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Article
Publication date: 5 April 2022

David Huntsman, Alex Greer, Haley Murphy and Xiangyu (Dale) Li

While uncertainty during emergency response operations necessitates adaptive performance, emergency response organizations, such as the fire service, tend to constrain adaptive…

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Abstract

Purpose

While uncertainty during emergency response operations necessitates adaptive performance, emergency response organizations, such as the fire service, tend to constrain adaptive behaviors due to their highly formalized bureaucratic structures. Structural theories suggest that leaders can empower employees to bypass these constraints.

Design/methodology/approach

Using survey data from four US fire departments, this research tests whether mid-level supervisors can empower firefighters by increasing their ability to improvise during complex emergency response operations, and whether this enhances department adaptive performance. Moderated mediation is also performed to assess whether senior leaders must also be effective, empowering leaders in order to achieve heightened levels of empowerment and subsequent adaptive performance, as many senior leaders in the fire service are criticized for being overly bureaucratic, risk averse, and resistant to change.

Findings

The findings support compensatory effects and show how immediate supervisors are key to overcoming senior leader deficiencies and producing adaptive performance during conditions of high uncertainty and complexity.

Originality/value

The lack of response organizations’ success during complex incidents is often attributed to senior leaders who are risk averse, overly bureaucratic, and resistant to change (Wankhade and Patnaik, 2020). This study is the first to show how empowering leadership can help overcome these constraints to enhance adaptive performance under complex conditions in the fire service.

Details

International Journal of Emergency Services, vol. 11 no. 2
Type: Research Article
ISSN: 2047-0894

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Article
Publication date: 25 May 2022

Yee Sye Lee, Ali Rashidi, Amin Talei, Mehrdad Arashpour and Farzad Pour Rahimian

In recent years, deep learning and extended reality (XR) technologies have gained popularity in the built environment, especially in construction engineering and management. A…

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Abstract

Purpose

In recent years, deep learning and extended reality (XR) technologies have gained popularity in the built environment, especially in construction engineering and management. A significant amount of research efforts has been thus dedicated to the automation of construction-related activities and visualization of the construction process. The purpose of this study is to investigate potential research opportunities in the integration of deep learning and XR technologies in construction engineering and management.

Design/methodology/approach

This study presents a literature review of 164 research articles published in Scopus from 2006 to 2021, based on strict data acquisition criteria. A mixed review method, consisting of a scientometric analysis and systematic review, is conducted in this study to identify research gaps and propose future research directions.

Findings

The proposed research directions can be categorized into four areas, including realism of training simulations; integration of visual and audio-based classification; automated hazard detection in head-mounted displays (HMDs); and context awareness in HMDs.

Originality/value

This study contributes to the body of knowledge by identifying the necessity of integrating deep learning and XR technologies in facilitating the construction engineering and management process.

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