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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 introduce error ellipse into the bootstrap method to improve the reliability of small samples and the credibility of the S-N curve.

Based on the bootstrap method and the reliability of the original samples, two error ellipse models are proposed. The error ellipse model reasonably predicts that the discrete law of expanded virtual samples obeys two-dimensional normal distribution.

By comparing parameters obtained by the bootstrap method, improved bootstrap method (normal distribution) and error ellipse methods, it is found that the error ellipse method achieves the expansion of sampling range and shortens the confidence interval, which improves the accuracy of the estimation of parameters with small samples. Through case analysis, it is proved that the tangent error ellipse method is feasible, and the series of S-N curves is reasonable by the tangent error ellipse method.

The error ellipse methods can lay a technical foundation for life prediction of products and have a progressive significance for the quality evaluation of products.

The device, amplifies and sub-regionally transmits the current generated by the body temperature thermoelectric generator through a smart body temperature sensor.

The present study designs a wearable smart device regarding the relationship between temperature and emotion.

Experimental results show that the device can accurately detect changes in human body temperature under hilarious, fearful, soothing and angry emotions, so as to achieve changes in clothing colors, namely blue, red, green and brown.

Different areas of clothing produce controllable and intelligent color, so that adult emotions can be understood through changes in clothing colors, which is conducive to judging their moods and promoting social interaction.

The purpose of this study is to apply the triangle model of technology and the technology readiness index (TRI) in a qualitative study design to explore the geocaching phenomenon in state parks.

A framework was developed to examine the triangular relationships between the park, geocaching and visitors. A total of 12 semi-structured interviews were conducted with Texas state park officials. A thematic analysis was used to analyze the interview data.

Three types of interactions (i.e. park-visitor, visitor-technology and park-technology) were identified. Although geocaching leads to positive recreational experiences for park visitors, the study also revealed the decreasing popularity of geocaching along with park officials’ apprehension regarding the placement of caches. The findings suggest that Texas state parks fall within the “Avoiders” stage in terms of technology readiness because of a low level of optimism and innovation and a high level of discomfort and insecurity toward geocaching technology.

The study contributes to the extant literature by adding new knowledge regarding geocaching in the context of state parks. This study is one of the first to apply the triangle model of technology to examine the trilateral relationships between parks, geocaching and visitors. The study also innovatively adopts the TRI in a qualitative study to identify the technology readiness stage of state parks.

本研究旨在运用科技三角模型以及科技准备度指数（TRI）以定性研究为方法来探索地理藏宝这一现象。

本研究为探索公园, 地理藏宝以及访客的三角结构关系提出了理论框架。研究对德克萨斯州立公园行政人员进行了12项半结构化访谈。主题分析发进行了访谈数据分析。

研究发现了三种形式的互动：公园访客, 访客科技装备, 和公园的科技装备。尽管地理藏宝活动提高了公园访客的体验, 本研究通过公园人员的视角也发现访客的热情有所降低。研究结果发现德州州立公园在科技准备度意义来说仍处于“回避”阶段, 基于较低的积极度和创新意识, 以及对地理藏宝活动表现较高的不适以及不安。

本研究为已有的文献增添了有关州立公园地理藏宝的新发现。本研究是首次运用科技三角模型来研究公园, 地理藏宝和访客之间的三边关系。本论文也创新性的在定性研究中运用了TRI对州立公园科技准备度进行研究。