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The purpose of this paper is to explore the formation mechanism of the host country people's coping behavior regarding the construction of transnational railways to help engineering managers and decision makers improve their risk management and lead to sustainable transnational railway construction projects.

This paper adopted the grounded theory methodology to analyze the news stories reported by “Belt and Road Portal” and “The New York Times” about eight transnational railways. They were China–Kyrgyzstan–Uzbekistan (Central Asia), Mecca-to-Medina (West Asia), Hungarian–Serbia (Europe), China–Nepal (South Asia), Bi-Oceanic (South America), Mombasa–Nairobi (Africa), China–Laos (Southeast Asia) and Panama railways (North America). The keywords for news search were the names of each railway. After eliminating the problem sentences with semantic repetition and ambiguity, 2,631 effective sentences were formed to screen the information and code. The process included open, axial and selective coding.

It was concluded that the core structure of the formation mechanism was “situation,” “influence factor,” “cognition” and “coping behavior.” The country-of-origin image has served as an adjustment function in the analysis for the host country people. Governance strategies were suggested focusing on risk prevention, risk mitigation and risk response according to social risk management.

The rise of transnational railway construction is encouraged by the process of globalization. But during the long construction period, the host country people's coping behavior would develop into social conflicts and mass incidents, becoming a significant obstacle to construction objectives. Thus, studying the formation mechanism of public coping behaviors can better take measures to prevent social risks.

The contributions of this research are three aspects: first, a formation mechanism of the host country people's coping behavior based on grounded theory is presented. Second, the country-of-origin image is found to be a factor that cannot be ignored in a transnational context. The formation mechanism of public coping behaviors is improved compared to risk management in the domestic situation. Finally, the host country people pay more attention to the motivations of country-of-origin's controlling interests and their own emotions compared with internal stakeholders.

Social risk management has recently come to the fore as a significant feature of project management. This prominence is particularly evident in urban construction projects that take place in cultural heritage and tourism historic sites. Accordingly, this study aims to adopt social network analysis (SNA) to investigate social risks in construction projects occurring in urban districts rife with historically and culturally significant tourism sites.

The present study analyzed a real case study in Iran as an emergent economy and a developing country. Primarily, the study reviewed previous literature on social risks and relevant stakeholders. Next, the judgments of experts through the content validity ratio analysis confirmed 12 social risks and 9 key stakeholders. Finally, SNA is used to determine the relations between the social risks and stakeholders as well as the significance of each risk.

The investigation demonstrated that the most important social risks in the construction projects of the case study are “Psychological disorders”, “Environmental pollution” and “Cultural conflicts”.

The findings could help policymakers, urban planners and project managers in developing countries with a rich cultural heritage to reduce social risks and improve the efficiency of their projects.

To the best of the authors’ knowledge, the present study is one of the first instances to investigate construction projects implemented in densely populated urban areas hosting cultural heritage and historic tourism sites.

Managers of megaprojects face social risk management challenges throughout the various design, construction, and operation stages, owing to the various conflicts of interest among stakeholders, public skepticism, and opposition. However, most existing studies have not focused on the dynamic analysis of integrating social risks in these stages. This study developed a dynamic analysis approach to explore the dynamics of critical social risk factors and related stakeholders of megaprojects and built the managerial maps for various stakeholders.

Based on the social analysis network (SNA), a dynamic network analysis approach for understanding the dynamics of social risk and related stakeholders has been developed by literature and case analysis. The approach comprises the following steps: (1) generating social risk–stakeholder networks in different stages; (2) analysis of the critical stakeholders and social risk factors; (3) dynamic analysis of social risk factors; and (4) developing social risk management maps for various stakeholders. To verify the feasibility and effectiveness of the approach, 40 megaprojects from China were analyzed.

According to the results, the local government is a critical stakeholder during all stages, inadequate information promotion (IIP) and imperfect communication and coordination mechanism (ICCM) are key social risk sources throughout the megaproject life cycle. Furthermore, the management maps for government organizations, project implementation groups, and external stakeholders were constructed.

This research has three contributions. First, a dynamic analysis approach of stakeholder-associated social risks in megaprojects is developed, which enriches the social risk management theory of megaprojects and provides inspiration for future research focus. Second, the social risk–stakeholder networks and critical social risks in different stages are confirmed to provide a more valid and accurate picture of social risk management in megaprojects. Third, the social risk managerial maps for different stakeholders built in this research will be beneficial for governments, project implementation groups, and external stakeholders to optimize management strategies.

This study collected the bibliographic data of 2034 journal articles published in 2000–2021 from Web of Science (WoS) core collection database and adopted two bibliometric analysis methods, namely historiography and keyword co-occurrence, to identify the evolution trend of construction risk management (CRM) research topics.

CRM has been a key issue in construction management research, producing a big number of publications. This study aims to undertake a review of the global CRM research published from 2000 to 2021 and identify the evolution of the research topics relating to CRM.

This study found that risk analysis methods have shifted from simply ranking risks in terms of their relative importance or significance toward examining the interrelationships among risks, and that the objects of CRM research have shifted from generic construction projects toward specified types of construction projects (e.g. small projects, underground construction projects, green buildings and prefabricated projects). In addition, researchers tend to pay more attention to an individual risk category (e.g. political risk, safety risk and social risk) and integrate CRM into cost, time, quality, safety and environment management functions with the increasing adoption of various information and communication technologies.

This study focused on the journal articles in English in WoS core collection database only, thus excluding the publications in other languages, not indexed by WoS and conference proceedings. In addition, the historiography focused on the top documents in terms of document strength and thus ignored the role of the documents whose strengths were a little lower than the threshold.

This review study is more inclusive than any prior reviews on CRM and overcomes the drawbacks of mere reliance on either bibliometric analysis results or subjective opinions. Revealing the evolution process of the CRM knowledge domain, this study provides an in-depth understanding of the CRM research and benefits industry practitioners and researchers.

The purpose of this paper is to explore how capitalism has developed into a deeply integrative economic system of financial investments and manufacturing. This process of globalization has brought about the emergence of a transnational capitalist class that rules the world’s economy. Financialization, created by the speed and interconnectivity of information technologies, is a key element that has produced immense wealth for a few while reducing their dependence on the labor of workers. This system of global accumulation has lead to a crisis of democracy with several different possible outcomes.

This paper begins with an historical examination of capitalism and capitalist class formation by tracing developments from nation-centric capitalism to globalization. A conceptual explanation of the development of the transnational capitalist class (TCC) is offered. Research on current economic data to support the thesis on the emergence of the TCC in both its private and statist forms is included, as well as an examination of the latest technology developments that affect financialization and how this impacts class relations. The conclusion analyzes the development of democracy as a class dialectic, and the impact of globalization that is altering the historic relationships between capital and labor. The paper ends with a discussion of possible political/economic futures.

Globalization is a new era in which capitalism has deepened its inherent tendency toward creating world markets and production. This process has been greatly enhanced by the new technological tools of financial production. Organizing and overseeing this system of global accumulation is the transnational capitalist class. The emergence of this class has transformed class relations based within the historic perimeters of nation-states, and it threatens the content and character of democracy that arose out of the bourgeois democratic revolutions in America and France.

Transnational Capitalist Class Theory is a recently developed field of research. It is a new critic of mainstream international relations analysis which centers on nation to nation relationships. It also differs with world system theory which divides countries into a center/peripheral analysis. Within the field of TCC research, this paper offers an original historic perspective between global economics and the development of democracy. It also makes new theoretical connections between information technology, financialization and the destruction of the social contract.

The tendency to utilize transnational organizations (TNO), with the tacit support of transnational institutions such as the European Union, to realize mega projects affecting local populations and territories distant from decision-making boardrooms, may result in increasing democratic alienation between those who are charged with implementing these projects and local citizens.

This chapter presents Stage 2 of a study to examine democratic participation and communicative action between a transnational organization, governing bodies, and the citizens affected by a high-speed rail project in Susa Valley, Italy. Findings related to potential democratic alienation between citizens and decision-makers are presented. Societal factors which contribute to this alienation, such as a communication deficit, are considered, as well as the strategies adopted to counter this participatory gap – including a reliance on electronic media for disseminating information and the creation of transnational resistance networks.

Results suggest that the emergence of transnational resistance networks such as the Forum Against Unnecessary and Imposed Mega Projects – spearheaded by members of the No TAV social movement, may provide new avenues for democratic participation and citizen engagement.

It is no news that Chinese construction companies are highly motivated to invest in Africa in terms of infrastructure and construction. This influx from the beginning of the millennium marked a game-changer for infrastructural development in most African countries. This study, therefore, explores how the partnership between China and Africa has impacted the construction industry in Africa with a focus on Nigeria.

A quantitative approach was adapted for the study, which is descriptive in nature, and the primary participants of the study were core construction professionals within the Nigerian construction industry. Data was collected via a structured questionnaire, and multivariate statistics was used to analyse the data.

The study results revealed that the benefits accrued from Chinese participation in the African construction industry can be classified into three distinct categories: socio-economic development through construction, land transportation system development and construction industry development. The study further revealed that Chinese involvement has been most beneficial to the development of the land transportation system in Nigeria with more investment in the construction and maintenance of roads and railways.

The study will serve as a basis for making informed future decisions on Chinese participation in the Nigerian construction industry as it exposes the impacts of the relationship within the current system. The outcome of this study can be used to refocus the partnership to ensure the optimum development of the local construction industry. The government and other relevant agencies can use the findings from this study to ensure that there is sustainable growth in the local construction industry through Chinese participation.

In the past few decades, traditional project management theories mainly focused on quality, cost and schedule. However, with larger scale and wider influence of infrastructure projects, especially in megaprojects, social problems have gradually become pressing issues in the field of project governance. As the public is the main body of society, public participation has attracted the attention from both the academic field and industry field. Despite people are gradually realizing the significance of public participation, a deeper and more systematic understanding is still needed to be developed in this field. Therefore, this paper aims to conduct a systematic literature review on public participation in infrastructure projects. Based on existing literatures, this paper draws a knowledge map and develops a research framework in this field. Also, this paper tries to provide some theoretical and practical directions for the future.

In total, 142 papers from Web of Science Core collection were selected to be used in this systematic review. Quantitative analysis of this paper is concentrated on the knowledge map with bibliometric tools. Qualitative analysis is concentrated on identifying the research framework.

This paper reviewed existing literatures and the results are as below. Firstly, the results show a knowledge map containing knowledge domains, knowledge frontiers and knowledge evolution of research fields in public participation. Secondly, the results indicate a research framework in this field, including situational dimension, implementation dimension, individual dimension and influence dimension. Moreover, each dimension has several research topics, respectively. Finally, according to the results, the paper proposes practical suggestions for stakeholders and research directions for further study.

It is the first paper to draw a holistic knowledge map and build up a multilevel framework for public participation in the field of infrastructure projects. This paper bridges the gap in both quantitative and qualitative identification of existing literatures in this field. Besides, this paper proposes some practical suggestions and research directions for further study and development of public participation.

The purpose of this paper is to focus on the corporate response of Chinese railway companies after the deadly Wenzhou train accident in China which happened on July 23, 2011. Few studies on corporate social responsibility (CSR) in developing countries have looked into whether the information disclosed by companies is satisfactory with sufficient response after a major incident has happened.

Five companies with the largest market value in the Chinese railway industry involved in the production of trains and railway systems connected to the “7.23” incident were taken as the observations in this study. Information published by the companies and the media related to the accident, including CSR and sustainability reports, company Web sites, news and press releases and Internet postings, were investigated in detail in a qualitative manner.

The findings show that disclosure of information related to the “7.23” incident was very low or almost inexistent in the observed companies. For those that claimed that they had followed CSR reporting standards and guidelines, the disclosed information appeared to be insufficient to reveal practical information and fulfill stakeholders’ requirements. The study also sheds light on the corporate reporting behaviors of Chinese state-owned enterprises by applying legitimacy, stakeholder and institutional theories to the unique social and political environment in the country.

This paper critically reveals the poor corporate response after the “7.23” incident in Chinese railway companies. The case serves as an example for the companies to ponder on what improvements are called for in terms of social reporting and relevant corporate actions after a major accident. Also, the study contributes to the CSR disclosure literature concerning developing countries by examining the case of China and the little studied railway industry run by the state.

Density-based spatial clustering of applications with noise (DBSCAN) is the most commonly used density-based clustering algorithm, while it cannot be directly applied to the railway investment risk assessment. To overcome the shortcomings of calculation method and parameter limits of DBSCAN, this paper proposes a new algorithm called Improved Multiple Density-based Spatial clustering of Applications with Noise (IM-DBSCAN) based on the DBSCAN and rough set theory.

First, the authors develop an improved affinity propagation (AP) algorithm, which is then combined with the DBSCAN (hereinafter referred to as AP-DBSCAN for short) to improve the parameter setting and efficiency of the DBSCAN. Second, the IM-DBSCAN algorithm, which consists of the AP-DBSCAN and a modified rough set, is designed to investigate the railway investment risk. Finally, the IM-DBSCAN algorithm is tested on the China–Laos railway's investment risk assessment, and its performance is compared with other related algorithms.

The IM-DBSCAN algorithm is implemented on China–Laos railway's investment risk assessment and compares with other related algorithms. The clustering results validate that the AP-DBSCAN algorithm is feasible and efficient in terms of clustering accuracy and operating time. In addition, the experimental results also indicate that the IM-DBSCAN algorithm can be used as an effective method for the prospective risk assessment in railway investment.

This study proposes IM-DBSCAN algorithm that consists of the AP-DBSCAN and a modified rough set to study the railway investment risk. Different from the existing clustering algorithms, AP-DBSCAN put forward the density calculation method to simplify the process of optimizing DBSCAN parameters. Instead of using Euclidean distance approach, the cutoff distance method is introduced to improve the similarity measure for optimizing the parameters. The developed AP-DBSCAN is used to classify the China–Laos railway's investment risk indicators more accurately. Combined with a modified rough set, the IM-DBSCAN algorithm is proposed to analyze the railway investment risk assessment. The contributions of this study can be summarized as follows: (1) Based on AP, DBSCAN, an integrated methodology AP-DBSCAN, which considers improving the parameter setting and efficiency, is proposed to classify railway risk indicators. (2) As AP-DBSCAN is a risk classification model rather than a risk calculation model, an IM-DBSCAN algorithm that consists of the AP-DBSCAN and a modified rough set is proposed to assess the railway investment risk. (3) Taking the China–Laos railway as a real-life case study, the effectiveness and superiority of the proposed IM-DBSCAN algorithm are verified through a set of experiments compared with other state-of-the-art algorithms.