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Modular integrated construction (MiC) reengineers the traditional construction process. By introducing factory production and onsite assembly (OA) of modules, MiC reinvents construction projects' uncertainties and risk profiles. The OA stage constitutes the highest end of the MiC delivery and supply chains, where several inherited and symbiotic errors and risk events become realities, negatively impacting the MiC project's success. This study explored the severities of OA risk factors for MiC projects.

A comprehensive literature review, consultation of experts and a questionnaire survey of domain experts were conducted to assess the severity of fifteen OA risk factors for MiC projects. The risk severity index was used to compute and rank the severities of critical OA risk factors for MiC projects, followed by proposed mitigation strategies.

The study revealed that the top five OA risk factors with the severest impact on MiC projects include modules installation discrepancies and errors, poor cooperation among critical onsite stakeholders, a mismatch between production schedules and site conditions, improper lifting equipment selection for onsite installation and site-fit rework due to discrepancies in drawings.

This study is the first to offer some important insights into the uncertainties that could compromise the OA objectives of MiC projects. It discussed risk management strategies for known and unknown OA risks and made a unique contribution to the theory, practice, and praxis of MiC supply chain risk management.

This study proposes an approach to solve the fundamental problem in using query-based methods (i.e. searching engines and patent retrieval tools) to screen patents of information and communication technology in construction (ICTC). The fundamental problem is that ICTC incorporates various techniques and thus cannot be simply represented by man-made queries. To investigate this concern, this study develops a binary classifier by utilizing deep learning and NLP techniques to automatically identify whether a patent is relevant to ICTC, thus accurately screening a corpus of ICTC patents.

This study employs NLP techniques to convert the textual data of patents into numerical vectors. Then, a supervised deep learning model is developed to learn the relations between the input vectors and outputs.

The validation results indicate that (1) the proposed approach has a better performance in screening ICTC patents than traditional machine learning methods; (2) besides the United States Patent and Trademark Office (USPTO) that provides structured and well-written patents, the approach could also accurately screen patents form Derwent Innovations Index (DIX), in which patents are written in different genres.

This study contributes a specific collection for ICTC patents, which is not provided by the patent offices.

The proposed approach contributes an alternative manner in gathering a corpus of patents for domains like ICTC that neither exists as a searchable classification in patent offices, nor is accurately represented by man-made queries.

A deep learning model with two layers of neurons is developed to learn the non-linear relations between the input features and outputs providing better performance than traditional machine learning models. This study uses advanced NLP techniques lemmatization and part-of-speech POS to process textual data of ICTC patents. This study contributes specific collection for ICTC patents which is not provided by the patent offices.

This paper aims to investigate the relationship between earnings management and media reports, assess the roles played by the media in determining the reputation mechanism and examine whether the media has an influence on executives’ behavior in the case of earnings management.

This paper uses Chinese A-share listed firms from the period 2008 to 2012 to test the research questions using regression analyses.

Although the Chinese Stock Markets are still immature compared to those of developed countries, the media seems to play a role in affecting executives’ decisions about dabbling in earnings management. Specifically, firms receiving more media attention are more likely to undertake earnings management. Furthermore, negative media reports result in even higher levels of earnings management activities, indicating that managers tend to use earnings management to achieve earnings goals to reduce or relieve the pressure they feel from the media and to remedy any reputation loss. Moreover, the authors have found that firms whose CEOs have higher reputations are more likely to manage earnings and they are more likely to be affected by negative media reports. Similar results were found for state-owned enterprises (SOEs).

This study analyzes how the level and tone of media coverage affect earnings management rather than just assessing the overall effect of media coverage on earnings management. This paper verifies that the reputation mechanism of the media works in China, but it leads to different results than those experienced in developed countries. Reputational benefits have been introduced into the equation for measuring the governance effect of the media to derive a more in-depth analysis of the reputation mechanism. This paper is among the first to link news coverage and state ownership with earnings management.

Proper assessment of contractors' competitiveness is important for assisting contractors in taking internal analysis and for assisting clients in selecting suitable contractors. This paper seeks to address this issue.

With previously identified contractor key competitiveness indicators (KCIs), this study presents a fuzzy competitiveness rating (FCR) method for measuring contractor competitiveness with reference to the Hong Kong construction industry. A set of linguistic terms is used for facilitating the assessment process.

For illustration, an example is used to show the application of the FCR method. The results provide valuable information for helping contractors in the local construction industry to understand their competitive advantages and weaknesses, and to formulate effective competition strategies to improve their competitiveness.

The model used in this study is not validated by real cases. In a future paper, the model will be further demonstrated by conducting real case studies, and the linguistic terms and corresponding fuzzy numbers will also be re‐defined based on the collected data.

As the competitiveness assessment process involves complexity and uncertainty, a fuzzy competitiveness rating method is considered suitable for reflecting the reality and the assessment panel can easily give their opinions by using the linguistic language.

This paper aims to discuss the key factors affecting the quality characteristics, such as the number of solder balls, the spread distance of residual underfill and the completion time of the underfilling.

The Taguchi method is applied to configure the orthogonal table and schedule and execute the experiment. In addition, principal components analysis is used to obtain the points. Then, based on gray relational analysis and the technique for order preference by similarity to ideal solution, the closeness between each quality characteristic and the ideal solution is adopted as the basis for evaluating the quality characteristics.

The optimal parameter combination is proposed, which includes 4 dispensing (11 mg/dispensing), a “half flow” interval state, 80°C preheating module PCB board and an L-shaped dispensing path and verification testing is performed.

For vehicles and handheld electronic products, solder joints that connect electronic components to printed circuit boards may be cracked due to collision, vibration or falling. Consequently, solder balls are closely surrounded and protected by the underfill to improve joint strength and resist external force factors, such as collision and vibration. This paper addresses the defects caused during the second reflow process of a vehicle electronic communication module after the underfilling process.

As a strand in industrialization movement in architecture, engineering and construction (AEC) industry, prefabricated construction (PC) has gained widespread popularity due to high efficiency, energy saving, low environmental impacts, safety and other advantages of PC. Well-managed supply chain can further leverage the advantages of PC. However, there is a lack of more systematically overview of the prefabricated construction supply chain (PCSC). This paper aims to comb the current status and look into the future direction of PCSC by reviewing the existing research.

In total, 131 articles related to prefabricated construction supply chain management (PCSCM) from 2000 to 2022 have been collated to (1) conduct a bibliometric analysis by using VOSviewer, including the literature sources, keywords co-occurrence, co-authorships, authorship citation and country active in the field of PCSCM; (2) classify and summarize the status of research in PCSCM through qualitative discussion and (3) point out the future research directions.

In total, 131 articles are carried out for bibliometric analysis and in-depth qualitative discussion, the visualization maps and the main research themes in the field of PCSCM are obtained. The results show that supply chain intelligentization and informatization are hot topics. Finally, future research directions that should be paid attention to in the field of PCSCM are pointed out.

This study can help project managers understand the current status and problems of PCSC operations and provide a basis for future management decisions.

Compared with previous studies, this study adds the dimension of “article authorship” to the quantitative analysis and discusses the research themes in the field of PCSCM in a comprehensive manner. In addition, this paper deeply discusses the main research topics from both the specific contents and research methods adopted.

Human group behavior is the driving force behind many complex social and economic phenomena. Few studies have integrated multi-dimensional travel patterns and city interest points to construct urban security risk indicators. This paper combines traffic data and urban alarm data to analyze the safe travel characteristics of the urban population. The research results are helpful to explore the diversity of human group behavior, grasp the temporal and spatial laws and reveal regional security risks. It provides a reference for optimizing resource deployment and group intelligence analysis in emergency management.

Based on the dynamics index of group behavior, this paper mines the data of large shared bikes and ride-hailing in a big city of China. We integrate the urban interest points and travel dynamic characteristics, construct the urban traffic safety index based on alarm behavior and further calculate the urban safety index.

This study found significant differences in the travel power index among ride-sharing users. There is a positive correlation between user shared bike trips and the power-law bimodal phenomenon in the logarithmic coordinate system. It is closely related to the urban public security index.

Based on group-shared dynamic index integrated alarm, we innovatively constructed an urban public safety index and analyzed the correlation of travel alarm behavior. The research results fully reveal the internal mechanism of the group behavior safety index and provide a valuable supplement for the police intelligence analysis.

The factory production stage constitutes the bridge in the supply chains of modular integrated construction (MiC) projects. It embodies the fundamental differences between MiC and site-based construction. However, there is a poverty of knowledge of the uncertainties and risk events at the production stage. This study aims to investigate the critical production risk factors (PRFs) for MiC projects.

Comprehensive literature research and expert review identified and validated 22 candidate PRFs for MiC projects. A structured questionnaire survey was then used to gather opinions of domain experts in 18 countries on the relative impact of the validated PRFs for MiC projects. The collected data were analysed using multiple statistical techniques.

Statistical analysis identified nine critical PRFs for MiC projects. The top five include dimensional conflicts between modules during production; delays in production materials procurement; defective design; design information gap between designer and manufacturer; and limited capacity of manufacturers.

The study addressed the gap associated with identifying critical risk factors peculiar to the factory production stage of MiC projects. Its novelty lies in providing an opposite assessment of severities and prioritization of critical PRFs for MiC projects. The prioritized critical PRFs for MiC projects may inform resource allocation. Thus, it provides valuable information to MiC production specialists and project managers in their production risk planning and management strategies. The identified PRFs contribute to the theoretical checklist of MiC supply chain risk factors and may assist practitioners in assessing the severity levels of the PRFs of their MiC projects.

The purpose of this paper is to investigate the heat and mass transport characteristics in microchannel reactors with non-uniform catalyst distributions.

A two-dimensional model is developed to study the heat and mass transport characteristics in microchannel reactors. The heat and mass transport processes in the microchannel reactors with non-uniform catalyst distribution in the catalytic combustion channel are also studied.

The simulated results are compared in terms of the distributions of species mole fraction, temperature and reaction rate for the conventional and new designed reactors. It is found that the chemical reaction, heat and mass transport processes are significantly affected and the maximum temperature in the reactor is also greatly reduced when a non-uniform catalyst distribution is applied in the combustion catalyst layer.

This study can improve the understanding of the transportation characteristics in microchannel reactors with non-uniform catalyst distributions and provide guidance for the design of microchannel reactors.

The design of microchannel reactors with non-uniform catalyst distributions can be used in methane steam reforming to reduce the maximum temperature inside the reactor.