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The purpose of this paper is to propose an effective knowledge elicitation method and representation scheme that empowers humanitarian assistance/disaster relief (HA/DR) analysts and experts to create analytic models without the aid of data scientists and methodologists while addressing the issues of complexity, collaboration, and emerging technology across a diverse global network of HA/DR organizations.

The paper used a mixed-methods research approach, with qualitative research and analysis to select the model elicitation method, followed by quantitative data collection and evaluation to test the representation scheme. A simplified analytic modeling approach was created based on emerging activity-based intelligence (ABI) analytic methods.

Using open source data on the Syrian humanitarian crisis as the reference mission, ABI analytic models were proven capable in modeling HA/DR scenarios of physical systems, nonphysical systems, and thinking.

As a data-agnostic approach to develop object and network knowledge, ABI aligns with the objectives of modeling within multiple HA/DR organizations.

Using an analytic method as the basis for model creation allows for immediate adoption by analysts and removes the need for data scientists and methodologists in the elicitation phase. Applying this highly effective cross-domain ABI data fusion technique should also supplant the accuracy weaknesses created by traditional simplified analytic models.

The purpose of this paper is to apply Lean in the workers’ compensation industry. It focuses on identifying patterns of repetitive non-value-added transnational activities for physical-therapy patients and healthcare providers. It addresses the research gap in this field.

In this study, we designed and deployed multiple case studies to better understand the journey of an injured worker within the worker compensation system in the United States of America. We partnered with Concentra Inc., a leading national healthcare provider in the field of workers’ compensation having 520 medical centers in 44 states. Both case studies included conducting direct observations, Gemba walk, in five clinics in two states: Florida and Pennsylvania. We analyzed the data of 263 injured workers with 8 or more physical therapy visits who got admitted to Concentra clinics in both states over the period of 31 days.

The results revealed that the time intervals at which activities associated with physical therapy treatment pre-authorization accounted for 91.59% of the total non-value-added activities and are thus the key administrative factor leading to process inefficiency in the state of Florida. The Process Cycle Efficiency of Pennsylvania was 75.36% compared to 53.16% of Florida. The injured workers in Florida needed 39.58 days on average to complete eight physical therapy visits compared to 27.92 days in Pennsylvania (a median of 34.09 vs 22.15 days).

This study is limited as it only focuses on processes on the healthcare provider side. An expanded value stream map that includes the treatment pre-authorization process on the insurance side would be beneficial for generating more potential solutions to streamline the process.

This study shows that Lean could play a critical role in identifying and quantifying continuous improvement opportunities that could accelerate patient’s treatment, reduce administrative burden on healthcare providers and improve the overall claim cost of insurance companies. It provides data-driven argument for insurance companies to consider eliminating physical therapy pre-authorization.

This is the first study to apply Lean methodology in the workers’ compensation field.

The purpose of this paper is to provide insights into the relationship between ISO 9001 conformance of suppliers and the quality of products they provide, within a procurement system of a manufacturer operating under contracts with the US Department of Defense.

Chi‐square tests of independence were performed to compare the receipt acceptance rate of material provided by ISO 9001‐conforming suppliers to that of non‐ISO 9001‐conforming suppliers, for more than 46,000 receipts representing 21 material commodity groups provided by almost 800 suppliers. Acceptance of receipts required conformance to both hardware and paperwork requirements. Tests were also performed on data subsets, to determine the impact of ISO 9001 conformance on product quality for each of the 21 material commodity groups, for manufacturers versus distributors, and for two material control levels.

For the overall data set, and for the majority of data subsets analyzed, the product quality of non‐ISO 9001‐conforming suppliers was significantly better than that of ISO 9001‐conforming suppliers. When only hardware non‐conformances were considered to cause rejections, the results were similar, but effect sizes were generally smaller.

The quantities of receipts and suppliers included in this investigation were very large; however, care should be exercised in generalizing the results, because of the potential influence of the defense industry‐related requirements imposed upon the material and the suppliers.

This is believed to be the first paper to investigate the impact of ISO 9001 conformance on product quality using a large quantity of actual product data, for both ISO 9001‐conforming and non‐ISO 9001‐conforming suppliers, in contrast to numerous assessments of quality impact performed using interview and survey data.

The purpose of this paper is to provide maintenance personnel with a methodology for using masked field reliability data to determine the probability of each subassembly failure.

The paper compares an iterative maximum likelihood estimation method and a Bayesian methodology for handling masked data collected from 227 identical radar power supplies. The power supply consists of several subassemblies hereafter referred to as shop replaceable assemblies (SRAs).

The study examined two approaches for dealing with masking, an iterative maximum likelihood estimate procedure, IMLEP, and a Bayesian approach implemented with the application WinBUGS. It indicates that the performances of IMLEP and WinBUGS in estimating the parameters of the SRA distribution under no masking conditions are similar. IMLEP and WinBUGS also provide similar results under masking conditions. However, the study indicates that WinBUGS may perform better than IMLEP when the competing risk responsible for a failure represents a smaller total percentage of the total failures. Future study to confirm this conclusion by expanding the number of SRAs into which the item under study is organized is required.

If an item is considered to be comprised of various subassemblies and the failure of the first subassembly causes the item to fail, then the item is referred to as a series system in the literature. If the probability of a each subassembly failure is statistically independent then the item can be represented by a competing risk model and the probability distributions of the subassemblies can be ascertained from the item's failure data. When the item's cause of failure is not known, the data are referred to in the literature as being masked. Since competing risk theory requires a cause of failure and a time of failure, any masked data must be addressed in the competing risk model.

This study indicates that competing risk theory can be applied to the equipment field failure data to determine a SRA's probability of failure and thereby provide an efficient sequence of replacing suspect failed SRAs.

The analysis of masked failure data is an important area that has had only limited study in the literature due to the availability of failure data. This paper contributes to the research by providing the complete historical equipment usage data for the item under study gathered over a time frame of approximately seven years.

This research aims to examine the relationship between information security strategy and organization performance, with organizational capabilities as important factors influencing successful implementation of information security strategy and organization performance.

Based on existing literature in strategic management and information security, a theoretical model was proposed and validated. A self‐administered survey instrument was developed to collect empirical data. Structural equation modeling was used to test hypotheses and to fit the theoretical model.

Evidence suggests that organizational capabilities, encompassing the ability to develop high‐quality situational awareness of the current and future threat environment, the ability to possess appropriate means, and the ability to orchestrate the means to respond to information security threats, are positively associated with effective implementation of information security strategy, which in turn positively affects organization performance. However, there is no significant relationship between decision making and information security strategy implementation success.

The study provides a starting point for further research on the role of decision‐making in information security.

Findings are expected to yield practical value for business leaders in understanding the viable predisposition of organizational capabilities in the context of information security, thus enabling firms to focus on acquiring the ones indispensable for improving organization performance.

This study provides the body of knowledge with an empirical analysis of organization's information security capabilities as an aggregation of sense making, decision‐making, asset availability, and operations management constructs.