Privacy and pricing personal information

The issues we address here are – How should a firm (e.g. Internet service provider (ISP)) that is capable of collecting personal information (browsing information, purchase history, etc.) about consumers, price its service, given that consumers vary in their valuation for privacy, and also vary in terms of the value of their personal information to a third party (firms that need consumer information)? Should the firm have a blanket policy of never collecting, or a policy of always collecting and revealing information? Surprisingly we find that in some cases the collector of information may be no worse off in the asymmetric information case than in the full information case. The paper provides a justification for the strategy of some firms such as ISP’s which never collect information and also for the strategy of other firms, like grocery stores that do. We also find that it is non-optimal for the firm to design contracts where the consumer can choose an intermediate level of privacy.     

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.     

Information amount and higher-order efficiency in estimation

By means of second-order asymptotic approximation, the paper clarifies the relationship between the Fisher information of first-order asymptotically efficient estimators and their decision-theoretic performance. It shows that if the estimators are modified so that they have the same asymptotic bias, the information amount can be connected with the risk based on convex loss functions in such a way that the greater information loss of an estimator implies its greater risk. The information loss of the maximum likelihood estimator is shown to be minimal in a general set-up. A multinomial model is used for illustration.     

考虑相互信息监督下的服务合作生产契约

知识密集型服务合作生产由于存在相互之间的知识依赖和信息粘性,双方信息管理效率影响合作激励机制的设计。从相互信息监督视角出发,综合考虑双方信息监督效率和相对重要性参数对服务合作生产契约设计的影响。结果表明,在双方信息监督效率相同情况下,相对更重要的一方拥有剩余激励是最优的;在双方信息监督效率不同时,让监督更有效且相对更重要的一方拥有剩余激励是最优的;如果监督效率优势和相对重要性优势没有集中于一方,则结果取决于两者的比较,具有更强优势的一方应该成为剩余激励索取者。双方的相对重要性和信息监督效率共同决定合作契约。     

A method based on PSO and granular computing of linguistic information to solve group decision making problems defined in heterogeneous contexts

Group decision making is a type of decision problem in which multiple experts acting collectively, analyze problems, evaluate alternatives, and select a solution from a collection of alternatives. As the natural language is the standard representation of those concepts that humans use for communication, it seems natural that they use words (linguistic terms) instead of numerical values to provide their opinions. However, while linguistic information is readily available, it is not operational and thus it has to be made usable though expressing it in terms of information granules. To do so, Granular Computing, which has emerged as a unified and coherent framework of designing, processing, and interpretation of information granules, can be used. The aim of this paper is to present an information granulation of the linguistic information used in group decision making problems defined in heterogeneous contexts, i.e., where the experts have associated importance degrees reflecting their ability to handle the problem. The granulation of the linguistic terms is formulated as an optimization problem, solved by using the particle swarm optimization, in which a performance index is maximized by a suitable mapping of the linguistic terms on information granules formalized as sets. This performance index is expressed as a weighted aggregation of the individual consistency achieved by each expert.     

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.     

Relative Efficiency Assessments Using Data Envelopment Analysis: An Application to Data on Rates Departments

This paper examines the nature of information obtained from data envelopment analysis (DEA) in comparative studies of the efficiency of decision-making units, and it discusses the interpretation and practical usefulness of such information. The themes developed in the paper are illustrated by an application of DEA to data on the rate-collection function of London Boroughs and Metropolitan District Councils. The paper begins with an overview of DEA, followed by a discussion of some of the practical considerations arising in the application of DEA. It then describes the structuring of the rate-collection function for assessment by DEA, and explores the extent to which units can be classified as relatively efficient or inefficient. In respect of relatively inefficient units, it illustrates the construction of target inputs and outputs so that their relative efficiency may improve. In respect of relatively efficient units, it is argued that their identification is weak in the sense that for some of them their apparent efficiency may be simply a reflection of an uncommon input-output profile. It is shown, nevertheless, that information about relatively efficient units can be used to identify those of them which may prove examples of good operating practice in given aspects of their function. (Readers not familiar with British taxes may wish to note that rates are a tax on property, levied by local authorities.)     

On consistency of information models

During the last years a number of approaches to information modeling have been presented. An information model is then assumed to be expressed in some formalism based on a set of basic concepts and construction rules. Some approaches also include inference rules, but few include consistency criteria for information models. Two different approaches to information modeling have been analyzed within the framework of first-order predicate logic. In particular, their consistency criteria are compared with that of predicate logic. The approaches are completely expressible in predicate logic and the consistency criteria have a logical counterpart only when a set of implicit assumptions is stated explicitly.This work is supported by the National Swedish Board for Technical Development.     

Information management for concurrent engineering

The main objective of Concurrent Engineering is the reduction of development lead time. This shorter time-to-market is achieved by paralleling development and production activities. With the deliberate use of incomplete and uncertain information an enormous reduction of development lead time can be achieved in comparison to parallel activities which are only based on exact information. Thus many activities can be started even if their predecessors are not completed. This article focuses mainly on two concepts to provide an adequate information management for Concurrent Engineering. The first concept is based on a systematic integration of uncertainty into the information flow. The second concept allows to restructure the sequential and document-oriented information flow by creating small information units. The application of both concepts supports an early information flow. Thus it becomes possible to coordinate activities more efficiently because critical topics can be recognized and balanced in advance, shifting the communication requirement to the early stages of the development process. Hence, expensive iterations, especially in the late stages of the product development process, can be avoided and the length of iteration loops can be reduced.     

PROMETHEE-MD-2T method for project selection

Project selection is a real problem of multicriteria group decision making (MCGDM) where each decision maker expresses his/her preferences depending on the nature of the alternatives and on his/her own knowledge over them. Thus, information, as much quantitative as qualitative, coexists. The traditional methods of MCGDM developed for project selection usually discriminates in favour of quantitative information at the expense of qualitative information, and this is due to the capability to integrate this first type of information inside their procedure. In this article, two new multicriteria 2-tuple group decision methods called “Preference Ranking Organisation Method for Enrichment Evaluation Multi Decision maker 2-Tuple-I and II” (PROMETHEE-MD-2T-I and II) are presented. They are able to integrate inside their procedure both quantitative and qualitative information in an uncertain context. This has been performed by integrating a 2-tuple linguistic representation model dealing with non-homogeneous and imprecise information data made up by valued intervals, numerical and linguistic values into the aggregation operators of Promethee methods. Although they have been developed for project selection problems, these proposed methods can be applied to all kinds of decision-making problems with heterogeneous and multigranular information.     

The role of operating premises and reasoning paths in upper elementary students’ problem solving

The validity of students’ reasoning is central to problem solving. However, equally important are the operating premises from which students’ reason about problems. These premises are based on students’ interpretations of the problem information. This paper describes various premises that 11- and 12-year-old students derived from the information in a particular problem, and the way in which these premises formed part of their reasoning during a lesson. The teacher’s identification of differences in students’ premises for reasoning in this problem shifted the emphasis in a class discussion from the reconciliation of the various problem solutions and a focus on a sole correct reasoning path, to the identification of the students’ premises and the appropriateness of their various reasoning paths. Problem information that can be interpreted ambiguously creates rich mathematical opportunities because students are required to articulate their assumptions, and, thereby identify the origin of their reasoning, and to evaluate the assumptions and reasoning of their peers.     

Some results on zero-sum games with incomplete information: The dependent case

In games with incomplete information, the players' states of information may be determined either through independent chance moves or through a unique one. Generally, a unique chance move generates some dependance in the players' state of information thus giving rise to significant complications in the analysis. However, it turns out that many results obtained in the simpler independent case have their counterpart in the dependent one. This is proved in this paper for several previous results of the authors.     

Information acquisition and disclosure by firms in the presence of additional available information

In this paper we analyze a model which addresses two stylized facts which have received little attention in disclosure theory. (a) Information that is acquired for internal decision-making can subsequently be disclosed to outside investors who can use it to update their assessment of the firm’s prospects. Thus, the decision to gather information in the first place does not only depend on the decision value of information. (b) Information disclosed by firms is only one element of the information environment upon which investors can draw. This setting creates an interaction between firms’ information gathering and disclosure decisions as well as alternative sources of information. We identify an equilibrium structure which we call a Countersignaling equilibrium in which only average firms acquire information whereas good and bad firms do not. We show that while several equilibria can coexist, a Countersignaling equilibrium is often the economically most efficient one.     

Factor analysis and classification methods: An application to the study of corporate custom

Banks have numerous data available for the management of their corporate customers. But they often only use a small part of it (financial data) and frequently disregard qualitative or subjective information accessible at their branches (capacity to export, flexibility with regard to credit squeeze,…). However, some methods for quantifying and homogenizing the various sources of information can be used in order to best exploit them. After having thus developed a complete profile of each client, factor analysis enables us to extract the most significant variables and achieve a meaningful synthesis. In this way, we get a limited selection of criteria which can be easily updated. A subsequent use of factor analysis and classification methods for the selected variables brings out typologies and gives prominence to customer evolution. Such a methodology is useful in the decision making process and enables us to build up a consistent policy for the management of the whole range of customers.     

Optimal investment and reinsurance policies in insurance markets under the effect of inside information

In this paper, we study the problem of optimal investment and proportional reinsurance coverage in the presence of inside information. To be more precise, we consider two firms: an insurer and a reinsurer who are both allowed to invest their surplus in a Black–Scholes‐type financial market. The insurer faces a claims process that is modeled by a Brownian motion with drift and has the possibility to reduce the risk involved with this process by purchasing proportional reinsurance coverage. Moreover, the insurer has some extra information at her disposal concerning the future realizations of her claims process, available from the beginning of the trading interval and hidden from the reinsurer, thus introducing in this way inside information aspects to our model. The optimal investment and proportional reinsurance decision for both firms is determined by the solution of suitable expected utility maximization problems, taking into account explicitly their different information sets. The solution of these problems also determines the reinsurance premia via a partial equilibrium approach. Copyright © 2011 John Wiley & Sons, Ltd.     

Application of modified information criterion to multiple change point problems

The modified information criterion (MIC) is applied to detect multiple change points in a sequence of independent random variables. We find that the method is consistent in selecting the correct model, and the resulting test statistic has a simple limiting distribution. We show that the estimators for locations of change points achieve the best convergence rate, and their limiting distribution can be expressed as a function of a random walk. A simulation is conducted to demonstrate the usefulness of this method by comparing the powers between the MIC and the Schwarz information criterion.     

Parallel decomposition of multistage stochastic programming problems

A new decomposition method for multistage stochastic linear programming problems is proposed. A multistage stochastic problem is represented in a tree-like form and with each node of the decision tree a certain linear or quadratic subproblem is associated. The subproblems generate proposals for their successors and some backward information for their predecessors. The subproblems can be solved in parallel and exchange information in an asynchronous way through special buffers. After a finite time the method either finds an optimal solution to the problem or discovers its inconsistency. An analytical illustrative example shows that parallelization can speed up computation over every sequential method. Computational experiments indicate that for large problems we can obtain substantial gains in efficiency with moderate numbers of processors.This work was partly supported by the International Institute for Applied Systems Analysis, Laxenburg, Austria.     

Sampling on successive occasions to re-estimate future asset management expenditure

Sampling schemes are used by the utilities such as electricity and water to assess the condition of their networks, and hence to predict future expenditure. Frequently the assessment process has to be carried out on a regular basis, e.g. every 5 years. However there is little published literature to provide guidance as to how much resampling to undertake, how to use the extra information gained and how accurate the results are likely to be. Therefore this paper describes simple linear and quadratic regression models for predicting future condition and investigates their performance. As this investigation requires all items to have a full condition history, a deterioration model is developed to generate this information.     

A system to support the enhancement of strategic flexibility in manufacturing enterprises

Manufacturing companies are finding it necessary to change their corporate strategy with increasing frequency, as a result of more rapid changes either in the demands made by customers or in the company's view of business. However, it is only possible to respond to these pressures for change if the information systems of the organisation are capable of helping the companies meet these new requirements. The aim of the work described here is to develop a decision support system (DSS) that will help companies to enhance their strategic flexibility, that is to increase the ability of their systems to support a broader range of corporate strategies. The development of this system is discussed. Particular attention is paid to describing the structure of the DSS and the manner in which the extensive fieldwork carried out with UK manufacturing businesses has provided information about the appropriate factors and parameters to be included in the system. Possible further development of the DSS is briefly considered.     

Sources of Information for Operational Research Studies

The information explosion and the wide-ranging interests of operational research workers cause severe problems in the finding of information relevant to their studies. This paper attempts to show how an operational research worker can set about finding information for himself on any aspect of his work and a hundred examples of sources of information likely to be useful are briefly described with special reference to the needs of British workers.