The evolution of the intellectual structure of strategic management between 1980 and 2019

2020 ◽  
Vol 13 (4) ◽  
pp. 503-534
Author(s):  
Mehmet Ali Köseoğlu ◽  
John Parnell
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Strategic Management ◽  
Citation Analysis ◽  
Intellectual Structure ◽  
Future Directions ◽  
Content Type ◽  
The Social ◽  
Economic Foundation

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.

Duality beyondPersons and Groups

2020 ◽  
pp. 391-413
Author(s):  
Sophie Mützel ◽  
Ronald Breiger
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Network Data ◽  
Future Directions ◽  
Affiliation Networks ◽  
The Social ◽  
Recent Developments ◽  
Principle Of Duality ◽  
Seminal Article

This chapter focuses on the general principle of duality, which was originally introduced by Simmel as the intersection of social circles. In a seminal article, Breiger formalized Simmel’s idea, showing how two-mode types of network data can be transformed into one-mode networks. This formal translation proved to be fundamental for social network analysis, which no longer needed data on who interacted with whom but could work with other types of data. In turn, it also proved fundamental for the analysis of how the social is structured in general, as many relations are dual (e.g. persons and groups, authors and articles, organizations and practices), and are thus susceptible to an analysis according to duality principles. The chapter locates the concept of duality within past and present sociology. It also discusses the use of duality in the analysis of culture as well as in affiliation networks. It closes with recent developments and future directions.

scholarly journals Polarisation in political Twitter conversations

2014 ◽  
Vol 66 (3) ◽  
pp. 329-341 ◽  
Author(s):  
David Gunnarsson Lorentzen
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Design Methodology ◽  
Right Wing ◽  
Content Type ◽  
The Social ◽  
Left Block ◽  
The Right

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.

Trend analysis of co-authorship network in Library Hi Tech

2019 ◽  
Vol 37 (1) ◽  
pp. 43-56 ◽  
Author(s):  
Fei-Fei Cheng ◽  
Yu-Wen Huang ◽  
Der-Chian Tsaih ◽  
Chin-Shan Wu
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Research Field ◽  
Collaboration Network ◽  
Knowledge Map ◽  
Content Type ◽  
Visual Knowledge ◽  
The Social ◽  
Cohesive Subgroup

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.

MNEs from emerging markets: a review of the current literature through “bibliographic coupling” and social network analysis

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Francisco García-Lillo ◽  
Enrique Claver ◽  
Bartolomé Marco-Lajara ◽  
Pedro Seva-Larrosa ◽  
Lorena Ruiz-Fernández
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Emerging Markets ◽  
Citation Index ◽  
Intellectual Structure ◽  
Bibliographic Coupling ◽  
Content Type ◽  
Research Fronts ◽  
Active Research

PurposeIn recent years, author and document citation and co-citation analyses have often been applied to map the “intellectual structure” of different scientific fields, including management and international business. However, the technique of bibliographic coupling between scientific documents, which seeks to identify active research fronts in a scientific field or discipline, has been less commonly used. This study utilized this technique to identify and visualize the research fronts in the context of papers on emerging markets multinational enterprises (EM-MNEs) recently published in a wide variety of journals. The aim is not only to complement and expand the results obtained in prior studies that have used other types of systematization, such as qualitative content analysis methodology but also to propose avenues for future research.Design/methodology/approachThe primary databases utilized to carry out the present research work – both comprised in the Web of Science™ (WoS) Core Collection – were: the Social Sciences Citation Index® (SCI) developed by the Institute for Scientific Information (ISI) and the Emerging Sources Citation Index. A total of 496 “peer-reviewed journal articles” published between 2014 and December 30, 2019 were retrieved. With regards to the methodology, bibliometric methods were utilized, as well as social network analysis (SNA).FindingsParticularly, the analytical techniques employed – adopting a “quantitative” method of a deductive character – allowed the identification of the most active research “fronts” in international research related to the topic under analysis: the phenomenon of EM-MNEs.Research limitations/implicationsThe present study has several limitations resulting from the utilization of bibliometric methods applied in the analyses performed.Originality/valueThe authors believe that this research is of value for future researchers since it allows the identification of research “fronts,” which shape the vanguard of knowledge and reveal current trends and future directions in the area under examination.

Broadcasting, reacting, engaging – three strategies for CSR communication in Twitter

2014 ◽  
Vol 18 (4) ◽  
pp. 322-342 ◽  
Author(s):  
Michael Etter
Keyword(s):  
Social Media ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Public Relations ◽  
Design Methodology ◽  
Relationship Building ◽  
Content Type ◽  
Csr Communication ◽  
The Social

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.

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
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Social Context ◽  
Network Analysis ◽  
Construction Projects ◽  
Dynamic Assessment ◽  
Social Sustainability ◽  
Assessment Model ◽  
Content Type ◽  
The Social

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.

Predicting investor funding behavior using crunchbase social network features

2016 ◽  
Vol 26 (1) ◽  
pp. 74-100 ◽  
Author(s):  
Yuxian Eugene Liang ◽  
Soe-Tsyr Daphne Yuan
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Link Prediction ◽  
Social Relationship ◽  
Jaccard Coefficient ◽  
Network Graph ◽  
Content Type ◽  
The Social ◽  
Relationship Factors

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.

The Oxford Handbook of Social Networks

2020 ◽  
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Social Life ◽  
Information Science ◽  
Computational Social Science ◽  
The Social ◽  
Diverse Field ◽  
The Rich

Social networks fundamentally shape our lives. Networks channel the ways that information, emotions, and diseases flow through populations. Networks reflect differences in power and status in settings ranging from small peer groups to international relations across the globe. Network tools even provide insights into the ways that concepts, ideas and other socially generated contents shape culture and meaning. As such, the rich and diverse field of social network analysis has emerged as a central tool across the social sciences. This Handbook provides an overview of the theory, methods, and substantive contributions of this field. The thirty-three chapters move through the basics of social network analysis aimed at those seeking an introduction to advanced and novel approaches to modeling social networks statistically. The Handbook includes chapters on data collection and visualization, theoretical innovations, links between networks and computational social science, and how social network analysis has contributed substantively across numerous fields. As networks are everywhere in social life, the field is inherently interdisciplinary and this Handbook includes contributions from leading scholars in sociology, archaeology, economics, statistics, and information science among others.

scholarly journals Evaluation of Coordination of Emergency Response Team through the Social Network Analysis. Case Study: Oil and Gas Refinery

2015 ◽  
Vol 6 (1) ◽  
pp. 30-34 ◽  
Author(s):  
Iraj Mohammadfam ◽  
Susan Bastani ◽  
Mahbobeh Esaghi ◽  
Rostam Golmohamadi ◽  
Ali Saee
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Emergency Response ◽  
Oil And Gas ◽  
The Social ◽  
Response Team ◽  
Gas Refinery
Sign in / Sign up

Export Citation Format

Share Document