Open information system and crisis communication in China

This paper discusses the role of media and communication at times of public crisis and contends that a modern, open information system is a precondition for good crisis management. It traces evolving policy discourse in Mainland China with a special focus on the relationship between the authorities and media. An overview is provided to contextualize and historicize the contemporary development. By examining a series of critical news events triggered by public crises, especially the Severe Acute Respiratory Syndrome (SARS) epidemic in 2003, it provides a broad assessment of the issues involved in the creation of China's open information system, with regard to both institutional policy‐making as well as everyday journalistic practices in reporting the emergent events. Finally, the paper discusses pertinent legislative and regulatory measures in recent years that hold particular importance to state‐media relationship during public crises, especially the Emergency Response Law promulgated in June 2007.     

Review article

Social processes in the world today are characterized by the growing importance of relations between actors located in different national spaces (transnational relations). Based on case studies, this article illustrates how nowadays transnational relations between local and transnational actors affect in different ways the social production of representations that are sociopolitically significant – insofar as they articulate meanings in the constitution and practices of social organizations and movements of diverse political orientations. Through the analysis of cases related to the social production of representations of ideas of pan-ethnic indigenous identities, ‘culture and development’, ‘civil society’, and ‘free trade’, this text seeks to contribute to the theoretical debate about culture, communication, and social change in the contemporary world. The cases discussed in this article are based on field and documentary research undertaken in Argentina, Bolivia, Ecuador, Mexico, the United States, and Venezuela.     

A Proposed ASEAN Disaster Response, Training and Logistic Centre Enhancing Regional Governance in Disaster Management

The Southeast Asian region is remarkably vulnerable to natural disasters which repeatedly cause devastations to both human lives and properties. However, current disaster relief efforts have not lived up to the high standards. Even worse is that humanitarian efforts have been frequently frustrated by the rejections from national authorities under the name of “sovereignty”. All these problems necessitate a widely accepted, politically neutral, well coordinated and effectively governed organization within the region. We, hereby propose a Disaster Response Training and Logistic Centre under the umbrella of the Association of Southeast Asian Nations (ASEAN), which aims to mitigate the devastation of disasters, to provide accurate relief assessment, and training for relief team on a regular basis, and to allocate and mobilize humanitarian aid. The Centre will be endorsed through an agreement by all ASEAN governments. The philosophy underpinning the organization reflects a regional approach whereby stronger government involvement and regional integration in disaster relief is indispensable in the context of the Southeast Asian region.      

Nonparametric binary regression using a Gaussian process prior

The article describes a nonparametric Bayesian approach to estimating the regression function for binary response data measured with multiple covariates. A multiparameter Gaussian process, after some transformation, is used as a prior on the regression function. Such a prior does not require any assumptions like monotonicity or additivity of the covariate effects. However, additivity, if desired, may be imposed through the selection of appropriate parameters of the prior. By introducing some latent variables, the conditional distributions in the posterior may be shown to be conjugate, and thus an efficient Gibbs sampler to compute the posterior distribution may be developed. A hierarchical scheme to construct a prior around a parametric family is described. A robustification technique to protect the resulting Bayes estimator against miscoded observations is also designed. A detailed simulation study is conducted to investigate the performance of the proposed methods. We also analyze some real data using the methods developed in this article.     

A Compromise Experimental Design Method for Parametric Polynomial Response Surface Approximations

This study presents a compromise approach to augmentation of experimental designs, necessitated by the expense of performing each experiment (computational or physical), that yields higher quality parametric polynomial response surface approximations than traditional augmentation. Based on the D-optimality criterion as a measure of experimental design quality, the method simultaneously considers several polynomial models during the experimental design, resulting in good quality designs for all models under consideration, as opposed to good quality designs only for lower-order models, as in the case of traditional augmentation. Several numerical examples and an engineering example are presented to illustrate the efficacy of the approach.     

社会治理视域下防范和应对突发事件的策略研究

目前我国的社会正在经历前所未有的深层次变革,社会各项事业正在面临深层创新与发展。在这一特定的历史时期内,多元化社会矛盾所导致的突发事件大量出现,为我国社会治理提出了严峻的挑战。突发事件形成的原因不仅有社会转型与体制转轨的诱发、基层政府社会治理水平的不足、社会自我调控能力的薄弱,同时也有法治建设的不完善以及社会保障的诸多漏洞等。因此,必须要从加强社会治理,维护社会稳定、提高政府的社会治理水平、培育多元社会治理主体、推进法制与社会保障建设等途径入手提高整个社会防范与应对突发事件的综合能力。     

Pro-innovation culture,ambidexterity and new product development performance: Polynomial regression and response surface analysis

This study examines the intervening role of organizational ambidexterity in the relationship between pro-innovation culture and new product development (NPD) performance. The results indicate that organizational ambidexterity positively mediates the relationship between pro-innovation culture and NPD performance. The results show that when both exploration and exploitation are increased simultaneously, after an initial decline, NPD performance shows a rising trend. NPD performance tends to decline generally when there is an imbalance between the two though the plateau is at a point where exploitation is slightly higher than exploration. Additionally, pro-innovation culture can increase the gap between exploration and exploitation for exploration-oriented firms, which can lower their NPD performance. Overall, this study contributes to a deeper understanding of the underlying mechanisms that explain why firms with pro-innovation culture have higher NPD performance. Further, it enhances our understanding of the role of pro-innovation culture as an organizational context for building organizational ambidexterity, and provides new insights that can help reconcile the combined and balanced views of ambidexterity in enhancing NPD performance.     

A numerical study for comparing two response-adaptive designs for continuous treatment effects

We study two sequential, response-adaptive randomized designs for clinical trials; one has been proposed in Bandyopadhyay and Biswas (Biometrika 88: 409–419, 2001) and in Biswas and Basu (Sankhya Ser B 63:27–42, 2001), the other stems from the randomly reinforced urn introduced and studied in Muliere et al. (J Stat Plan Inference 136:1853–1874, 2006a). Both designs can be used in clinical trials where the response from each patient is a continuous variable. Comparison is conducted through numerical studies and along a new guideline for the evaluation of a response-adaptive design.     

On some robust estimation procedures for quantiles based on data

This paper introduces some robust estimation procedures to estimate quantiles of a continuous random variable based on data, without any other assumptions of probability distribution. We construct a reasonable linear regression model to connect the relationship between a suitable symmetric data transformation and the approximate standard normal statistics. Statistical properties of this linear regression model and its applications are studied, including estimators of quantiles, quartile mean, quartile deviation, correlation coefficient of quantiles and standard errors of these estimators. We give some empirical examples to illustrate the statistical properties and apply our estimators to grouping data.     

Box‐Cox transformations in linear models: Large sample theory and tests of normality

The authors provide a rigorous large sample theory for linear models whose response variable has been subjected to the Box‐Cox transformation. They provide a continuous asymptotic approximation to the distribution of estimators of natural parameters of the model. They show, in particular, that the maximum likelihood estimator of the ratio of slope to residual standard deviation is consistent and relatively stable. The authors further show the importance for inference of normality of the errors and give tests for normality based on the estimated residuals. For non‐normal errors, they give adjustments to the log‐likelihood and to asymptotic standard errors.