Data-driven analysis has been increasingly used in various decision making processes. With more sources, including reviews, news, and pictures, can now be used for data analysis, the authenticity of data sources is in doubt. While previous literature attempted to detect fake data piece by piece, in the current work, we try to capture the fake data sender's strategic behavior to detect the fake data source. Specifically, we model the tension between a data receiver who makes data-driven decisions and a fake data sender who benefits from misleading the receiver. We propose a potentially infinite horizon continuous time game-theoretic model with asymmetric information to capture the fact that the receiver does not initially know the existence of fake data and learns about it during the course of the game. We use point processes to model the data traffic, where each piece of data can occur at any discrete moment in a continuous time flow. We fully solve the model and employ numerical examples to illustrate the players' strategies and payoffs for insights. Specifically, our results show that maintaining some suspicion about the data sources and understanding that the sender can be strategic are very helpful to the data receiver. In addition, based on our model, we propose a methodology of detecting fake data that is complementary to the previous studies on this topic, which suggested various approaches on analyzing the data piece by piece. We show that after analyzing each piece of data, understanding a source by looking at the its whole history of pushing data can be helpful.

In this article, we propose a new measure of firms' dyadic business proximity. Specifically, we analyze the unstructured texts that describe firms' businesses using the natural language processing technique of topic modeling, and develop a novel business proximity measure based on the output. When compared with the existent methods, our approach provides finer granularity on quantifying firms' similarity in the spaces of product, market, and technology. We then show our measure's effectiveness through an empirical analysis using a unique dataset of recent mergers and acquisitions in the U.S. high technology industry. Building upon the literature, our model relates the likelihood of matching of two firms in a merger or acquisition transaction to their business proximity and other characteristics. We particularly employ a class of statistical network analysis methods called exponential random graph models to accommodate the relational nature of the data.

Cooperative technological solutions for Distributed Denial-of-Service (DDoS) attacks are already available, yet organizations in the best position to implement them lack incentive to do so, and the victims of DDoS attacks cannot find effective methods to motivate them. In this article we discuss two components of the technological solutions to DDoS attacks: cooperative filtering and cooperative traffic smoothing by caching. We then analyze the broken incentive chain in each of these technological solutions. As a remedy, we propose usage-based pricing and Capacity Provision Networks, which enable victims to disseminate enough incentive along attack paths to stimulate cooperation against DDoS attacks.

Abstract A majority of critical decisions requires collaborative efforts among analysts to build situation awareness. Teams of decision makers frequently have to react to incoming facts and developing events in a timely fashion such that the consequences of the decisions made largely have a positive impact on a developing situation. This problem is further exacerbated due to the multitude of agencies involved in the decision‐making process. Thus, the decision‐making processes faced by the intelligence agencies are characterized by group deliberations that are highly ill structured and yield limited analytical tractability. In this context, a collaborative approach to providing cognitive support to decision makers using a connectionist modeling approach is proposed. The connectionist modeling of such decision scenarios offers several unique and significant advantages in developing systems to support collaborative discussions. Several inference rules for augmenting the argument network and to capture implicit notions in arguments are proposed. We further explore the effects of incorporating notions of information source reliability within arguments and the effects thereof.

This research evaluates and analyzes existing mechanisms of online reputation systems based on cooperative feedbacks of past transaction information. We find existing popular feedback systems do not provide sustained incentives for sellers to behave honestly over time. We propose a new design of reputation system based on exponential smoothing. This mechanism is shown to be more robust compared to the existing systems. We relax the assumption of a static product value and have implemented a two-level exponential smoothing policy to process and aggregate reputation information. The simulation results show that the policy can serve as a sustained incentive mechanism for the seller.

Simulation graph models provide a powerful and general modeling framework for discrete-event simulation. Within this framework it has been shown that an eventcancellation construct is a modeling convenience rather than a necessary modeling tool. As a result, very little work on the formal development of simulation graph models directly considers an event-canceling construct. However, to the simulation practitioner, the modeling convenience and functionality provided by a canceling construct is important. This is clearly demonstrated by the presence of some sort of event-canceling construct in all the major simulation software packages. This paper extends the simulation graph modeling framework to include a general approach to handling event cancellation. The extension is provided in algorithmic form. We demonstrate how the algorithm can be implemented in event graphs (and the corresponding commercial software SIGMA) and in the commercial software SIMAN.

One of the major investments of information technologies in large companies in the past decade has been the enterprise system. Although the enterprise system has the advantages of managing and integrating almost all of the business processes in the whole company, there have been strong criticisms that the enterprise system often imposes its own logic or business process on a company and lacks flexibility and adaptability in today's dynamic business environment. The goal of this paper is to outline a new approach in enterprise system development. We analyse the factors that affect the adoption of enterprise systems. Market and business changes, and advances in information technologies call for a more flexible, open, and scalable enterprise architecture. We describe the process that Dell Computer Corporation took in adopting its component-based enterprise system architecture. The Dell example has demonstrated the importance of fit between business information systems and fundamental organizational dimensions of the company including strategy, business environment, and organizational structure. We also discuss the design methodologies for component-based enterprise system design. We take a coordination perspective, both at the software level and the organizational level, in addressing the design methodologies for component-based enterprise system development.

The information technology (IT) infrastructure of today's organization is often one of distributed networked computing, with a flexible architecture to incorporate diverse software and hardware components to meet the needs of different user groups. One problem that may be encountered in this environment is the lack of information exchange across user groups or teams because of incompatible data definitions, diversity of formats, and differences in information processing capabilities and IT resource allocation across the organization. Successful information flows involve a user group providing information attribute levels (e.g., levels of precision or detail, timeliness, etc.), data definitions, formats and presentation styles required by the recipient group(s). When information exchange occurs without a fit between the attribute required and that provided, we have the problem of "information coordination." It is thus critical to design and implement a set of organizational mechanisms which will encourage units within an organization to share relevant information in a coordinated manner. We develop a stylized model of coordination based information exchange between two decision units, and show that structured communication regarding the units' intended information sharing choices can partly mitigate the problem of coordination. When there is uniformity in information management capability and IT resources across the organization, the positive impact of such communication is reinforced, These results imply an emerging role of MIS, where the latter functions as a coordinator of communication and understanding between interdependent derision units, and a facilitator of equity in information processing capability across the units.

Quantitative research and statistical techniques have long been regarded as superior ways of analyzing knowledge in social sciences. To deal with incomplete or imprecise knowledge while modeling systems, traditional approaches in social sciences (i.e., management science, operations research) have attempted to measure social facts by making approximations of the problem under analysis. Artificial intelligence (AI) research on qualitative reasoning which focuses on using qualitative knowledge to reason about the everyday physical world, suggests an opportunity to extend the capability of current logico-mathematical instruments used by social scientists. This paper proposes an interval propagation difference equation method, a type of qualitative-quantitative simulation method, to model dynamic systems by abstracting from the underlying true model. The proposed difference equation method can be used to model problems requiring discrete-time analysis, such as applications involving time-lag relationships. Moreover, the method does not require the exact functional form of the problem under analysis to be known with certainty. The incomplete or imprecise knowledge available about the functional form of the true model, and the values of its variables, are represented with bounding functions and interval values respectively.>

Explores a multi-agent resource allocation problem in an environment of incomplete information. The paper posits the existence of a central policy maker who integrates information acquisition with decision making, in order to optimally allocate resources among multiple agents. The study focuses on three salient aspects: first, the policy maker uses a nonparametric revealed preference approach for the elicitation of each agent's preference profiles. This allows the policy maker to avoid distorting the allocation decision and emerging with suboptimal allocations. Second, the process of information gathering and decision making is a challenging task in view of the extremely large numbers of possible profiles for each agent, even for problems of modest size. To find an optimal allocation, the policy maker can use schemes that utilize partial preference information to handle the complexity of the problem. Third, the incorporation of costs into the information process and the minimal assumptions made about the problem environment allow the policy maker to realistically analyze the resource allocation problem.>

Petri net models for the Horn clause form of propositional logic and of first-order predicate logic are studied. A net model for logical inconsistency check is proposed. Algorithms for computing T-invariants of Petri net models of logical inference systems are investigated. The algorithms are based on the idea of resolution and exploit the presence of one-literal, pure-literal, and splitting clauses to lead to faster computation. Algorithms for computing T-invariants of high-level Petri net (HLPN) models of predicate logic are presented.>

Classical techniques used in project planning and control generally lack the required functionality to manage large-scale projects characterized by a dynamic environment and uncertain and incomplete information. In order to overcome some of these problems, a distributed knowledge-based approach is proposed for planning and controlling large projects. It is shown how a model of truth maintenance can be effectively combined with existing planning and scheduling tools to allow for incomplete plans and for effective updating and control as more knowledge becomes available. The authors' model is particularly well suited for supporting the extensive collaborative process among project participants that characterizes a large project.>

The purpose of this study was to investigate and compare the Management Information Systems (MIS) curricula in higher education in the United States (U.S.) and the Republic of China (R. O.C.).Several factors that affect the MIS curricula and its development in these two countries were closely examined.Similarities and differences were identified and compared; strengths and weaknesses were analyzed and described.In particular, this study focused on the undergraduate MIS programs in both countries.Comparisons of the MIS programs were made concerning: MIS program history, MIS program setting, admission requirements and standards, graduation requirements and standards, computer hardware and software facilities, curriculum model adopted, required courses, instructional methods, faculty profiles, student profiles, and relationships with the industry.Based on the findings, some recommendations for improving the Chinese MIS curricula were offered.

We present the file search problem in a decision-theoretic framework, and discuss a variation of it that we call the common index problem. The goal of the common index problem is to return the best available record in the file, where best is in terms of a class of user preferences. We use dynamic programming to construct an optimal algorithm using two different optimality criteria, and we develop sufficient conditions for obtaining complete information.

Planning in flexible manufacturing systems must take into account both the multiprocessing environment and the dynamically changing states. This paper uses a knowledge-based approach to handle such a planning system, where three levels-i.e., the control, state, and operational levels-constitute its manufacturing knowledge. The construction of plans for multiple manufacturing jobs requires four steps: (1) linear plan generation, (2) conflict detection, (3) plan synthesis, and (4) plan revision. To achieve goals, these steps will search for planning operators using a backward chaining inference procedure. To perform the scheduling and sequencing of the multiple jobs within a flexible manufacturing cell, the planning system modifies the nonlinear planning approach and adds resources and durations information to the action formalism. Because the plan-generation process is goal-directed, the dynamically adjustable plan can be constructed on-line.

An April 1984 workshop on research directions was sponsored by the Decision and Management Science Program of the National Science Foundation at the University of Texas at Dallas. One session concerned the relationship of research to phenomena in decisionmaking and operations. Nine presentations from workers in very diverse areas comprised the session. Together, they provide a very useful compendium of commonalities and differences in this important area of contemporary thought that offers much insight into future research directions. What follows was initially prepared by the nine presenters at the session, edited by the editor of this Transactions, distributed to all session presenters for their thorough review and commentary, and then revised for publication by the editor. It is our hope that this provides the research community at large with the results of a very useful dialog.

Internal control is an important aspect of accounting office systems.The implementation and maintenance of a control structure which protects corporate assets from theft, misuse, and fraud and permits the preparation of accurate and reliable financial reports is a result of both good business practice and legal requirements.This article presents a precedence model for specifying accounting office systems.Formal analysis procedures are formulated for evaluating the internal controls of the modeled system.The procedures establish precondition and postcondition relationships between designated control points.

Decisionmaking under uncertainty (DMUU) has been analyzed in a variety of ways in the literature. The uncertainty considered here Involves matters of life and death. It is postulated that individuals can affect the probability and nature of certain outcomes, including their own survival probabilities, by taking appropriate actions. The interaction of individualistic decisionmaking in the face of uncertainty about the state of nature is analyzed using a two-period model. The results are generalized to include investment opportunities and the model is extended to group decisomaking and Interrelated preferences.

This paper describes the design of a language intended for use in a data base environment. The language is of interest for several reasons. It is used as a vehicle to introduce the concept of transformation grammar as a basis for describing a high level programming language. We will show that a transformational grammar may define a natural English-like language while providing an efficient method for language recognition. Another important aspect of the language is its data view, in that data files are the processing unit, rather than in dividual records. Finally, the language is well suited to the programming orientation of viewing a program in terms of data mappings, allowing a more structured approach to programming. The examples presented in this paper are framed in terms of logical data structures. Because of the modular nature of the language processor, any physical data organization and data base implementation can be supported. In particular, both CODASYL-type and relational data bases C 1,23 can be handled via the appropriate transformations. This paper has two basic goals. One is to describe the language in both theoretical and practical terms. This is done primarily through the use of examples. The second goal is the introduction of the linguistic techniques used to define the language. These include transformational grammars. The purpose is not to be tutorial, but to indicate the nature of the technique.

This paper investigates some of the problems encountered in the management of a data base that is logically distributed. The term logical distribution is used to connote a situation wherein users in various locales are responsible for creation and maintenance of their own portions of a data base, but a user in one locale can access data maintained by a user in another locale. An example of this situation is drawn from the realm of water quality management. A generalised mapping language is proposed as a mechanism for information transferral within a distributed data base, and a general data structure for supporting the mapping function is illustrated. The presented method accommodates a variety of user views, is independent of whether the data base is geographically distributed or centralised, furnishes a straightforward security mechanism and provides a basis for treating the contingency of uninformed or non-programming users.

As the availabilities of data base management systems become greater the need to interface already existing programs with the data base will become important. This paper presents a technique whereby these programs can be interfaced automatically with the data base through the use of a query/extraction interface, thus providing the capability to retrieve, modify and use data in various application programs without knowing the physical data structure and without using the data manipulation language.

Providing computer facilities and data availability to larger numbers of users generates increased system vulnerability which is partially offset by software security systems. Much too often these systems are presented as ad hoc additions to the basic data management system. One very important constituent of software security systems is the access control mechanism which may be the last resource available to prohibit unauthorized data retrieval. This paper presents a specification for an access control mechanism. The mechanism is specified in a context for use with the GPLAN decision support system by a theoretical description consistent with the formal definition of GPLAN's query language. Incorporation of the mechanism into the language guarantees it will not be an ad hoc addition. Furthermore, it provides a facile introduction of data security dictates into the language processor.