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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.

The ongoing paradigm shift in the energy sector holds paramount implications for the realization of the sustainable development goals, encompassing critical domains such as resource optimization, environmental stewardship and workforce opportunities. Concurrently, this transformative trajectory within the power sector possesses a dual-edged nature; it may ameliorate certain challenges while accentuating others. In light of the burgeoning research stream on open innovation, this study aims to examine the intricate dynamics of knowledge-based industry-university-research networking, with an overarching objective to elucidate and calibrate the equilibrium of ambidextrous innovation within power systems.

The authors scrutinize the role of different innovation organizations in three innovation models: ambidextrous, exploitative and exploratory, and use a multiobjective decision analysis method-entropy weight TOPSIS. The research was conducted within the sphere of the power industry, and the authors mined data from the widely used PatSnap database.

Results show that the breadth of knowledge search and the strength of an organization’s direct relationships are crucial for ambidextrous innovation, with research institutions having the highest impact. In contrast, for exploitative innovation, depth of knowledge search, the number of R&D patents and the number of innovative products are paramount, with universities playing the most significant role. For exploratory innovation, the depth of knowledge search and the quality of two-mode network relations are vital, with research institutions yielding the best effect. Regional analysis reveals Beijing as the primary hub for ambidextrous and exploratory innovation organizations, while Jiangsu leads for exploitative innovation.

The study offers valuable implications to cope with the dynamic state of ambidextrous innovation performance of the entire power system. In light of the findings, the dynamic state of ambidextrous innovation performance within the power system can be adeptly managed. By emphasizing a balance between exploratory and exploitative strategies, stakeholders are better positioned to respond to evolving challenges and opportunities. Thus, the study offers pivotal guidance to ensure sustained adaptability and growth in the power sector’s innovation landscape.

The primary originality is to extend and refine the theoretical understanding of ambidextrous innovation within power systems. By integrating several theoretical frameworks, including social network theory, knowledge-based theory and resource-based theory, the authors enrich the theoretical landscape of power system ambidextrous innovation. Also, this inclusive examination of two-mode network structures, including the interplay between knowledge and cooperation networks, unveils the intricate interdependencies between these networks and the ambidextrous innovation of power systems. This approach significantly widens the theoretical parameters of innovation network research.

Blockmodeling is viewed often as a data reduction method. However, this is a simplistic view of the class of methods designed to uncover social structures, identify subgroups, and reveal emergent roles. Worse, this view misses the richness of the method as a tool for uncovering novel human resource management (HRM) insights. Here, we provide a brief overview of some essentials of blockmodeling and discuss research questions that can be addressed using this approach in applied HRM settings. Finally, we offer an empirical example to illustrate blockmodeling and the types of information that can be gleaned from its implementation.

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.

This study aims to investigate the content of hotel brands’ mission statements (MSs) and their relationship with selected attributes of hotel brands.

Content analysis of hotel brands’ MSs was used to detect the MSs’ key words, which were further processed by methods of social network analysis, complemented by clustering techniques and correspondence analysis on the generalized aggregated lexical tables, a special type of correspondence analysis.

Hotel brands operating in luxurious markets more often emphasize experiences than those in midscale markets. Furthermore, hotel brands with longer traditions and those with a large number of controlled rooms communicate words in their MSs that represent a rather traditional approach to hospitality. Younger hotel brands with fewer controlled rooms chose words that indicate a more commercially oriented approach. Finally, cluster analysis revealed four dimensions of hotel brands’ MSs, instead of the nine most typically used in mission statement component models.

Understanding the frequencies and networks of keywords, and their relationship with hotel brand attributes, will help create more focussed MSs. This will strengthen hotel brands, raise their revenues and subsequently increase company performance.

The analysis provides valuable insight into MSs in the specific tourism context of hotel brands. The authors have achieved this with the use of a wide range of advanced network analytic methods. These insights can guide hotel brands to better position themselves in the competitive tourism accommodation market.

Corporate success depends partially on the quality of knowledge accessible to the executive board. One route of access to such knowledge is the appointment of directors who already hold directorships with prominent other corporate actors. Such director appointments provide interlocks to a corporate knowledge ecosystem (Haunschild and Beckman, 1998). The purpose of this paper is to examine how linkages between companies belonging to different sectors impact firm performance and to examine how linkages created by female directors, as opposed to male directors, shape performance.

This paper investigates the interlocks created between UK FTSE 350 companies from 2010 to 2018. It draws on network analysis to map the roles that male and female directors play in linking firms with varying sector classifications. The paper provides an examination of the impact of these roles on firm performance, through a panel data regression analysis.

This paper finds that there is an increase of inter-industry brokers over the period, and that men are still dominant in both the network and creating inter-industry ties amongst companies. However, the role of women in establishing these ties appears to be changing, and women are more important when it comes to create inter-industry ties among key economic sectors.

This paper provides a novel approach to examine the interplay between gendered inter (and intra) sectoral linkages and firm performance. It provides an original application of the two-mode brokerage analysis framework proposed in Jasny and Lubell (2015).

Bipartite networks (e.g., software developers linked to open-source projects) are common in settings studied by organization scholars. But the structure underlying bipartite networks tends to be overlooked. Commonly, two modes are reduced to one mode for analysis, causing loss of information. We review techniques for projecting 2-modes onto 1-mode and discuss 2-mode measures of clustering. We also address the potential for 2-mode theory development concerning (a) how change in one mode influences change in the other, (b) the question of two types of agency, and (c) how diversity in one mode is a substitute for diversity in the other mode.

The role of relationships in the process of leadership and change is central, yet the social aspect of the work of reform is often background in favor of more technical approaches to improvement. Therefore, the purpose of this paper is to argue that social network theory and analysis provides a useful theory and set of tools to unpack the complex social work of leadership.

In this paper the authors begin by reviewing social network theory in education to date. The authors identify strengths and gap areas and use findings and data from existing social network studies of educational leadership to highlight major concepts.

Along with empirical examples, the paper proposes four important strands of social network analysis for future research in educational leadership: multiplex networks; multi-mode networks; longitudinal networks; and real time networks.

This paper builds on recent scholarship using social network analysis in educational leadership and suggests that social network theory and methods provides unique and important analytic purchase in the study of educational leadership.

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).

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.