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In recent years, the increasing complexity of the hyper-connected world demands new approaches for social network analysis. The main challenges are to find new computational methods that allow the representation, characterization and analysis of these social networks. Nowadays, formal concept analysis (FCA) is considered an alternative to identifying conceptual structures in a social network. In this FCA-based work, this paper aims to show the potential of building computational models based on implications to represent and analyze two-mode networks.

This study proposes an approach to find three important substructures in social networks such as conservative access patterns, minimum behavior patterns and canonical access patterns. The present study approach considered as a case study a database containing the access logs of a cable internet service provider.

The result allows us to uncover access patterns, conservative access patterns and minimum access behavior patterns. Furthermore, through the use of implications sets, the relationships between event-type elements (websites) in two-mode networks are analyzed. This paper discusses, in a generic form, the adopted procedures that can be extended to other social networks.

A new approach is proposed for the identification of conservative behavior in two-mode networks. The proper implications needed to handle minimum behavior pattern in two-mode networks is also proposed to be analyzed. The one-item conclusion implications are easy to understand and can be more relevant to anyone looking for one particular website access pattern. Finally, a method for a canonical behavior representation in two-mode networks using a canonical set of implications (steam base), which present a minimal set of implications without loss of information, is proposed.

This paper aims to forecast the future development of UIC technology according to the changes of IPC in different time periods. The findings also provide a theoretical basis for the UIC policymakers of energy-saving environmental protection industry.

The present study will take energy-saving technology as an example, through using a two-mode network analysis method to build the four-stage IPC code UIC innovation-technology network, researching UIC innovation network applicant heterogeneity, UIC technology network and technology relevance.

Through the establishment of UIC innovation-technology two-mode network, namely, applicant node CN and IPC node TN, this paper analyzes the important applicants, focal technologies, correlation of focal technologies and the development trends of energy saving technology in the future by using the related theories and methods of two-mode network.

At present, only about 11% of energy-saving enterprises in China have R&D activities. The government needs to implement top-level design, improve industrial policies, strengthen investment in technology R&D and build a platform for technological innovation in energy-saving industries to support the R&D of common and key technologies in energy-saving industries.

Prefabricated construction (PC) can benefit construction industry due to its high efficiency, energy saving, consumption reduction and safety. However, the high capital cost is a critical challenge hindering its development in China. The collaboration of PC stakeholders is conducive to improving cost management efficiency and optimizing resource allocation which has been ignored in previous studies. Therefore, this study aims to explore the collaboration paths of stakeholders in the process of solving critical cost influencing factors (CIFs) of PC to reduce costs.

Firstly, 25 CIFs and five main stakeholders that affect PC capital cost were identified through literature research and expert interviews. Then, questionnaires were used to investigate the relationship between stakeholders and CIFs from the perspectives of three stakeholder attributes of proximity, attitude and power, respectively. Finally, based on the survey data, three stakeholder-CIF networks from three attributes perspective and a comprehensive network were constructed and used for subsequent social network analysis.

(1) Stakeholders mainly show willingness and potential to collaborate on organization and management factors; (2) More stakeholders pay attention to incentive policies and the setting of prefabrication rates and assembly rates, while all stakeholders have the right to facilitate information and resource sharing in the PC supply chain; (3) The comprehensive network shows a core-periphery structure. As core stakeholders, contractor, designer and manufacturer are more likely to actively manage the 14 core CIFs.

This paper innovatively combined stakeholder and cost management in PC, and used two-mode network based on three stakeholder perspectives to reveal the collaboration potential and motivation of stakeholders in PC cost management. The findings not only provide guidance for stakeholders to find potential partners and optimize resource allocation in solving specific cost issues, but also facilitate stakeholders' sustainable collaboration to achieve PC's cost performance.

Despite carbon reduction commitments, many constraints hinder the delivery of low-carbon buildings (LCBs) in high-rise high-density cities. The collaborative commitment of relevant stakeholders is vital to effectively address and mitigate these constraints. Hence, this study aims to comprehensively explore the required stakeholder collaboration attributes to address and mitigate the “common” constraints of delivering LCBs by focussing on several high-rise high-density cities.

A list of 21 “significant and common” constraints was identified through a systematic literature review followed by a questionnaire survey covering five economies (Hong Kong, Singapore, Australia, Qatar and the UAE). Nineteen influential stakeholders/stakeholder categories were identified through the literature, and their ability to influence the 21 constraints was mapped and identified through a two-round Delphi survey of 15 experienced professionals. The Delphi survey findings were analysed through social network analysis (SNA) methods to assess the stakeholder engagement and collaboration attributes.

The SNA results revealed the ability of stakeholders to influence the constraints, required collaborative stakeholder networks to address the constraints, significance of stakeholders according to the SNA centrality measures, core and periphery stakeholders and individual co-affiliation networks of core stakeholders.

While achieving the planned primary target of exploring stakeholder collaboration and their significance through SNA, this study also presents a useful sequential methodological approach for future researchers to conduct similar studies in different contexts. The findings also provide a foundation for accelerating the delivery of LCBs by strengthening stakeholder collaboration.

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.

Online web searches have played crucial roles in influencing consumers’ purchasing decisions. Web search traffic information enables researchers and practitioners to better understand consumers in terms of their preferences and interests, among other things. The purpose of this paper is to use web search traffic information provided by Google Trends to derive relationships among product brands as well as those between product brands and product attributes to propose a method to enhance the visibility of consumer brand positioning.

This study builds upon the interesting observation that consumers’ behavior in performing simultaneous searches, or searches including two or more keywords, can be converted into data indicating relationships among brands as well as those between brands and their attributes. The study focuses on the cases of hybrid cars and tablet PCs, and applies a social network analysis method to identify these relationships. Time series information on web search traffic is used because it can track these two product groups from the early stages to the present. This step is completed to verify the changes in the status of each brand and in their relationships that occurred in consumers’ minds over time.

Results show that consumers’ web search behaviors reveal the brand positioning and brand-attribute associations in their minds. Specifically, using consumers’ simultaneous search data, the authors derived relationships among brands (brand-brand network) from consumers’ behaviors of searching simultaneously for two brands and the relationships between brands and attributes (brand-product attributes network) from consumers’ behavior of searching simultaneously for a specific brand and certain product attributes.

Theoretically, this study verifies that consumers’ web search traffic information can be used to microscopically identify the positions of individual brands and their relationships in the minds of consumers. Regarding practical applications, this study proposes a method that can be used by companies to track how consumers perceive their brands by performing a simple and cost-effective analysis using the free search traffic information provided by Google.

Applications of social network analysis (SNA) are evidently popular amongst scholars for mapping stakeholder and other relational networks in improving the sustainability of construction activities and the resulting built environment. Nevertheless, the literature reveals a lack of thorough understanding of optimal SNA applications in this field. Therefore, this paper aims to convey a comprehensive critical review of past applications of SNA in this field.

95 relevant journal papers were initially identified from the “Web of Science” database and a bibliometric analysis was carried out using the “VOS Viewer” software. The subsequent in-depth review of the SNA methods, focussed on 24 specifically relevant papers selected from these aforesaid 95 papers.

A significant growth of publications in this field was identified after 2014, especially related to topics on stakeholder management. “Journal of Cleaner Production”, “International Journal of Project Management” and “Sustainability” were identified as the most productive sources in this field, with the majority of publications from China. Interviews and questionnaires were the popular data collection methods while SNA “Centrality” measures were utilised in over 70% of the studies. Furthermore, potential areas were noted, to improve the mapping and thereby provide useful information to managers who could influence relevant networks and consequentially better sustainability outcomes, including those enhanced by collaborative networks.

Closer collaboration has been found to help enhance sustainability in construction and built environment, hence attracting research interest amongst scholars on how best to enable this. SNA is established as a significant methodological approach to analysing interrelationships and collaborative potential in general. In a pioneering application here, this paper initiates the drawing together of findings from relevant literature to provide useful insights for future researchers to comprehensively identify, compare and contrast the applications of SNA techniques in construction and built environment management from a sustainability viewpoint.

This study aims to identify the stakeholders and critical factors (CFs) of promoting age-friendly communities (AFCs), discuss the relationship between the stakeholders and CFs and develop a preliminary framework for the briefing stage of promoting AFCs in urban China.

Stakeholders and CFs were identified through literature review and document analysis. The Delphi method was used to screen the extracted stakeholders and CFs. The focus group methodology was applied to obtain evaluation matrices of relationships between stakeholders and CFs. A two-mode social network was formed to analyse the evaluation matrices generated.

Results of the analyses indicate that local governments and policymaking institutions, together with project investors, obtained high prioritisations in the stakeholders' group, whilst senior citizens and caregivers appear to rank last. For CFs, communities' environmental factors receive the most attention from stakeholders.

Results of the analyses can only show similarities of the participating stakeholders' opinions on their concerns, and provide researchers and practitioners with initial ideas on analysing stakeholders and CFs at the briefing stage of promoting AFCs. For a specific project, the concerns and prioritisations would change. Diverse voices are necessary and case studies are in need.

Challenges in promoting AFCs in urban China are discussed, and a preliminary framework of the briefing stage is developed for practitioners to follow when promoting AFCs.

This study discusses which CFs should be considered priorities and what consensuses are generally reached by stakeholders. CFs are utilised to interpret stakeholders' relationships, influences and concerns on AFC projects when conducting the social network analysis (SNA).

The purpose of this paper is to develop a novel risk analysis method named fuzzy critical risk analysis (FCRA) for assessing the infrastructure risks from a risk-community network perspective. The basis of this new FCRA method is the integration of existing risk magnitude analysis with the novel risk impact propagation analysis performed in specific infrastructure systems to assess the criticality of risk within specific social-infrastructure interrelated network boundary.

The FCRA uses a number of scientific methods such as failure mode effect and criticality analysis (FMECA), social network analysis (SNA) and fuzzy-set theory to facilitate the building of risk evaluation associated with the infrastructure and the community. The proposed FCRA approach has been developed by integrating the fuzzy-based social network analysis (FSNA) method with conventional fuzzy FMECA method to analyse the most critical risk based on risk decision factors and risk impact propagation generated by various stakeholder perceptions.

The application of FSNA is considered to be highly relevant for investigating the risk impact propagation mechanism based on various stakeholder perceptions within the infrastructure risk interrelation and community networks. Although conventional FMECA methods have the potential for resulting in a reasonable risk ranking based on its magnitude value within the traditional risk assessment method, the lack of considering the domino effect of the infrastructure risk impact, the various degrees of community dependencies and the uncertainty of various stakeholder perceptions made such methods grossly ineffective in the decision-making of risk prevention (and mitigation) and resilience context.

The validation of the model is currently based on a hypothetical case which in the future should be applied empirically based on a real case study.

Effective functioning of the infrastructure systems for seamless operation of the society is highly crucial. Yet, extreme events resulted in failure scenarios often undermine the efficient operations and consequently affect the community at multiple levels. Current risk analysis methodologies lack to address issues related to diverse impacts on communities and propagation of risks impact within the infrastructure system based on multi-stakeholders’ perspectives. The FCRA developed in this research has been validated in a hypothetical case of infrastructure context. The proposed method will potentially assist the decision-making regarding risk governance, managing the vulnerability of the infrastructure and increasing both the infrastructure and community resilience.

The new approach developed in this research addresses several infrastructure risks assessment challenges by taking into consideration of not only the risk events associated with the infrastructure systems but also the dependencies of various type communities and cascading effect of risks within the specific risk-community networks. Such a risk-community network analysis provides a good basis for community-based risk management in the context of mitigation of disaster risks and building better community resilient.

The novelty of proposed FCRA method is realized due to its ability for improving the estimation accuracy and decision-making based on multi-stakeholder perceptions. The process of assessment of the most critical risks in the hypothetical case project demonstrated an eminent performance of FCRA method as compared to the results in conventional risk analysis method. This research contributes to the literature in several ways. First, based on a comprehensive literature review, this work established a benchmark for development of a new risk analysis method within the infrastructure and community networks. Second, this study validates the effectiveness of the model by integrating fuzzy-based FMECA with FSNA. The approach is considered useful from a methodological advancement when prioritizing similar or competing risk criticality values.

Defining key artificial intelligence (AI) technologies is especially fundamental because AI applications involve the development of multiple technical fields and have the potential to generate numerous business opportunities in the future. However, most related studies have examined patent grants granted by or patent applications filed to major patent offices; few studies have employed the perspective of standard-essential patents (SEPs) from a holistic technical view. In addition, because few studies have explored the status signals of countries in relation to SEPs, the present study integrated “country” into the model and determined differences among countries in terms of their technological focus.

In this study, through patent technological network analysis in various periods, the author not only observed the focus fields of AI-related SEPs but also examined temporal trends to determine technical development trends.

This study identified technologies that have been key players in the SEP network in recent years; these technologies were centered on electric digital data processing, recognition of data and transmission of digital information. Moreover, many of these technologies have been applied in areas such as management and commerce and radio navigation. Furthermore, the USA plays a crucial role in the global development of AI technical network.

This study constructs a technical network model to identify key technologies and trends that can serve as a reference for national research and development resource allocation.