Author
Matthew R. Hallowell
Other affiliations: Oregon State University, Bucknell University
Bio: Matthew R. Hallowell is an academic researcher from University of Colorado Boulder. The author has contributed to research in topics: Construction site safety & Construction management. The author has an hindex of 35, co-authored 119 publications receiving 4233 citations. Previous affiliations of Matthew R. Hallowell include Oregon State University & Bucknell University.
Papers published on a yearly basis
Papers
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TL;DR: In this article, the Delphi technique has been used to identify and qualify potential expert panelists according to objective guidelines and select appropriate parameters of the study such as the number of panelists, number of rounds, type of feedback, and measure of consensus.
Abstract: Construction engineering and management CEM researchers often rely on alternative research techniques when traditional methods fail. For example, surveys, interviews, and group-brainstorming techniques may not be appropriate for research that involves confounding factors and requires access to sensitive data. In such an environment, the Delphi technique allows researchers to obtain highly reliable data from certified experts through the use of strategically designed surveys. At present, the Delphi method has not seen widespread use in CEM research. This is likely due to variation among studies that implement Delphi in CEM research and ambiguity in literature that provides guidance for the specific parameters associated with the method. Using the guidance in this paper, the reader may: 1 understand the merits, appropriate application, and appropriate procedure of the traditional Delphi process; 2 identify and qualify potential expert panelists according to objective guidelines; 3 select the appropriate parameters of the study such as the number of panelists, number of rounds, type of feedback, and measure of consensus; 4 identify potential biases that may negatively impact the quality of the results; and 5 appropriately structure the surveys and conduct the process in such a way that bias is minimized or eliminated.
664 citations
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TL;DR: The review indicates that the existing wearable technologies applied in other industrial sectors can be used to monitor and measure a wide variety of safety performance metrics within the construction industry.
259 citations
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TL;DR: In this paper, the authors describe the results of a recent study designed to determine the relative effectiveness of safety program elements by quantifying their individual ability to mitigate construction safety and health risks.
Abstract: Construction safety and health management has improved significantly following the Occupational Safety and Health Act of 1970. In response to this legislation, contractors began implementing safety programs to reduce occupational safety and health hazards on construction sites. Researchers recently found that the current process of selecting specific elements for a safety program is informal. This paper describes the results of a recent study designed to determine the relative effectiveness of safety program elements by quantifying their individual ability to mitigate construction safety and health risks. In order to determine the effectiveness of individual safety program elements, the following research activities were performed: (1) an appropriate safety risk classification system was created using an aggregation of relevant literature; (2) highly effective safety program elements were identified in literature; and (3) the ability of each safety program element to mitigate a portion of each of the safety risk classes was quantified using the Delphi method. The results of the research indicate that the most effective safety program elements are upper management support and commitment and strategic subcontractor selection and management and the least effective elements are recordkeeping and accident analyses and emergency response planning. It is expected that the data presented in this paper can be used to strategically select elements for a safety program, target specific safety and health risks, and influence resource allocation when funds are limited.
214 citations
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TL;DR: The proposition that manual content analysis of injury reports can be eliminated using natural language processing (NLP) is tested and the results indicate that the NLP system is capable of quickly and automatically scanning unstructured injury reports for 101 attributes and outcomes with over 95% accuracy.
204 citations
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TL;DR: Two state-of-the-art ML models, Random Forest and Stochastic Gradient Tree Boosting, were applied to a data set of carefully featured attributes and categorical safety outcomes, extracted from a large pool of textual construction injury reports via a highly accurate Natural Language Processing tool developed by past research.
200 citations
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01 Jan 2006
TL;DR: Probability distributions of linear models for regression and classification are given in this article, along with a discussion of combining models and combining models in the context of machine learning and classification.
Abstract: Probability Distributions.- Linear Models for Regression.- Linear Models for Classification.- Neural Networks.- Kernel Methods.- Sparse Kernel Machines.- Graphical Models.- Mixture Models and EM.- Approximate Inference.- Sampling Methods.- Continuous Latent Variables.- Sequential Data.- Combining Models.
10,141 citations
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01 May 1981TL;DR: This chapter discusses Detecting Influential Observations and Outliers, a method for assessing Collinearity, and its applications in medicine and science.
Abstract: 1. Introduction and Overview. 2. Detecting Influential Observations and Outliers. 3. Detecting and Assessing Collinearity. 4. Applications and Remedies. 5. Research Issues and Directions for Extensions. Bibliography. Author Index. Subject Index.
4,948 citations
01 Jan 2008
TL;DR: In this article, the authors argue that rational actors make their organizations increasingly similar as they try to change them, and describe three isomorphic processes-coercive, mimetic, and normative.
Abstract: What makes organizations so similar? We contend that the engine of rationalization and bureaucratization has moved from the competitive marketplace to the state and the professions. Once a set of organizations emerges as a field, a paradox arises: rational actors make their organizations increasingly similar as they try to change them. We describe three isomorphic processes-coercive, mimetic, and normative—leading to this outcome. We then specify hypotheses about the impact of resource centralization and dependency, goal ambiguity and technical uncertainty, and professionalization and structuration on isomorphic change. Finally, we suggest implications for theories of organizations and social change.
2,134 citations