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Limited use of Internet of Things (IoT) technology on construction sites has restricted its value in the construction industry. To propel its widespread application, this paper explores the influencing factors and action paths of construction companies' IoT technology adoption behavior.

First, literature research, technology adoption theories, and semi-structured expert interviews were employed to build the adoption model. Second, a questionnaire survey was conducted among Chinese construction contractors to collect empirical data. Third, the structural equation model method and regression analysis were used to test the adoption model. Finally, the findings were further validated with interviews, case studies, and field observations.

External environmental pressure (EEP), perceived benefit (PB), top management support (TMS), company resource readiness (CRR), adoption intention (AI), and perceived compatibility (PCA) have a direct positive impact on adoption behavior (AB). In contrast, perceived cost (PC) and perceived complexity (PCL) exert a direct negative impact on AB. The EEP, PB, and PC are critical factors affecting AB, whereas AI is strongly affected by CRR and TMS. Besides, AI plays a part mediating role in the relationship between seven factors and AB. Company size and nature positively moderate AI's positive effect on AB.

This paper contributes to the knowledge of IoT technology adoption behavior in the construction sector by applying the technology adoption theories. Exploring the implementation barriers and drivers of IoT technology in construction sites from the perspective of organizational technology adoption behavior and introducing moderating variables to explain adoption behavior are innovations of this paper. The findings can help professionals better understand the IoT technology adoption barriers and enhance construction companies' adoption awareness, demand, and ability. This work also provides a reference for understanding the impact mechanism of the adoption behavior of other innovative technologies in construction.

Human–robot collaboration (HRC) is an emerging research field for the construction industry along with construction robot adoption, but its implementation remains limited in construction sites. This paper aims to identify critical risk factors and their interactions of HRC implementation during engineering project construction.

Literature research, expert interviews, a questionnaire survey and a social network analysis (SNA) method were used. First, literature research and expert interviews were employed to identify risk factors of HRC implementation and preliminarily understand factor interactions. Second, a questionnaire survey was conducted to determine the degree of interactions between risk factors. Third, based on the data collected from the questionnaire survey, SNA metrics were used to find critical risk factors and critical interactions.

The critical risk factors consist of robot technology reliability, robot-perceived level, conflict between designers and users of construction robots, organisational culture, organisational strength, project cost requirements, changeability of project construction, project quality requirements and project safety requirements. The interactions between risk factors are strong and complex. Robot technology risk factors were relatively fundamental risk factors, and project risk factors had a direct influence on the risk of HRC implementation. The implementation cost of HRC was not identified as a critical risk factor. Individual risk factors could be mitigated by improving technical and organisational factors.

This paper contributes to the body of knowledge in the field of both HRC behaviours and its risk management in construction project management. Identifying the critical risk factors and their interactions of HRC implementation in the construction industry and introducing social network theory to the research on critical risk factors are the innovations of this paper. The findings and proposed suggestions could help construction professionals to better understand the HRC risk factors and to manage the risk of HRC implementation more effectively.

The main purpose of this paper is to present a comprehensive upscale theory of the thermo-mechanical coupling particle simulation for three-dimensional (3D) large-scale non-isothermal problems, so that a small 3D length-scale particle model can exactly reproduce the same mechanical and thermal results with that of a large 3D length-scale one.

The objective is achieved by following the scaling methodology proposed by Feng and Owen (2014).

After four basic physical quantities and their similarity-ratios are chosen, the derived quantities and its similarity-ratios can be derived from its dimensions. As the proposed comprehensive 3D upscale theory contains five similarity criteria, it reveals the intrinsic relationship between the particle-simulation solution obtained from a small 3D length-scale (e.g. a laboratory length-scale) model and that obtained from a large 3D length-scale (e.g. a geological length-scale) one. The scale invariance of the 3D interaction law in the thermo-mechanical coupled particle model is examined. The proposed 3D upscale theory is tested through two typical examples. Finally, a practical application example of 3D transient heat flow in a solid with constant heat flux is given to illustrate the performance of the proposed 3D upscale theory in the thermo-mechanical coupling particle simulation of 3D large-scale non-isothermal problems. Both the benchmark tests and application example are provided to demonstrate the correctness and usefulness of the proposed 3D upscale theory for simulating 3D non-isothermal problems using the particle simulation method.

The paper provides some important theoretical guidance to modeling 3D large-scale non-isothermal problems at both the engineering length-scale (i.e. the meter-scale) and the geological length-scale (i.e. the kilometer-scale) using the particle simulation method directly.

The purpose of this study is to simultaneously investigate a comprehensive analysis of the extent to which strategic orientations, namely, imitation and innovation orientations, and knowledge management affect firm performance.

Drawing on the theoretical frameworks of the resource-based view and dynamic capability theory, this scholarly inquiry has proposed a comprehensive framework that delineates the relationships amongst imitation, innovation, absorptive capacity (ACAP), innovation performance and financial performance. To scrutinize the proposed research model, bootstrap routines were used through Smart partial least squares to estimate the procedures. To collect the necessary data, a questionnaire and financial statements were acquired from a sample of 100 Iranian firms listed on the Tehran Stock Exchange. The findings of the study have important implications for both scholars and practitioners seeking to enhance firm performance through the effective utilization of imitation, innovation and ACAP.

The results indicate that imitation activities have directly led to the improvement in innovation performance, even in the presence of innovation and ACAP. However, the relationship has not been confirmed by financial performance.

Imitation and innovation orientations have been identified as pivotal strategic orientations that can significantly affect firm performance. As far as the authors know, this investigation represents the first comprehensive examination of both imitation and innovation activities as a critical transition in emerging markets (EMs) characterized by complex economies, such as Iran. The findings may aid firms in enhancing their performance by providing insight into the strategic importance of imitation and innovation orientations in EMs.

This study aims to investigate the influence mechanism of brazing and aging on the strengthening and corrosion behavior of novel multilayer sheets (AA4045/AA7072/AA3003M/AA4045).

Polarization curve tests, immersion experiments and transmission electron microscopy analysis were used to study the corrosion behavior and tensile properties of the sheets before and after brazing and aging.

The strength of the sheet is weakened after brazing due to brittle eutectic phases, and recovered after aging due to enhanced precipitation strengthening in the AA7072 interlayer. The core of nonbrazed sheets cannot be protected due to the significant galvanic coupling effect between the intermetallic particles and the substrate. Brazing and aging treatments promote the redissolved of second phased and limit corrosion along the eutectic region in the clad, allowing the core to be protected.

AA7xxx alloy was added to conventional brazed sheets to form a novel Al alloy composite sheet with AA4xxx/AA7xxx/AA3xxx structure. The strengthening and corrosion mechanism of the sheet was proposed. The added interlayer can sacrificially protect the core from corrosion and improves strength after aging treatment.

The purpose of this study is to investigate how artificial intelligence (AI), as well as machine learning (ML) techniques, are being applied and implemented within supply chains (SC) and to develop future research directions from thereof.

Using a systematic literature review methodology, this study analyzes the publications available on Web of Science, Scopus and Google Scholar that linked both AI and supply chain from one side and ML and supply chain from another side. A total of 388 research studies have been identified through the before said three database searches which are further screened, sorted and finalized with 50 studies. The research thoroughly reviews and analyzes the final lists of 50 studies that were found relevant and significant to the theme of AI and ML in supply chain management (SCM).

AI and ML applications are still at the infant stage and the opportunity for them to elevate supply chain performance is very promising. Some researchers developed AI and ML-related models which were tested and proved to be effective in optimizing SC, and therefore, the application of AI and ML in supply chain networks creates competitive advantages for firms. Other researchers claim that AI and ML are both currently adding value while many other researchers believe that they are still not fully exploited and their tools and techniques can leverage the supply chain’s total value. The research found that adoption of AI and ML have the ability to reduce the bullwhip effect, and therefore, further supports the performance of supply chain efficiency and responsiveness.

This research was limited in terms of scope as it covered AI and ML applications in the supply chain while there are other dimensions that could be investigated such as big data and robotics but it was found too lengthy to include these additional dimensions, and therefore, left for future research studies that other researchers could explore and pursue.

This study opens the door wide for other researchers to explore how AI and ML can be adopted in SCM and what are the models that are already tested and proven to be viable. In addition, the paper also identified a group of research studies that confirmed the unexploited avenues of AI and ML which could be of high interest to other researchers to explore.

Although few earlier research studies touch based on the AI applications within manufacturing and transportation, this study is different and makes a unique contribution by offering a holistic view on the AI and ML implications within SC as a whole. The research carefully reviews a number of highly cited papers classifying them into three main themes and recommends future direction.

This paper aims to investigate the stress corrosion cracking (SCC) process of sensitized 304 stainless steel during the slow strain rate test by using the electrochemical noise (EN) technique.

EN data are interpreted based on chaos and wavelet analyses, and correlation dimension and wavelet energy distribution are used as indicators for SCC process identification.

Experimental results reveal that the corrosion potential abruptly decreases from 180 to 100 mV at 6,300 s and the current increases from 10 to 100 nA accordingly, which is attributed to passive film breakdown and crack initiation. Chaos and wavelet analyses results reveal that, as crack initiates, the correlation dimensions increase from 1.2 to 1.9, and the corresponding distribution frequencies of maximum relative wavelet energy change from high frequency to low frequency.

SCC is monitored in lab, and crack initiation and propagation are identified by chaos and wavelet analyses. This work lays the foundation for SCC detection in field using EN.

With the increasingly intensifying competition and the development and maturity of the modern organization, employees have no longer fully been attached to the organization. The employee‐organization relationship gets more and more attention. As spokespersons of their organizations, the leaders in all levels, to a considerable extent, have an effect on the understanding of the employee for the organization. The purpose of this paper is to explore leader and member exchange (LMX) relationships' impact on employees' organizational commitment and discuss the mediating effect of perceived organizational support (POS) during the period.

A sample consisting of 423 employees in four organizations was investigated. After testing the reliability of all questionnaires, the authors constructed a model of the mediating effect of POS between LMX relationships' impact on employees' organizational commitment and used structural equation model technology to verify it.

The results showed that: affect, loyalty and professional respect have a significant impact on affective commitment but the result of the contribution is not significant. So, work exchange (contribution) was different from social exchange (affect, loyalty and professional respect) in the influence on employee's organizational affective commitment. POS had an intermediary effect between the affect exchange and affective commitment in the organization. Leader‐membership has an important implication for the employee‐organization relationship. The exchanges of different dimensions between the leader and the member were different no matter for the affected contents of the attitude to the organization of the employee or for the affecting mechanism.

All variable data came from the same employee questionnaires, which may lead to potential problems of same source bias or common method variance. In order to test the influence of common method variance, this research carried out Harman's one‐factor test.

The organization should emphasize developing the relationship between the leaders from various levels and the members, and in particular the social exchange out of the work must not be neglected.

The present study explores LMX's influence on employees' affective commitment towards the organization from a social exchange perspective. The authors adopted multi‐dimensions LMX, which is different from prior studies (e.g. Wayne et al. and Zhou and Bao) to discuss the mechanism of LMX's impact on subordinates' attitudes to the organization.

Attitudes and beliefs towards marriage and family held by Chinese and American college students were compared in this study. The primary dimensions included whether to marry, age to marry, number of desired children, age to have children, perceptions of divorce, willingness to cohabit, openness to blended marriages, and gender roles within marriage. If a global convergence of cultures is occurring, then similarities should be found throughout the views of all respondents towards the institution of marriage. Dissimilarities in views could be interpreted as evidence of the entrenchment and uniqueness of culture, an outcome advanced by those who question cultural homogenisation. Hundreds of college students in several large universities in China and one regional university in the United States were surveyed at convenience. The Chinese students were found to prefer marrying and to plan having children a year later in age compared to the Americans. They also desired having nearly one fewer total number of children on average compared to the Americans. Surprisingly, the Chinese were more agreeable with divorce. The Americans were more likely to support gender equality within marriage and to accept blended types of marriage. Both groups equally approved of the overall idea of couples cohabiting if they plan on marrying. However, the Americans were far more willing to say that they themselves would cohabit. Visions of the benefits of married life were similar across countries. Overall, far more significant differences were found than no differences. The results suggest that elements of marriage norms in the world’s largest economies are somewhat constrained by social forces in their ability to completely converge.

Considering its vast utility in industries, this paper aims to present a detailed review on fundamentals, classification and progresses in pressure sensors, along with its wide area of applications, its design aspects and challenges, to provide state-of-the-art gist to the researchers of the similar domain at one place.

Swiftly emerging research prospects in the micro-electro-mechanical system (MEMS) enable to build complex and sophisticated micro-structures on a substrate containing moving masses, cantilevers, flexures, levers, linkages, dampers, gears, detectors, actuators and many more on a single chip. One of the MEMS initial products that emerged into the micro-system technology is MEMS pressure sensor. Because of their high performance, low cost and compact in size, these sensors are extensively being adopted in numerous applications, namely, aerospace, automobile and bio-medical domain, etc. These application requirements drive and impose tremendous conditions on sensor design to overcome the tedious design and fabrication procedure before its reality. MEMS-based pressure sensors enable a wide range of pressure measurement as per the application requirements.

The paper provides a detailed review on fundamentals, classification and progresses in pressure sensors, along with its wide area of applications, its design aspects and challenges, to provide state of the art gist to the researchers of the similar domain at one place.

The present paper discusses the basics of MEMS pressure sensors, their working principles, different design aspects, classification, type of sensing diaphragm used and illustration of various transduction mechanisms. Moreover, this paper presents a comprehensive review on present trend of research on MEMS-based pressure sensors, its applications and the research gap observed till date along with the scope for future work, which has not been discussed in earlier reviews.