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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.

The Internet of Things (IoT) offers substantial potential for improving efficiency and effectiveness in various applications, notably within the domain of smart construction. Despite its growing adoption within the Architecture, Engineering, and Construction (AEC) industry, its utilization remains limited. Despite efforts made by policymakers, the shift from traditional construction practices to smart construction poses significant challenges. Consequently, this study aims to explore, compare, and prioritize the determinants that impact the acceptance of the IoT among construction practitioners.

Based on the integrated model of Unified Theory of Acceptance and Use of Technology (UTAUT2), Task-Technology Fit (TTF), and perceived risk. A cross-sectional survey was administered to 309 construction practitioners in China, and the collected data were analyzed using structural equation modeling (SEM) to test the proposed hypotheses.

The findings indicate that TTF, performance expectancy, effort expectancy, hedonic motivation, facilitating conditions, and perceived risk exert significant influence on construction practitioners’ intention to adopt IoT. Conversely, social influence and habit exhibit no significant impact. Notably, the results unveil the moderating influence of gender on key relationships – specifically, performance expectancy, hedonic motivation, and habit – in relation to the behavioral intention to adopt IoT among construction practitioners. In general, the model explains 71% of the variance in the behavioral intention to adopt IoT, indicating that the independent constructs influenced 71% of practitioners’ intentions to use IoT.

These findings provide both theoretical support and empirical evidence, offering valuable insights for stakeholders aiming to gain a deeper understanding of the critical factors influencing practitioners’ intention to adopt IoT. This knowledge equips them to formulate programs and strategies for promoting effective IoT implementation within the AEC field.

This study contributes to the existing literature by affirming antecedents and uncovering moderators in IoT adoption. It enhances the existing theoretical frameworks by integrating UTAUT2, TTF, and perceived risk, thereby making a substantial contribution to the advancement of technology adoption research in the AEC sector.

In recent years, augmented reality (AR) has shown its potential to assist various construction activities. Its use commonly requires additional refinement to be integrated into the building information modeling (BIM) process. Nevertheless, few studies have investigated AR implementation in BIM-enabled projects because of numerous challenges related to its implementation. This study aims to investigate the implementation of AR in construction and identify the critical mechanisms for implementing BIM-AR successfully.

A mixed methodology was adopted for this study. First, this work presents a bibliometric analysis covering articles obtained from Scopus database published between 2000 and 2022. A sample size of 65 research papers pertinent to AR in construction was analyzed using VOSviewer software. Second, a participatory case study was conducted for a BIM-enabled project in China to gain insight into how BIM-AR implementation in construction is achieved.

The findings from the bibliometric analysis show an increasing interest in AR research within construction. The results indicate that AR research focuses on four clusters: real-time communication, project management, construction activities and education. Findings from the case study provide an empirical experience of AR application scenarios in a BIM-enabled project. Concomitantly, 15 critical success factors that influence BIM-AR implementation were finally identified and demonstrated.

This study provides a rich insight into the understanding and awareness of implementing AR. First, the findings are beneficial to construction practitioners and researchers because they provide a concentrated perspective of AR for emerging activities in the construction industry. Second, the results obtained from the case study could provide a useful guide for effectively implementing AR in a BIM-enabled construction project. Overall, this study may stimulate further research on AR-related studies in construction, such as BIM integration, factor analysis and construction education.

The purpose of this study is to systematically identify, assess, and categorize the barriers to digital transformation (DT) in the engineering and construction sectors, and thus to better understand the impact and how these sectors might be overcome.

This study adopted a sequential mixed qualitative and quantitative data collection and analysis approach. DT barriers were first identified from relevant literature and verified by an expert panel. Then, a questionnaire survey assessing the impacts of the identified DT barriers was distributed to construction professionals in China, and 192 valid responses were retrieved. Further, the data obtained were analyzed using ranking analysis, exploratory factor analysis (EFA), and partial least squares-structural equation modeling (PLS-SEM).

Based on the ranking analysis, the top three barriers are “lack of industry-specific standards and laws,” “lack of clear vision, strategy and direction for DT,” and “lack of support from top management for DT.” EFA enabled the grouping of the 26 barriers into 3 categories: (1) lack of laws and regulations (LLR), (2) lack of support and leadership (LSL), and (3) lack of resources and professionals (LRP). The PLS-SEM analysis revealed that LLR, LSL, and LRP were found to have significant negative impacts on DT.

These findings contribute to the body of knowledge on DT in the construction industry and help construction firms and government bodies improve the understanding of these barriers to DT and put forward relevant policies and incentives, thus seizing the DT benefits as a way to enhance construction project management.

The purpose of this paper is to test the relationships between a hotel’s design quality and the property’s business performance.

Hotel guests’ assessments of the design quality of hotels that they recently visited are tested using the design quality indicator (DQI). Business performance is measured using indexed values for each property’s occupancy, average daily rate (ADR) and revenue per available room (RevPAR). The data are analyzed using exploratory factor analysis and a variation of a hedonic pricing model.

Factor analysis reduced the DQI instrument to 19 measurement items. Factors that measure navigability and signage positively impact occupancy index. Factors that measure flexible space usage negatively impact the RevPAR and ADR indices. Factors that reflect aesthetic constructs, including Urban & Social Integration and Character & Form, positively impact the RevPAR and ADR indices.

The study examines a nationwide sample of guests from two full-service brands of a single multi-brand hotel company. The study provides a parsimonious, validated design measurement instrument and a revised hedonic pricing analysis.

Hoteliers can use this technique to assist with resource allocation decisions. Aesthetic elements, including the building’s Urban & Social Integration with its surroundings and its Character & Form, lead to higher ADR and RevPAR performance. Managers should ensure a coherent layout and good signage program to drive occupancy.

This study offers a technique to measure design quality and a new method of performing a hedonic pricing analysis.

This study aims to focus on the effect of interlayer bonding and thermal decomposition on the mechanical properties of fused filament fabrication-printed polylactic acid specimens at high extrusion temperatures.

A printing process, that is simultaneous manufacturing of contour and specimen, is used to improve the printing accuracy at high extrusion temperatures. The effects of the extrusion temperature on the mechanical properties of the interlayer and intra-layer are evaluated via tensile experiments. In addition, the microstructure evolution affected by the extrusion temperature is observed using scanning electron microscopy.

The results show that the extrusion temperature can effectively improve the interlayer bonding property; however, the mechanical properties of the specimen for extrusion temperatures higher than 270°C may worsen owing to the thermal decomposition of the polylactic acid (PLA) material. The optimum extrusion temperature of PLA material in the three-dimensional (3D) printing process is recommended to be 250–270°C.

A temperature-compensated constitutive model for 3D printed PLA material under different extrusion temperatures is proposed. The present work facilitates the prediction of the mechanical properties of specimens at an extrusion temperature for different printing temperatures and different layers.

This paper studies the location-inventory problem (LIP) in pallet pooling systems to improve resource utilization and save logistics costs, which is a new extension of the classical LIP and also an application of the LIP in pallet pooling systems.

A mixed-integer linear programming is established, considering the location problem of pallet pooling centers (PPCs) with multi-level capacity, multi-period inventory management and bi-directional logistics. Owing to the computational complexity of the problem, a hybrid genetic algorithm (GA) is then proposed, where three local searching strategies are designed to improve the problem-solving efficiency. Lastly, numerical experiments are carried out to validate the feasibility of the established model and the efficiency of the proposed algorithm.

The results of numerical experiments show that (1) the proposed model can obtain the integrated optimal solution of the location problem and inventory management, which is better than the two-stage model and the model with single-level capacity; (2) the total cost and network structure are sensitive to the number of PPCs, the unit inventory cost, the proportion of repairable pallets and the fixed transportation cost and (3) the proposed hybrid GA shows good performance in terms of solution quality and computational time.

The established model extends the classical LIP by considering more practical factors, and the proposed algorithm provides support for solving large-scale problems. In addition, this study can also offer valuable decision support for managers in pallet pooling systems.

Library science and information science, two subdisciplines of library and information science (LIS), are developed independently but interconnectedly. In this information age, LIS is in a special period of transformation and development, which has caused some changes in both library science and information science. By accurately capturing these changes and analyzing them, the authors can effectively map the development of LIS in the new century, thus providing a reference for the evolution and development of the field. The purposes of this paper are to explore the mainstream research fields and frontiers of library science and information science, respectively, since the new century, and to make a comparative analysis of the two subdisciplines.

By using CiteSpace to visualize LIS journals, this study draws knowledge maps of the two subdisciplines of LIS through the co-occurrence descriptors network. Using burst detection algorithm, this study detects words of high frequency variation by investigating the time frequency distribution.

The results show that the research focus of library science has experienced a change from traditional to digital library while information science has moved from information to data focus. This study also finds the similarities and differences between mainstream areas of library science and information science.

This study focuses on the evolution of library science and information science, and explores their mainstream research fields and frontiers in the 21st century. These findings will promote the transformation and development of LIS as well as provide research directions for scholars in the field.

Along with the acceleration of Chinese urbanization, urban history degrades at a rapid rate, and development follows formalism. Based on architectural typology, this study introduces a methodology of concept mapping and discusses the urban complex design method from a perspective of regional cultural elements. The theoretical analysis shows that concept mapping represents an integrated solution that incorporates regional cultural elements into architectural planning. Through the concept mapping method, it not only protects the physical environment, but also strengthens modern urban residents’ psychological sense of belonging to their own living space. Meanwhile, distinct regional cultural elements can be efficiently combined in the overall layout, monomer building design, building details design, and landscape design of urban complex by using different architectural design methods. This design method is validated using an actual case in Guizhou. Therefore, it forms a complete set of design method with a three-step framework, namely positioning cultural areas, summarizing regional cultural elements, and selecting the mapping method and combination mode.