Public Multichannel Management – an Integrated Framework of Off- and Online Multichannel Government Services

Government institutions have introduced multichannel environments over time following trends and technological innovations. These public multichannel environments often neglect specific channel characteristics and potentials and thus miss the opportunity to make full use of a strategic channel integration and combination with a focus on customer value creation. This study offers a systematic approach to establish an integrated public multichannel system not only taking into account user preferences, habits and their environment, but also the respective channel issuer and the characteristics of channels and public interfaces. Against this background, the study presents a systematic approach to expand services and channels according to their capacities, and provides academics and practitioners with a framework on public multichannel strategies.     

An omnibus lack of fit test in logistic regression with sparse data

The usefulness of logistic regression depends to a great extent on the correct specification of the relation between a binary response and characteristics of the unit on which the response is recoded. Currently used methods for testing for misspecification (lack of fit) of a proposed logistic regression model do not perform well when a data set contains almost as many distinct covariate vectors as experimental units, a condition referred to as sparsity. A new algorithm for grouping sparse data to create pseudo replicates and using them to test for lack of fit is developed. A simulation study illustrates settings in which the new test is superior to existing ones. Analysis of a dataset consisting of the ages of menarche of Warsaw girls is also used to compare the new and existing lack of fit tests.     

Qualitätsmanagement in organisierten HandlungssystemenQuality Management in Organized Systems of Action

Despite their prevalence and prominence, quality management in organizations as well as the various discourses on the topic lack theoretical framework and pervasion. The field is dominated by empirical-inductive experiences stemming from the so-called practice on the one hand and by pragmatic-normative suggestions for this practice. In contrast, for the purpose of a theoretically based analysis, we identify four implicit principles as the basal grammar of contemporary strategies of quality management, locate them within the Parsonian scheme of organized action systems, and embed them into the broader context of economy and society. This Parsonian perspective makes us aware of quality management as a one-dimensional imperative for action that in reality is still undermined, however, by subversive quality management practices, following a fifth principle.     

Hallmarks of the Political in Community Organizing: An Arendtian Perspective

VOLUNTAS: International Journal of Voluntary and Nonprofit Organizations - Drawing upon Hannah Arendt’s adherence to existential phenomenology, the article advances a political understanding...     

State Immigration Policies: The Role of State Compacts and Interest Groups on Immigration Legislation

US states are active in enacting immigration policies, which vary widely and have substantial impact on the lives of immigrants. Our understanding of what produces these divergent state laws remains limited. Qualitative research demonstrates the importance of a 2010 immigration compact, supported by a powerful religious organization, in shaping immigration policies in Utah, and the Utah Compact was held up as a model for other states. But is the experience of Utah applicable across other states? We test the effects of compacts and interest groups on immigration policy adoption across all 50 states between 2005 and 2013. Our findings suggest that compacts are actually associated with more restrictive immigration policy. Although states with compacts are more likely to pass inclusive immigration laws, these are counterbalanced by higher numbers of exclusive laws. Both religious and non‐religious interests groups are associated with policy, but they do not explain the effects of compacts.     

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.     

Major Accidents (Gray Swans) Likelihood Modeling Using Accident Precursors and Approximate Reasoning

Compared to the remarkable progress in risk analysis of normal accidents, the risk analysis of major accidents has not been so well‐established, partly due to the complexity of such accidents and partly due to low probabilities involved. The issue of low probabilities normally arises from the scarcity of major accidents’ relevant data since such accidents are few and far between. In this work, knowing that major accidents are frequently preceded by accident precursors, a novel precursor‐based methodology has been developed for likelihood modeling of major accidents in critical infrastructures based on a unique combination of accident precursor data, information theory, and approximate reasoning. For this purpose, we have introduced an innovative application of information analysis to identify the most informative near accident of a major accident. The observed data of the near accident were then used to establish predictive scenarios to foresee the occurrence of the major accident. We verified the methodology using offshore blowouts in the Gulf of Mexico, and then demonstrated its application to dam breaches in the United Sates.