Three pseudo-paradoxes in ‘quantum’ decision theory: Apparent effects of observation on probability and utility

In quantum domains, the measurement (or observation) of one of a pair of complementary variables introduces an unavoidable uncertainty in the value of that variable's complement. Such uncertainties are negligible in Newtonian worlds, where observations can be made without appreciably disturbing the observed system. Hence, one would not expect that an observation of a non-quantum probabilistic outcome could affect a probability distribution over subsequently possible states, in a way that would conflict with classical probability calculations. This paper examines three problems in which observations appear to affect the probabilities and expected utilities of subsequent outcomes, in ways which may appear paradoxical. Deeper analysis of these problems reveals that the anomalies arise, not from paradox, but rather from faulty inferences drawn from the observations themselves. Thus the notion of quantum decision theory is disparaged.     

Differences in white-nonwhite community mental health center service utilization patterns

Routinely collected computerized data were used to study the process of service delivery in terms of admission patterns, type and quantity of services rendered, and status at termination for whites and nonwhites in two community mental health centers. Social area analysis techniques were employed to control for socio-economic status, ethnicity and life style variables, and an epidemiologic model was used to analyze admission and service delivery rate differences. It was found that nonwhite admission rates were at least twice as great as white rates. Service delivery rates to the population at large were considerably greater for nonwhites than for whites. Delivery of direct services within the centers differed for whites and nonwhites, but no consistent trends emerged when types and amounts of services rendered were analyzed, controlling for sex, ethnicity, age, diagnosis and social area. Disruption of care indices were greater for nonwhites than for whites. Highlighted were some of the complexities involved in interpreting results of utilization studies.     

Information and communications technologies, strategic asymmetry and national security

In the history of warfare, there are a number of examples of strategic uses of asymmetric technologies. Consistent with history and theory, individuals, organizations and nations have spotted opportunities to employ information and communications technologies to gain and exploit asymmetric advantages and to counter asymmetric weaknesses. This article discusses various asymmetries associated with institutions, nations and organizations that influence the ICT-national security nexus. Regulative, normative and cognitive institutions in a country provide various mechanisms that affect the nature of positive and negative asymmetries. Nations and organizations also differ in terms of their capability to assimilate ICT tools to gain positive asymmetries and deal with vulnerabilities of negative asymmetries. Integrative approaches that combine policy and technological measures at various levels are likely to make the world more secure.     

网络时代的适时财务监控与公司治理

网络技术应用的普及使传统财务监控的变革已成为公司治理和财务管理的热点话题,本文简要揭示新概念——适时财务监控与公司治理的关系,剖析了公司不同管理层次的适时财务监控的实时需求,从公司治理的基本需要对公司价值流再造、公司信息系统变革和适时财务监控机制重构等三个方面进行了初步研究,为网络适时财务监控在公司治理实务中的应用提供了一个基本框架。     

纵向沟通中隐性信息获取的激励兼容机制研究

下属隐性信息的获取是确保上级决策者有效决策的一个重要基础,现有的研究未能解决隐性信息获取的效率与预算平衡的两难问题。本文通过确认决策者的作用,在分析模型中引入决策者成本,并借鉴政府征收“所得税”的思路,不仅解决了隐性信息获取的真实性,而且解决了原有方案未能同时兼顾的预算平衡、利润最大化以及向下属转移损失等问题。     

Persuasion: An experimental study of team decision making

This paper studies persuasion within teams and investigates why teams commonly take, by some measures, better decisions than individuals. The analysis is based on data from electronic communication within teams of two players. Thanks to the experimental design, changes of an individual’s decision can be attributed to the content of the team partner’s message. The results for knowledge-related and strategic problems show that individuals’ decisions change upon receiving more informative and sophisticated arguments and remain the same otherwise. This individual behavior is an essential part of the information aggregation in teams and can explain the advantage of teams in decision making and in games.     

Some Results Based on a Version of the Generalized Dynamic Entropies

We propose new dynamic measures of uncertainty based on the notion of generalized dynamic entropy introduced in Di Crescenzo and Longobardi (2006). These can uniquely determine distribution functions in continuous and discrete cases, and the characterizations of some well-known distributions are provided. We also define some orderings and aging notions based on the generalized dynamic measures, and prove some of their properties, obtaining as corollaries results that have recently appeared in the literature.     

Beyond mere information transfer: The importance of a relational approach to market-related internal communication

Despite the significance of relationship management in any information provision or exchange, public relations scholarship has typically focused on examining the underlying internal communication processes from a transactional perspective. These processes are frequently associated with organizational information dissemination, overlooking other critical contents to make strategic decisions. This study draws market information processing into the debate about internal communication, providing a greater understanding of how a relational approach can improve market intelligence dissemination. Results show that an effective management of market knowledge requires the use of such an approach, which in turn, cultivates the shared interpretation of market information and innovation performance. The findings stimulate fresh discussion about the nature and development of internal communication knowledge and practice.     

Generalized information matrix tests for copulas

We propose a family of goodness-of-fit tests for copulas. The tests use generalizations of the information matrix (IM) equality of White and so relate to the copula test proposed by Huang and Prokhorov. The idea is that eigenspectrum-based statements of the IM equality reduce the degrees of freedom of the test’s asymptotic distribution and lead to better size-power properties, even in high dimensions. The gains are especially pronounced for vine copulas, where additional benefits come from simplifications of score functions and the Hessian. We derive the asymptotic distribution of the generalized tests, accounting for the nonparametric estimation of the marginals and apply a parametric bootstrap procedure, valid when asymptotic critical values are inaccurate. In Monte Carlo simulations, we study the behavior of the new tests, compare them with several Cramer–von Mises type tests and confirm the desired properties of the new tests in high dimensions.     

A Tiered Framework for Risk‐Relevant Characterization and Ranking of Chemical Exposures: Applications to the National Children's Study (NCS)

A challenge for large‐scale environmental health investigations such as the National Children's Study (NCS), is characterizing exposures to multiple, co‐occurring chemical agents with varying spatiotemporal concentrations and consequences modulated by biochemical, physiological, behavioral, socioeconomic, and environmental factors. Such investigations can benefit from systematic retrieval, analysis, and integration of diverse extant information on both contaminant patterns and exposure‐relevant factors. This requires development, evaluation, and deployment of informatics methods that support flexible access and analysis of multiattribute data across multiple spatiotemporal scales. A new “Tiered Exposure Ranking” (TiER) framework, developed to support various aspects of risk‐relevant exposure characterization, is described here, with examples demonstrating its application to the NCS. TiER utilizes advances in informatics computational methods, extant database content and availability, and integrative environmental/exposure/biological modeling to support both “discovery‐driven” and “hypothesis‐driven” analyses. “Tier 1” applications focus on “exposomic” pattern recognition for extracting information from multidimensional data sets, whereas second and higher tier applications utilize mechanistic models to develop risk‐relevant exposure metrics for populations and individuals. In this article, “tier 1” applications of TiER explore identification of potentially causative associations among risk factors, for prioritizing further studies, by considering publicly available demographic/socioeconomic, behavioral, and environmental data in relation to two health endpoints (preterm birth and low birth weight). A “tier 2” application develops estimates of pollutant mixture inhalation exposure indices for NCS counties, formulated to support risk characterization for these endpoints. Applications of TiER demonstrate the feasibility of developing risk‐relevant exposure characterizations for pollutants using extant environmental and demographic/socioeconomic data.