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.     

The ‘Bakul Gendong’ as a communication strategy to reject the construction of a cement factory in Central Java

Since 2006, one of Indonesia’s biggest corporations operating in the cement industry has been trying to build a factory at Sukolilo village in Central Java, Indonesia. The potential for of environmental damage caused by mining and the construction of this new factory is the main source of conflict between the public and the giant corporation.The focus of this research was the communication strategy adopted by women in the community to reject the construction of the cement factory in Pati, Central Java, Indonesia. This research used a qualitative method through a case study approach. Interviews, observations, and literature studies were used as data collection techniques for in this research.We found that the practices of the “Bakul Gendong” communication strategy were effective in developing women’s awareness of environmental issues based on the values they believe in. Through the women peddlers, women’s awareness of the risk of environmental damage caused by the cement factories was successfully developed. They also created female farmers’ group named “Simbar Wareh” to strengthen cooperation between them and to better-organize their resistance. The women’s movement to resist the cement factory was also conducted by building a network, meeting authorities, demonstrating, displaying traditional symbols during celebrations such as the “Agustusan” (independence day celebration) and Kartinian (women’s day) as their sites of resistance. The local government and PT. Semen Gresik tended to use technical and economical communicative approaches, while the people mainly refer to local know how PT. Semen Gresik did not use the right communication strategy to understand the conflict that arose and how to handle it, until after 10 years of trying to build a factory in Sukolilo.     

The Aversion to Tampering with Nature (ATN) Scale: Individual Differences in (Dis)comfort with Altering the Natural World

People differ in their comfort with tampering with the natural world. Although some see altering nature as a sign of human progress, others see it as dangerous or hubristic. Across four studies, we investigate discomfort with tampering with the natural world. To do so, we develop the Aversion to Tampering with Nature (ATN) Scale, a short scale that is the first to directly measure this discomfort. We identify six activities that people believe tamper with nature (geoengineering, genetically modified organisms, pesticides, cloning, gene therapy, and nanoparticles) and show that ATN scores are associated with opposition to these activities. Furthermore, the ATN Scale predicts actual behavior: donations to an anti-tampering cause. We demonstrate that ATN is related to previously identified constructs including trust in technology, naturalness bias, purity values, disgust sensitivity, aversion to playing God, and environmental beliefs and values. By illuminating who is concerned about tampering with nature and what predicts these beliefs, the ATN Scale provides opportunities to better understand public opposition to technological innovations, consumer preferences for “natural” products, and strategies for science communication.     

数字经济供给使用表:概念架构与编制实践研究

数字经济供给使用表是数字经济卫星账户的核心表式,具有统计协调和分析工具的双重作用,能够准确监测数字经济产业发展规模及传统产业与数字经济的融合程度。目前,国际上对数字经济供给使用表的研究尚处于初期探索阶段,还未有国家编制出基于实际数据的数字经济供给使用表,经济合作与发展组织(OECD)对数字经济供给使用表的理论框架进行了前瞻性探索,但系统的数字经济供给使用表构建指南还亟待完善。本文首先从供给和使用层面构建数字经济供给使用表概念框架,界定数字经济特征活动的概念和范围,梳理OECD 划分的数字经济供给使用表中的产品清单和数字经济产业分类;阐释数字经济最终消费、固定资本形成、贸易活动的内涵和种类。其次,围绕“产品×产业×特征活动”三重维度,设计数字经济供给使用表整体架构、阐明其核心指标。再次,编制数字经济供给使用表实例,剖析编制流程、总结编制要点。最后,提出结论和建议。本文尝试完善数字经济统计核算体系,为提出促进我国数字经济高质量发展的政策建议提供核算方法参考。     

COWORDS: a probabilistic model for multiple word clouds

Word clouds constitute one of the most popular statistical tools for the visual analysis of text documents because they provide users with a quick and intuitive understanding of the content. Despite their popularity for visualizing single documents, word clouds are not appropriate to compare different text documents. Independently generating word clouds for each document leads to configurations where the same word is typically located in widely different positions. This makes it very difficult to compare two or more word clouds. This paper introduces COWORDS, a new stochastic algorithm to create multiple word clouds, including one for each document. The shared words in multiple documents are placed in the same position in all clouds. Similar documents produce similar and compact clouds, making it easier to simultaneously compare and interpret several word clouds. The algorithm is based on a probability distribution in which the most probable configurations are those with a desirable visual aspect, such as a low value for the total distance between the words in all clouds. The algorithm output is a set of word clouds that are randomly selected from this probability distribution. The selection procedure uses a Markov chain Monte Carlo simulation method. We present several examples that illustrate the performance and visual results that can be obtained by our algorithm.     

Experiences with systematic triangulation at the Global Environment Facility

Systematic triangulation may address common challenges in evaluation, such as the scarcity or unreliability of data, or the complexities of comparing and cross-checking evidence from diverse disciplines. Used to identify key evaluation findings, its application has proven to be effective in addressing the limitations encountered in country-level evaluation analysis conducted by the Independent Evaluation Office of the Global Environment Facility (GEF). These include the scarcity or unreliability of national statistics on environmental indicators and data series, especially in Least Developed Countries; challenges in evaluating the impacts of GEF projects; and inherent difficulties in defining the GEF portfolio of projects prior to the undertaking of the evaluation. In addition to responding to the need for further developing triangulation protocols, procedures and/or methodologies advocated by some authors, the approach offers a contribution to evaluation practice. This applies particularly to those evaluation units tasked with country-level evaluations in international organizations, facing similar constraints.     

Risk Perception and Information Processing: The Development and Validation of a Questionnaire to Assess Self‐Reported Information Processing

The role of information processing in understanding people's responses to risk information has recently received substantial attention. One limitation of this research concerns the unavailability of a validated questionnaire of information processing. This article presents two studies in which we describe the development and validation of the Information‐Processing Questionnaire to meet that need. Study 1 describes the development and initial validation of the questionnaire. Participants were randomized to either a systematic processing or a heuristic processing condition after which they completed a manipulation check and the initial 15‐item questionnaire and again two weeks later. The questionnaire was subjected to factor reliability and validity analyses on both measurement times for purposes of cross‐validation of the results. A two‐factor solution was observed representing a systematic processing and a heuristic processing subscale. The resulting scale showed good reliability and validity, with the systematic condition scoring significantly higher on the systematic subscale and the heuristic processing condition significantly higher on the heuristic subscale. Study 2 sought to further validate the questionnaire in a field study. Results of the second study corresponded with those of Study 1 and provided further evidence of the validity of the Information‐Processing Questionnaire. The availability of this information‐processing scale will be a valuable asset for future research and may provide researchers with new research opportunities.     

The effect of cognitive diversity on the illusion of control bias in strategic decisions: An experimental investigation

By integrating cognitive diversity into debiasing literature, this paper contributes towards opening the black box of executive judgment. Based on information processing theory we investigate the role of cognitive diversity in strategic decision making. We apply a vignette-based experimental research design to examine the effect of cognitive diversity in teams on decision maker's illusion of control. The results of these experiments provide evidence for a positive influence of high cognitive diversity for debiasing judgment while similarly indicating no such effect for groups with low cognitive diversity. These findings suggest that group composition aspects can play an important role for improving judgment in decision making teams and open promising new avenues for studying debiasing in behavioral strategy research.