Reducing Refusal Rates for Telephone Interviews

In two experiments, refusal rates to telephone interviews werenot affected by substantial changes in the introductory remarksof the interviewer. A prior letter significantly lowered refusalrates in a third experiment. In all three, interviewer sex hadno effect.     

Priority Setting for the Distribution of Localized Hazard Protection

We address the problem of distributing safety-enhancing devices across a region, where each identical device provides for only local protection of the population. The devices protect nonidentical sectors of the population. The sectors of population are exposed to nonidentical intensities of hazard. A method for the screening and prioritizing of needs for the protective devices is described. An approach of risk-benefit-cost analysis under uncertainty is recommended as follows. Measures of hazard intensity and population exposure are identified. Exogenous parameters that influence assessments of risks, benefits, and costs are identified. Uncertainties of the exogenous parameters are propagated by interval analysis. Several tiers of the plausibility of need for protection are identified. The tiers are useful in setting priorities for the distribution of the safety devices. The method is demonstrated in an engineering application to roadway lighting, but has implications for disaster preparedness, anti-terrorism, transportation safety, and other arenas of public safety.     

Analytical network process for software selection in product development: A case study

Application of software for manufacturing processes is one of the resolutions many enterprises have resorted to in the 21st century. This has been a result of increased complexity of products, globalization, rapid changes in technology and so on. The idea was that application of software especially for product development would increase the competitive advantage of industry nevertheless the irony has been that most of the investment in software has not achieved the expected results. We carry out a case study to introduce a methodology, the analytical network process as a multiattribute strategic decision making approach to help in the selection of appropriate software to suit the product development process of a particular product.     

A MINIMUM-COST AUDIT SAMPLING METHODOLOGY UNDER CONDITIONS OF PREDETERMINED BETA RISK

This paper presents a minimum-cost methodology for determining a statistical sampling plan in substantive audit tests. In this model, the auditor specifies β, the risk of accepting an account balance as correct when it is not, according to audit evidence requirements. Using β as a constraint, the auditor then selects a sampling plan to optimize the trade-off between sampling costs and the costs of follow-up audit procedures. Tables to aid in this process and an illustration are provided.     

Constructing Trustworthy Historical Narratives: Criteria,Principles and Techniques

Organizational scholars increasingly recognize the value of employing historical research. Yet the fields of history and organization studies struggle to reconcile. In this paper, the authors contend that a closer connection between these two fields is possible if organizational historians bring their role in the construction of historical narratives to the fore and open up their research decisions for discussion. They provide guidelines to support this endeavor, drawing on four criteria that are prevalent within interpretive organization studies for developing the trustworthiness of research: credibility; confirmability; dependability; and transferability. In contrast to the traditional use of trustworthiness criteria to evaluate the quality of research, the authors advance the criteria to encourage historians to generate more transparent narratives. Such transparency allows others to comprehend and comment on the construction of narratives, thereby building trust and understanding. Each criterion is converted into a set of guiding principles to enhance the trustworthiness of historical research, pairing each principle with a practical technique gleaned from a range of disciplines within the social sciences to provide practical guidance.     

GIS‐Based Integration of Social Vulnerability and Level 3 Probabilistic Risk Assessment to Advance Emergency Preparedness,Planning, and Response for Severe Nuclear Power Plant Accidents

In the nuclear power industry, Level 3 probabilistic risk assessment (PRA) is used to estimate damage to public health and the environment if a severe accident leads to large radiological release. Current Level 3 PRA does not have an explicit inclusion of social factors and, therefore, it is not possible to perform importance ranking of social factors for risk‐informing emergency preparedness, planning, and response (EPPR). This article offers a methodology for adapting the concept of social vulnerability, commonly used in natural hazard research, in the context of a severe nuclear power plant accident. The methodology has four steps: (1) calculating a hazard‐independent social vulnerability index for the local population; (2) developing a location‐specific representation of the maximum radiological hazard estimated from current Level 3 PRA, in a geographic information system (GIS) environment; (3) developing a GIS‐based socio‐technical risk map by combining the social vulnerability index and the location‐specific radiological hazard; and (4) conducting a risk importance measure analysis to rank the criticality of social factors based on their contribution to the socio‐technical risk. The methodology is applied using results from the 2012 Surry Power Station state‐of‐the‐art reactor consequence analysis. A radiological hazard model is generated from MELCOR accident consequence code system, translated into a GIS environment, and combined with the Center for Disease Control social vulnerability index (SVI). This research creates an opportunity to explicitly consider and rank the criticality of location‐specific SVI themes based on their influence on risk, providing input for EPPR.     

Studying categorical data over time

A review of recently developed simple techniques for analyzing data in the form of proportions from replicated, cross-sectional, sample surveys. (A) One variable over time—tests for homogeneity, pooling homogeneous proportions, tests for linear trends with as few as three time points, tests for departures from linearity; (B) Two variables with a constant percentage difference—four fold tables as rudimentary causal models, decomposing change with linear flow graphs; (C) Extension of the flow graph techniques to—three or more variables and changing coefficients; (D) Comments implying panel designs are somewhat over-rated and successive cross-sections somewhat under-rated.