighted‐majority game, two using only relative status of winnings in the game as the incentive (i.e., rank position of points accumulated) and two also using monetary reward as an incentive, are analyzed. Both relative status and resources (weights) were apparent to subjects in the studies. Results for coalitions and for payoffs show that a theory based on resources as the signal and one based on status as the signal both separately achieve success in the same bodies of data. As expected, the status‐signal theory better predicted coalitions in the two status‐reward studies, and the resource‐signal theory better predicted in the monetary‐reward studies. However, in all four studies, a two‐signal model which accounts for the reinforcing effects of signals achieves greater success. This indicates the importance of analyzing actors’ adoption of signals into their decision process, particularly in multisignal environments.     

Scheduling unit — time tasks on flow — shops under resource constraints

We consider the problem of scheduling tasks on flow shops when each task may also require the use of additional resources. It is assumed that all operations have unit lengths, the resource requirements are of 0–1 type and there is one type of the additional resource in the system. It is proved that when the number of machines is arbitrary, the problem of minimizing schedule length is NP-hard, even when only one unit of the additional resource is available in the system. On the other hand, when the number of machines is fixed, then the problem is solvable in polynomial time, even for an arbitrary number of resource units available. For the two machine case anO(n log ₂ ² n) algorithm minimizing maximum lateness is also given. The presented results are also of importance in some message transmission systems.     

Optimal sharing

We investigate a sharing method to distribute a given quantity of resources equitably through a capacity-constrained distribution network. The sharing, called an optimal sharing, not only maximizes the minimum share but also minimizes the maximum share. The optimal sharing is obtained in time O(|T| c(n e)) where |T| is the number of sinks in the network andc(n, e) is the time required to solve the maximum flow problem.     

Hierarchical Discrete Models of Competition for a Resource

A coupled pair of first order nonlinear discrete hierarchical age-structured models are applied to study two modes of intraspecific competitions; scramble and contest. The study focuses on several comparisons of the dynamical outcomes of the two competitions. For a constant resource, it is shown, using analytical and numerical approaches, that solutions of the contest model monotonically equilibrate, while solutions of the scramble model oscillate and become chaotic. It is also shown that the inherent net reproductive number of each population affects the comparison of equilibrium points in the two populations. By considering cases on the resource and model parameters, the local as well as the global stability of nontrivial equilibrium points are studied. The impact of a contest and a scramble consumer on a time dependent resource is considered numerically.     

Parallel systems under two sequential attacks with contest intensity variation

Single and double attacks against a system of parallel elements are analyzed. The vulnerability of each element depends on an attacker-defender contest success function. The contest intensity may change from the first to the second attack as determined by a contest intensity variation factor. The defender allocates its resource between deploying elements to provide redundancy, and protecting each element. The attacker allocates its resource optimally across the two attacks, may attack a subset of the elements in the first attack, observes which elements are destroyed in the first attack, and attacks all surviving elements in the second attack. A minmax two period game is analyzed where the defender moves first and the attacker moves second. The paper shows how the contest intensity variation factor affects the defense and attack strategies.     

Silent-noisy marksmanship contest with random termination

We consider a marksmanship contest in which Player I has one silent bullet, whereas Player II has one noisy bullet, the first contestant to hit his target wins, and the contest is to be terminated at a random timeT with cdfH(t). The model is a silent-noisy version of our previous paper (Ref. 8), and an extension of silent-noisy duel to nonzero-sum games of timing under an uncertain environment. It is shown that the uncertainty on the termination of the contest has influence on the equilibrium strategies and the equilibrium values, but the silent player has no advantages over the noisy one, in such a nonzero-sum model.The author thanks Professor M. Sakaguchi, Osaka University, who contributed to the research on mathematical decision-making problems and expresses appreciation for his continuous encouragement and guidance. The author also thanks Professor G. Kimeldorf, The University of Texas at Dallas, who invited the author to his university. Finally, the author expresses appreciation to Professors K. Sugahara and W. Fukui, Himeji Institute of Technology, for their encouragement and support.     

Trust,assurance, and inequality: A rational choice model of mutual trust 1

The rational choice approach to trust has three problems: it has not explicitly explained findings verified in social psychological study of trust; it stands on a limited assumption of asymmetric relationship between a truster and a trustee; and it has not dealt with situations in which a rich person encounters a poor person. We build a game theoretic model of mutual trust to solve these problems. Then we analyze an equilibrium of the model and derive some implications from it. That is, the ratio between the transaction costs and the opportunity costs affects actor' trustfulness; a more trustworthy actors finds it easier to leave his/her group in search of higher returns; and a rich actor is more willing to trust his/her counterpart than a poor actor.     

A Model of Vacancy Chains as a Mechanism for Resource Allocation

Vacancy chains can be tracked in any context where the availability of a desirable resource triggers a cascade of occupations through which the scarce resource flows through different owners. However, under certain conditions, vacancy chains, rather than markets or other forms of competition, determine the allocation of the resource. This article develops a formal and computational model of vacancy chains as a mechanism for resource allocation in order to find out their properties with respect to organizational forms.

We find that hierarchies with few middle managers are particularly prone to make use of vacancy chains in order to allocate resources that originate at the top, such as employment positions. In fact, vacancy chains often disappear when information is widely available, because information is likely to attract applicants who engage in a competition. Thus, the many middle managers of a thick organization may compete for a resource that originates at the top. On the contrary, organizations that are thick at the bottom and at the top, but thin in the middle, are most likely to regulate resource allocation by means of vacancy chains.     

The Emergence of Social Order by Processes of Typifying: A Computational Model

The article argues that Rational Choice approaches are not sufficient to explain the “how” of the emergence of social order. Therefore, the concept of “typifying” according to the theory of Berger and Luckmann is understood as the most important form of establishing social orders between different social actors. A computational model is described that captures the basic features of the typifying process. Each artifical actor consists of two different neural nets, an “action net” and a “perception net”. These nets allow an actor to establish social rules of interaction with other actors, to remember the other actors after a time and to typify new actors as persons that belong to the same type as actors the first actor is already “acquainted” with. Experimental results and theoretical consequences are also given.     

A silent nversus 1 bullet duel with retreat after the shots

This paper is concerned with silent duel in which the first player has nbullets and the second one-one bullet. The accuracy functions are the same. It is assumed that each player removes to the back after firing all his bullets. The situation when players have different speeds are considered as well as that in which the speeds are the same. In both situations the optimal strategies are determined and the value of the game is found.     

Centralized resource allocation DEA models based on revenue efficiency under limited information

In this paper, we extend the centralized DEA models by Lozano et al (2011) to allocate resources based on revenue efficiency across a set of DMUs under a centralized decision-making environment. The aim is to allocate resources so as to maximize the total output revenue produced by all the DMUs under limited information. To uncover the sources of total revenue increase from the centralized resource allocation model, we further decompose the aggregate revenue efficiency into three components: the aggregate output-oriented technical efficiency, the aggregate output allocative efficiency and the aggregate revenue re-allocative efficiency. Finally, two empirical data sets are presented to show that our proposed approach is not only an efficient tool to allocate the resources among the DMUs based on the revenue efficiency but additionally provides the central DM with guidance on how to identify the weak areas where more effort should be devoted to improve the total outputs.     

Universal Strict General Actors and Actors in Categories of Interest

For any category of interest ℂ we define a general category of groups with operations \mathbbC_G, \mathbbC\hookrightarrow\mathbbC_G\mathbb{C_G}, \mathbb{C}\hookrightarrow\mathbb{C_G}, and a universal strict general actor USGA(A) of an object A in ℂ, which is an object of \mathbbC_G\mathbb{C_G}. The notion of actor is equivalent to the one of split extension classifier defined for an object in more general settings of semi-abelian categories. It is proved that there exists an actor of A in ℂ if and only if the semidirect product \textUSGA(A)\ltimes A{\text{USGA}}(A)\ltimes A is an object of ℂ and if it is the case, then USGA(A) is an actor of A. We give a construction of a universal strict general actor for any A ∈ ℂ, which helps to detect more properties of this object. The cases of groups, Lie, Leibniz, associative, commutative associative, alternative algebras, crossed and precrossed modules are considered. The examples of algebras are given, for which always exist actors.     

Algebraic Connectivity of Connected Graphs with Fixed Number of Pendant Vertices

In this paper, we consider the following problem. Over the class of all simple connected graphs of order n with k pendant vertices (n, k being fixed), which graph maximizes (respectively, minimizes) the algebraic connectivity? We also discuss the algebraic connectivity of unicyclic graphs.     

基于非对称成本的设计竞赛博弈模型及奖金设置

论从项目业主的角度出发，利用博弈论和信息经济学理论和方法，在竞赛参与人成本不对称条件下，建立了一个项目业主和多个设计竞赛参与人组成的设计竞赛博弈模型；并在竞赛参与人成本函数分别为线性函数、凹函数和凸函数的条件下，研究对项目业主最优的竞赛奖金设置，研究表明：对于项目业主最优的奖金设置是单项奖金的方式。     

An Optimum Multivariate Stratified Sampling Design with Nonresponse: A Lexicographic Goal Programming Approach

In a multivariate stratified sample survey with L strata and p > 1 characteristics, defined on each unit of the population, let the estimation of all the p-population means be of interest. As discussed by Cochran (1977), since the optimum allocation for one characteristic will not in general be optimum for other characteristics some compromise must be reached in a multiple characteristics stratified surveys. Various authors worked out allocations that are based on a compromise criterion. The resulting allocations are optimal for all characteristics in some sense, for example an allocation that minimizes the trace of the variance-covariance matrix of the estimators of the population means or an allocation that minimizes the weighted average of the variances or an allocation that maximizes the total relative efficiency of the estimators as compared to the corresponding individual optimum allocations. In the present paper the problem of optimum allocation in multivariate stratified random sampling in the presence of nonresponse has been formulated as a multiobjective integer nonlinear programming problem and a solution procedure is developed using goal programming technique. Three numerical examples are worked out to illustrate the computational details. A comparison of the proposed method with some well known methods is also carried out to show the practical utility of the proposed method.     

Multi-level resource allocation for HIV prevention: A model for developing countries

Funds spent on HIV prevention commonly traverse several levels of distribution. For example, funds may be allocated to regions, and regional authorities may then allocate their funds to sub-regions or targeted risk groups. Decision makers at each level often make use of heuristics that may result in suboptimal allocation of resources. We examine the impact of equity-based heuristic allocation of HIV prevention funds versus optimal allocation of HIV prevention funds when there are two levels of decision making. Our results demonstrate that if optimization can only be applied to one level of the decision making process, there are more significant gains if it is applied at the lower level than at the upper level.     

An optimal control model of oil discovery and extraction

Starting with Hotelling (1931) [7] the stock of non-renewable resources have been treated as fixed. Along the line of Pindyck (1978) [8] and Greiner and Semmler (in press) [5] we treat the stock of oil resources as time varying, depending on new discoveries. The resource is finite and only a part of the resource is known while the rest has not yet been discovered. The discovery leads to a rise of known oil resource which can then be optimally exploited. The optimal control model has two state variables, the known stock of the resource and the cumulated past extraction. The control variable is the optimal extraction rate. The optimal control model assumes a monopolistic resource owner who maximizes intertemporal profits from exploiting the resource where the price of the resource depends on the extraction rate, the known stock of the resource, and the cumulated past extraction. The model is solved for a finite time horizon using NUDOCCCS, a numerical solution method to solve finite horizon optimal control problems. Various parameter constellations are explored. For certain parameter constellations the price path becomes U-Shaped as some empirical research, see Greiner and Semmler (in press) [5], have found to hold for actual price data. This holds if the stock of the initially known resource is small.     

S-modular games,with queueing applications

The notion ofS-modularity was developed by Glasserman and Yao [9] in the context of optimal control of queueing networks.S-modularity allows the objective function to be supermodular in some variables and submodular in others. It models both compatible and conflicting incentives, and hence conveniently accommodates a wide variety of applications. In this paper, we introduceS-modularity into the context ofn-player noncooperative games. This generalizes the well-known supermodular games of Topkis [22], where each player maximizes a supermodular payoff function (or equivalently, minimizes a submodular payoff function). We illustrate the theory through a variety of applications in queueing systems.Supported in part by NSF Grant MSS-92-16490, and by Columbia's Center for Telecommunications Research.