scholarly journals Assessment of social sustainability in construction projects using social network analysis

Facilities ◽  
2015 ◽  
Vol 33 (3/4) ◽  
pp. 152-176 ◽  
Author(s):  
Essam Almahmoud ◽  
Hemanta Kumar Doloi

Purpose – This paper aims to propose a framework that puts the stakeholders at the forefront of achieving sustainability in the social context. This research, thus, argues that the social sustainability outcomes in construction are best achieved by taking into account the satisfactions of the stakeholders. Design/methodology/approach – Based on sustainability and equity theories, a dynamic assessment model has been developed to evaluate the contributions of projects in a social context. Multiple stakeholders and their differing interests associated with the construction projects have been integrated using social network analysis. The mapping of the relationships between the project stakeholders, with respect to their relative stakes and seven social core functions, have been integrated in the assessment model. Findings – The findings of this research suggest that the degree of satisfying the needs of diverse stakeholders is highly significant in achieving social sustainability performance of projects. Using a case study from Saudi Arabia, the applicability and significance of the assessment model has been demonstrated. The application of the model provides the opportunity to identify any problems and to enhance the overall performance of projects in the social context. Research limitations/implications – The functionality and efficacy of the model need to be further tested outside the Saudi Arabian region. Originality/value – The research is original in the sense that for the first time, a novel approach has been developed, putting the stakeholders at the forefront of achieving sustainability outcomes in construction projects.

Author(s):  
Essam Almahmoud ◽  
Hemanta Kumar Doloi

This paper aims to propose a framework that puts the stakeholders at the forefront of achieving sustainability in the social context. This research, thus, argues that the social sustainability outcomes in construction are best achieved by taking into account the satisfaction of the stakeholders. Based on sustainability and equity theories, a dynamic assessment model has been developed to evaluate the contributions of projects in a social context. Multiple stakeholders and their differing interests associated with the construction projects have been integrated using social network analysis. The mapping of the relationships between the project stakeholders, with respect to their relative stakes and seven social core functions, have been integrated into the assessment model. The findings of this research suggest that the degree of satisfying the needs of diverse stakeholders is highly significant in achieving social sustainability performance of projects. Using a case study from Saudi Arabia, the applicability and significance of the assessment model has been demonstrated. The application of the model provides the opportunity to identify any problems and to enhance the overall performance of projects in the social context. The functionality and efficacy of the model need to be further tested outside the Saudi Arabian region. The research is original in the sense that for the first time, a novel approach has been developed, putting the stakeholders at the forefront of achieving sustainability outcomes in construction projects


2020 ◽  
Vol 13 (4) ◽  
pp. 503-534
Author(s):  
Mehmet Ali Köseoğlu ◽  
John Parnell

PurposeThe authors evaluate the evolution of the intellectual structure of strategic management (SM) by employing a document co-citation analysis through a network analysis for academic citations in articles published in the Strategic Management Journal (SMJ).Design/methodology/approachThe authors employed the co-citation analysis through the social network analysis.FindingsThe authors outlined the evolution of the academic foundations of the structure and emphasized several domains. The economic foundation of SM research with macro and micro perspectives has generated a solid knowledge stock in the literature. Industrial organization (IO) psychology has also been another dominant foundation. Its robust development and extension in the literature have focused on cognitive issues in actors' behaviors as a behavioral foundation of SM. Methodological issues in SM research have become dominant between 2004 and 2011, but their influence has been inconsistent. The authors concluded by recommending future directions to increase maturity in the SM research domain.Originality/valueThis is the first paper to elucidate the intellectual structure of SM by adopting the co-citation analysis through the social network analysis.


2014 ◽  
Vol 39 (4) ◽  
Author(s):  
Denis Wegge ◽  
Heidi Vandebosch ◽  
Steven Eggermont

AbstractYoung adolescents’ online bullying behavior has raised a significant amount of academic attention. Nevertheless, little is known about the social context in which such negative actions occur. The present paper addresses this issue and examines how the patterns of traditional bullying and cyberbullying are related, and how electronic forms of bullying can be linked to the social context at school. To address these questions, social network analysis was applied to examine the networks of social interactions and (cyber)bullying among an entire grade of 1,458 thirteen- to fourteen-year-old pupils. The results show that (1) cyberbullying is an extension of traditional bullying as victims often face the same perpetrators offline and online, (2) there is evidence of mutual cyberbullying among youngsters, and (3) cyberbullying is more likely to occur in same-gender and same-class students. The implications for future research and prevention of cyberbullying are discussed.


2014 ◽  
Vol 66 (3) ◽  
pp. 329-341 ◽  
Author(s):  
David Gunnarsson Lorentzen

Purpose – The purpose of this paper is to describe and analyse relationships and communication between Twitter actors in Swedish political conversations. More specifically, the paper aims to identify the most prominent actors, among these actors identify the sub-groups of actors with similar political affiliations, and describe and analyse the relationships and communication between these sub-groups. Design/methodology/approach – Data were collected during four weeks in September 2012, using Twitter API. The material included 77,436 tweets from 10,294 Twitter actors containing the hashtag #svpol. In total, 916 prominent actors were identified and categorised according to the main political blocks, using information from their profiles. Social network analysis was utilised to map the relationships and the communication between these actors. Findings – There was a marked dominance of the three main political blocks among the 916 most prominent actors: left block, centre-right block, and right-wing block. The results from the social network analysis suggest that while polarisation exists in both followership and re-tweet networks, actors follow and re-tweet actors from other groups. The mention network did not show any signs of polarisation. The blocks differed from each other with the right-wingers being tighter and far more active, but also more distant from the others in the followership network. Originality/value – While a few papers have studied political polarisation on Twitter, this is the first to study the phenomenon using followership data, mention data, and re-tweet data.


2021 ◽  
Vol 13 (17) ◽  
pp. 9847
Author(s):  
Tito Castillo ◽  
Rodrigo F. Herrera ◽  
Tania Guffante ◽  
Ángel Paredes ◽  
Oscar Paredes

A sustainable approach in the construction industry requires civil engineering professionals with technical and soft skills. Those skills complement each other and facilitate the professional to work effectively in multidisciplinary groups during the development of construction projects. Universities apply collaborative learning methods such as group work (GW) in the classroom to achieve these skills. There is disagreement on the best way to select the members of the GW to achieve their best performance, but it is clear that it should favor the interaction of diverse actors to promote the development of soft skills. A random or criteria-based selection could bring groups of people very close together, leading to the academic homogeneity of GW members and impairing performance and learning. Even the most alert instructors lack information about the closeness of their students, so they rely on their intuition without having tools that allow them to confirm their assumptions or relate them to GW performance. The objective of this paper was to discover the social structures within the classrooms and to identify the groups of people close by trust, knowledge, and informal conversation to relate them to their GW performance. For this purpose, a social network analysis (SNA) was applied to Civil Engineering degree students. In addition, a correlation analysis between SNA metrics and GW grades was performed. The results show that beyond the way in which members are selected, there is a social structure that affects such selection and GW performance. This study presents information that can be used for instructors for a better GW selection that propitiates the development of soft skills in Civil Engineering students.


2017 ◽  
Vol 24 (2) ◽  
pp. 229-259 ◽  
Author(s):  
Veronika Lilly Meta Schröpfer ◽  
Joe Tah ◽  
Esra Kurul

Purpose The purpose of this paper is to examine knowledge transfer (KT) practices in five construction projects delivering sustainable office buildings in Germany and the UK by using social network analysis (SNA). Design/methodology/approach Case studies were adopted as research strategy, with one construction project representing one case study. A combination of quantitative data, social network data and some qualitative data on perceptions of the sustainable construction process and its KT were collected through questionnaires. The data were analysed using a combination of descriptive statistics, cross-tabulations, content analysis and SNA. This resulted in a KT map of each sustainable construction project. Findings The findings resulted in a better understanding of how knowledge on sustainable construction is transferred and adopted. They show that large amounts of tacit knowledge were transferred through strong ties in sparse networks. Research limitations/implications The findings could offer a solution to secure a certain standard of sustainable building quality through improved KT. The findings indicate a need for further research and discussion on network density, tie strength and tacit KT. Originality/value This paper contributes to the literature on KT from a social network perspective. It provides a novel approach through combining concepts of network structure and relatedness in tie contents regarding specialised knowledge, i.e. sustainable construction knowledge. Thereby it provides a robust approach to mapping knowledge flows in office building projects that aim to achieve high levels of sustainability standards.


2019 ◽  
Vol 37 (1) ◽  
pp. 43-56 ◽  
Author(s):  
Fei-Fei Cheng ◽  
Yu-Wen Huang ◽  
Der-Chian Tsaih ◽  
Chin-Shan Wu

Purpose The purpose of this paper is to examine the evolution of collaboration among researchers in Library Hi Tech based on the co-authorship network analysis. Design/methodology/approach The Library Hi Tech publications were retrieved from Web of Science database between 2006 and 2017. Social network analysis based on co-authorship was analyzed by using BibExcel software and a visual knowledge map was generated by Pajek. Three important social capital indicators: degree centrality, closeness centrality and betweenness centrality were calculated to indicate the co-authorship. Cohesive subgroup analysis which includes components and k-core was then applied to show the connectivity of co-authorship network of Library Hi Tech. Findings The results indicated that around 42 percent of the articles were written by single author, while an increasing trend of multi-authored articles suggesting the collaboration among researchers in librarian research field becomes popular. Furthermore, the social network analysis identified authorship network with three core authors – Markey, K., Fourie, I. and Li, X. Finally, six core subgroups each included six or seven tightly connected researchers were also identified. Originality/value This study contributed to the existing literature by revealing the co-authorship network in librarian research field. Key researchers in the major subgroup were identified. This is one of the limited studies that describe the collaboration network among authors from different perspectives showing a more comprehensive co-authorship network.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Shahab Shoar ◽  
Nicholas Chileshe ◽  
Shamsi Payan

PurposeThe purpose of this study is to investigate the latent interrelationships of causes and effects of design deficiencies (DDs) and to identify the most crucial ones by considering the interactions among them.Design/methodology/approachFirst, through a comprehensive literature review, the most critical causes of DDs were identified. The review eventuated in a list of 22 causes and 12 effects, which were categorized into six groups. Second, through the rules of system dynamics and the interactions between the causes and effects were modeled and illustrated using causal loop diagrams (CLDs). With the aid of semi-structured interviews with 20 competent experts, the resultant CLDs were also validated. Third, the opinions of 54 experts, who were chosen from the Iranian community of clients and consultants, were solicited concerning the degree of influence which each factor (causes or effects) exerts on others. Finally, the social network analysis (SNA) approach was deployed to analyze and prioritize factors based on the gathered data from experts.FindingsSNA results indicated that factors such as “design firms' staff rework” and “design firms' loss of reputation” are the most central factors affecting DDs. The model results also identified that factors such as “schedule variance”, “workload” and “lack of quality control and supervision during the design phase” have the highest overall impact on DDs. In the end, some recommendations to address major factors and links were also put forward. Overall, more communications between the pair of stakeholder groups and continuous learning from project experiences are believed to be the main strategies.Originality/valueIt is believed that this study has provided a comprehensive understanding of causal mechanisms among factors, which can assist project managers of different parties (clients, contractors and consulting firms) in taking more effective actions to ameliorate the quality of design documents.


2014 ◽  
Vol 18 (4) ◽  
pp. 322-342 ◽  
Author(s):  
Michael Etter

Purpose – Symmetric communication and relationship building are core principles of public relations, which have been highlighted for CSR communication. The purpose of this paper is to develop three different communication strategies for CSR communication in Twitter, of which each contributes differently to the ideals of symmetric communication and relationship building. The framework is then applied to analyze how companies use the micro-blogging service Twitter for CSR communication. Design/methodology/approach – Social network analysis is used to identify the 30 most central corporate accounts in a CSR Twitter network. Findings – From the social network analysis 40,000 tweets are extracted and manually coded. Anova is applied to investigate differences in the weighting of CSR topics between the different strategies. Originality/value – So far not much is known about how social media, such as Twitter, contribute to the core principles of public relations, if companies use social media to foster symmetric communication and relationship management, or which CSR topics they address.


2016 ◽  
Vol 26 (1) ◽  
pp. 74-100 ◽  
Author(s):  
Yuxian Eugene Liang ◽  
Soe-Tsyr Daphne Yuan

Purpose – What makes investors tick? Largely counter-intuitive compared to the findings of most past research, this study explores the possibility that funding investors invest in companies based on social relationships, which could be positive or negative, similar or dissimilar. The purpose of this paper is to build a social network graph using data from CrunchBase, the largest public database with profiles about companies. The authors combine social network analysis with the study of investing behavior in order to explore how similarity between investors and companies affects investing behavior through social network analysis. Design/methodology/approach – This study crawls and analyzes data from CrunchBase and builds a social network graph which includes people, companies, social links and funding investment links. The problem is then formalized as a link (or relationship) prediction task in a social network to model and predict (across various machine learning methods and evaluation metrics) whether an investor will create a link to a company in the social network. Various link prediction techniques such as common neighbors, shortest path, Jaccard Coefficient and others are integrated to provide a holistic view of a social network and provide useful insights as to how a pair of nodes may be related (i.e., whether the investor will invest in the particular company at a time) within the social network. Findings – This study finds that funding investors are more likely to invest in a particular company if they have a stronger social relationship in terms of closeness, be it direct or indirect. At the same time, if investors and companies share too many common neighbors, investors are less likely to invest in such companies. Originality/value – The author’s study is among the first to use data from the largest public company profile database of CrunchBase as a social network for research purposes. The author ' s also identify certain social relationship factors that can help prescribe the investor funding behavior. Authors prediction strategy based on these factors and modeling it as a link prediction problem generally works well across the most prominent learning algorithms and perform well in terms of aggregate performance as well as individual industries. In other words, this study would like to encourage companies to focus on social relationship factors in addition to other factors when seeking external funding investments.


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