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The study provides an initial empirical examination of Jin et al.’s (2024) new READINESS model through the expert opinions of crisis communication academics and practitioners. Through this examination, the goal is to understand crisis READINESS and how it relates to other key concepts in the crisis literature, such as preparedness and resilience.

An exploratory quantitative online survey of 30 experts in crisis communication was conducted. Our participant pool consisted of members from the Crisis Communication Think Tank, which is an established crisis thought leadership network (Jin, 2023). Data collection took place in November and December 2023.

Key findings include the dual nature of crisis READINESS as both a process and an outcome, resilience as both a process and an outcome, and preparedness as an antecedent to READINESS. A key distinction between READINESS and preparedness emerged with the former conceived of as a mindset and the latter conceived of as physical tools, training and planning.

Preparedness and resilience alone are not enough to effectively manage crises and risks, and given this, it is important to study READINESS as a concept beyond (yet connected to) preparedness and resilience. It is our hope that the findings can lead to understanding indicators of crisis READINESS and developing crisis READINESS measurement tools which can equip organizations to more effectively manage crises.

In recent decades, interest in digital transformation (DX) within the architecture, engineering, and construction (AEC) industry has significantly increased. Despite the existence of several literature reviews on DX research, there remains a notable lack of systematic quantitative and visual investigations into the structure and evolution of this field. This study aims to address this gap by uncovering the current state, key topics, keywords, and emerging areas in DX research specific to the AEC sector.

Employing a holistic review approach, this study undertook a thorough and systematic analysis of the literature concerning DX in the AEC industry. Utilizing a bibliometric analysis, 3,656 papers were retrieved from the Web of Science spanning the years 1990–2023. A scientometric analysis was then applied to these publications to discern patterns in publication years, geographical distribution, journals, authors, citations, and keywords.

The findings identify China, the USA, and England as the leading contributors in the field of DX in AEC sector. Prominent keywords include “building information modeling”, “design”, “system”, “framework”, “adoption”, “model”, “safety”, “internet of things”, and “innovation”. Emerging areas of interest are “deep learning”, “embodied energy”, and “machine learning”. A cluster analysis of keywords reveals key research themes such as “deep learning”, “smart buildings”, “virtual reality”, “augmented reality”, “smart contracts”, “sustainable development”, “building information modeling”, “big data”, and “3D printing”.

This study is among the earliest to provide a comprehensive scientometric mapping of the DX field. The findings presented here have significant implications for both industry practitioners and the scientific community, offering a thorough overview of the current state, prominent keywords, topics, and emerging areas within DX in the AEC industry. Additionally, this research serves as an invaluable reference and guideline for scholars interested in this subject.