Search results

The purpose of this paper is to address the urgent need for transformation and upgrading in the construction industry amid the accelerating industrialization process. The focus is on understanding how value-added for construction enterprises can be achieved through servitization.

Grounded in the perspective of added value of construction enterprises, this paper uses a multicase analysis method, selecting four internationally renowned construction enterprises as the research subjects. The analysis investigates how these case study enterprises transition toward servitization and explores the trends in servitization in construction.

The research results indicate that servitization manifests in two aspects: contractor transition to servitization, and the shift of the construction industry toward integrated delivery. Furthermore, servitization in construction can achieve value-adding through three pathways: increasing product value, creating market demand and providing customized services.

This study contributes by providing insights into the manifestations of servitization and pathways for value-added. It provides a reference for the overall direction and basic strategy of servitization in construction.

Project-based temporary organizations, as an efficient organizational form for the execution of complex and innovative tasks, encounter challenges in fostering the effectiveness of inter-organizational cooperation within their temporary, uncertain, and dynamic nature. Although change-oriented organizational citizenship behaviors are recognized for promoting organizational relationships and performance in changing contexts, research in temporary organizational settings remains sparse. This study diverges from the majority concentrating on change-oriented behaviors on intra-organizational leader-employee relations and behaviors, aiming to propose a dynamic adaptive capacity of organizational leaders and explore how leadership capabilities and organizational climate shape their change-oriented organizational citizenship behaviors at inter-organizational level.

Developing a person-organization fit model tailored for complex and dynamic organizational settings, using survey data from 225 leaders with project cooperative experience and structural equation modeling for empirical analysis.

This study reveals the direct positive influences of organizational leaders’ dynamic adaptive capacity on their changed-oriented organizational citizenship behaviors. And, change self-efficacy, as a mediating psychological trait, enhances the positive relation between dynamic adaptive capacity and changed-oriented organizational citizenship behaviors. The findings also highlight person-organization interactions, where organizational justice, acting as a situational and moderating factor, has a positive yet disruptive effect on the relationship between dynamic adaptive capacity, change self-efficacy, and changed-oriented organizational citizenship behaviors.

This research enriches the mechanisms linking dynamic managerial capability in organizational leadership to citizenship behaviors at the micro-level, providing valuable insights for the management and development of temporary cross-organizational cooperation.

This study investigates two internationalization strategies, foreign direct investment (FDI) expansion and export expansion, and their effects on the innovation performance of Chinese multinational enterprises (MNEs). Additionally, it explores the moderating roles of both formal and informal political connections in the relationship between these internationalization strategies and innovation performance.

The hypotheses were tested using the Poisson panel model and data on 2,106 observations from 645 Chinese-listed firms between 2010 and 2017.

FDI expansion significantly enhances the innovation performance of Chinese MNEs compared to export expansion. Moreover, formal and informal political connections are found to have distinct moderating effects: formal political connections amplify the positive effect of FDI expansion on firm innovation, whereas informal political connections tend to weaken it.

This study contributes to the discourse on innovation and political connections, especially in the context of EMNEs. It enriches the theoretical understanding of internationalization strategies and innovation performance in EMEs, contrasting with the technology-utilization motives observed in MNEs from developed economies.

Learning from safety accidents and sharing safety knowledge has become an important part of accident prevention and improving construction safety management. Considering the difficulty of reusing unstructured data in the construction industry, the knowledge in it is difficult to be used directly for safety analysis. The purpose of this paper is to explore the construction of construction safety knowledge representation model and safety accident graph through deep learning methods, extract construction safety knowledge entities through BERT-BiLSTM-CRF model and propose a data management model of data–knowledge–services.

The ontology model of knowledge representation of construction safety accidents is constructed by integrating entity relation and logic evolution. Then, the database of safety incidents in the architecture, engineering and construction (AEC) industry is established based on the collected construction safety incident reports and related dispute cases. The construction method of construction safety accident knowledge graph is studied, and the precision of BERT-BiLSTM-CRF algorithm in information extraction is verified through comparative experiments. Finally, a safety accident report is used as an example to construct the AEC domain construction safety accident knowledge graph (AEC-KG), which provides visual query knowledge service and verifies the operability of knowledge management.

The experimental results show that the combined BERT-BiLSTM-CRF algorithm has a precision of 84.52%, a recall of 92.35%, and an F1 value of 88.26% in named entity recognition from the AEC domain database. The construction safety knowledge representation model and safety incident knowledge graph realize knowledge visualization.

The proposed framework provides a new knowledge management approach to improve the safety management of practitioners and also enriches the application scenarios of knowledge graph. On the one hand, it innovatively proposes a data application method and knowledge management method of safety accident report that integrates entity relationship and matter evolution logic. On the other hand, the legal adjudication dimension is innovatively added to the knowledge graph in the construction safety field as the basis for the postincident disposal measures of safety accidents, which provides reference for safety managers' decision-making in all aspects.

This study aims to investigate the effect of galvanic corrosion on the sulfide stress corrosion cracking (SSCC) of X80/Inconel 625 weld overlay by altering the cathode/anode area ratios, Na₂S₂O₃ concentrations and temperatures.

The effects of galvanic corrosion on X80/Inconel 625 weld overlay SSCC were investigated by immersion test, galvanic corrosion current test, electrochemical measurement, four-point bending experiment, hydrogen permeation experiment and scanning electron microscopy.

The anodic dissolution of the fusion boundary was enhanced as the cathode/anode area ratio increased, which is necessary for the SSCC of the X80/Inconel 625 weld overlay. However, severe galvanic corrosion reduced the SSCC susceptibility. The SSCC susceptibility showed a linear increase with Na₂S₂O₃ concentration in the range of 10⁻⁴ ∼ 10⁻² mol/L. However, further increasing the Na₂S₂O₃ concentration to 10⁻¹ mol/L resulted in the disappearance of SSCC. This is likely because sufficient hydrogen was required for SSCC initiation even under severe anodic dissolution conditions, which was further supported by the reduced SSCC susceptivity at elevated temperatures.

Limited studies aim to establish the relationship between the galvanic corrosion and SSCC of welded joints through altering the cathode/anode area ratios, Na₂S₂O₃ concentrations and temperatures. This work will pave the way for understanding the effect of galvanic corrosion on the SSCC of dissimilar weld joints.

The COVID-19 pandemic has compelled higher educational institutions to implement alternative educational strategies that rely heavily on internet accessibility and utilisation to monitor and evaluate students. This study aims to find certain indicators for planning and designing future courses of inclusive online education in the domain of disaster risk reduction (DRR).

The study reviews and analyses online teaching and learning experiences of DRR courses. It uses online surveys and interviews to derive the perspectives of selected students and educators in universities in Asia and the Pacific region.

Active engagement is considered to be achieved when students are active in chat boxes, through presentations, through assignments and when the video cameras of students are turned on. On the contrary, students perceive active engagement differently because they face emotional disturbances and health issues due to prolonged screen/digital device use, have inadequate information and communications technology infrastructure or have digital literacy deficiencies among others. The study finds that online courses have many sets of strengths, weaknesses, opportunities and threats, when they are balanced, they can improve DRR courses in the future.

The study is based on the outcome of interviews with 10 experienced educators in DRR courses as well as students from different schools taking courses in DRR education. However, the students are not necessarily taking the courses of the educators interviewed due to the inability of some educators to avail themselves and the challenge of contacting the students. This notwithstanding, the results of this study give a general overview of the situation to be considered in the planning and design of online and distance education.

The results do not reflect the reaction of students and tutors of the same course. Future studies of collecting and analyzing the responses from the students and the educators with the same course could provide tailored solutions.

This study attempts to find solutions to bridging two different perspectives on teaching and learning. The results would be important to strengthening and designing future online courses.

Damage of engineering structures is a nonlinear evolutionary process that spans across both material and structural levels, from mesoscale to macroscale. This paper aims to provide a comprehensive review of damage analysis methods at both the material and structural levels.

This study provides an overview of multiscale damage analysis of engineering structures, including its definition and significance. Current status of damage analysis at both material and structural levels is investigated, by reviewing damage models and prediction methods from single-scale to multiscale perspectives. The discussion of prediction methods includes both model-based simulation approaches and data-driven techniques, emphasizing their roles and applications. Finally, summarize the main findings and discuss potential future research directions in this field.

In the material level, damage research primarily focuses on the degradation of material properties at the macroscale using continuum damage mechanics (CDM). In contrast, at the mesoscale, damage research involves analyzing material behavior in the meso-structural domain, focusing on defects like microcracks and void growth. In structural-level damage analysis, the macroscale is typically divided into component and structural scales. The component scale examines damage progression in individual structural elements, such as beams and columns, often using detailed finite element or mesoscale models. The structural scale evaluates the global behavior of the entire structure, typically using simplified models like beam or shell elements.

To achieve realistic simulations, it is essential to include as many mesoscale details as possible. However, this results in significant computational demands. To balance accuracy and efficiency, multiscale methods are employed. These methods are categorized into hierarchical approaches, where different scales are processed sequentially, and concurrent approaches, where multiple scales are solved simultaneously to capture complex interactions across scales.

It is a complex and dynamic process to provide high-quality rural infrastructure. However, there lacks a holistic performance evaluation method for rural infrastructure provision that reflects changing rural social needs and takes a village as a whole. This study aims to develop a holistic and dynamic performance evaluation model for rural infrastructure in Mainland China.

This study established an evaluation index system by combining the lifecycle theory and the economy, efficiency, effectiveness and equity (4E) theory. This study developed an evaluation model by using the analytic network process (ANP) and matter-element analysis theory (MEAT). The model was validated by two representative villages in Mainland China.

The developed model can reflect dynamic social needs and effectively evaluate the overall infrastructure provision performance of a village. The weight of indicators reflects the changes in Mainland China’s contemporary rural social needs, with particular emphasis on the impact and output performance. The evaluation result shows that the overall performance of the representative villages was excellent but had a tendency toward good. Although the output performance was excellent, different input, process and impact performances resulted in different downgrade trends.

This study provides a theoretical basis for disaggregating the complex issue of the performance of rural infrastructure provision. The results can be used by relevant authorities to make a holistic and dynamic evaluation of the performance of rural infrastructure provision and timely revise planning and management policies.

This paper aims to find a suitable solution to degrade the C.I. Reactive Red 24 (RR24) dyeing wastewater by using sodium persulphate to recycle water and inorganic salts.

The effects of temperature, the concentration of inorganic salts and Na₂CO₃ and the initial pH value on the degradation of RR24 were studied. Furthermore, the relationship between free radicals and RR24 degradation effect was investigated. Microscopic routes and mechanisms of dye degradation were further confirmed by testing the degradation karyoplasmic ratio of the product. The feasibility of the one-bath cyclic dyeing in the recycled dyeing wastewater was confirmed through the properties of dye utilization and color parameters.

The appropriate conditions were 0.3 g/L of sodium persulphate and treatment at 95°C for 30 min, which resulted in a decolorization rate of 98.4% for the dyeing wastewater. Acidic conditions are conducive to rapid degradation of dyes, while ·OH or SO₄⁻· have a destructive effect on dyes under alkaline conditions. In the early stage of degradation, ·OH played a major role in the degradation of dyes. For sustainable cyclic dyeing of RR24, inorganic salts were reused in this dyeing process and dye uptake increased with the times of cycles. After the fixation, some Na₂CO₃ may be converted to other salts, thereby increasing the dye uptake in subsequent cyclic staining. However, it has little impact on the dye exhaustion rate and color parameters of dyed fabrics.

The recommended technology not only reduces the quantity of dyeing wastewater but also enables the recycling of inorganic salts and water, which meets the requirements of sustainable development and clean production.

Building a smart city is a necessary path to achieve sustainable urban development. Smart city public–private partnership (PPP) project is a necessary measure to build a smart city. Since there are many participants in smart city PPP projects, there are problems such as uneven distribution of risks; therefore, in order to ensure the normal construction and operation of the project, the reasonable sharing of risks among the participants becomes an urgent problem to be solved. In order to make each participant clearly understand the risk sharing of smart city PPP projects, this paper aims to establish a scientific and practical risk sharing model.

This paper uses the literature review method and the Delphi method to construct a risk index system for smart city PPP projects and then calculates the objective and subjective weights of each risk index through the Entropy Weight (EW) and G1 methods, respectively, and uses the combined assignment method to find the comprehensive weights. Considering the nature of the risk sharing problem, this paper constructs a risk sharing model for smart city PPP projects by initially sharing the risks of smart city PPP projects through Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) to determine the independently borne risks and the jointly borne risks and then determines the sharing ratio of the jointly borne risks based on utility theory.

Finally, this paper verifies the applicability and feasibility of the risk-sharing model through empirical analysis, using the smart city of Suzhou Industrial Park as a research case. It is hoped that this study can provide a useful reference for the risk sharing of PPP projects in smart cities.

In this paper, the authors calculate the portfolio assignment by EW-G1 and construct a risk-sharing model by TOPSIS-Utility Theory (UT), which is applied for the first time in the study of risk sharing in smart cities.