Exploring government networks through interorganizational relationships: research strategies based on social network analysis (SNA)

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Diogo Ribeiro da Fonseca

PurposeThe purpose of this paper is to provide methodological guidelines and examples of how social network analysis (SNA) can be used in public management network research. SNA describes network structures formed by the patterns of relationships between different actors. Exchange relationships between government, market and society, which conceptualize public sector policies and goals, can be analyzed as a means to highlight underlying governance structures, coordination and management mechanisms, organizational capabilities and strategies of government activities.Design/methodology/approachDrawing from key aspects and concepts of network management, structuring, and modes of governance, research strategies are presented for the analysis of public networks through an illustrative study of relational patterns between providers and receivers of training in the public sector.FindingsSNA highlights prevalent modes of organizing – bureaucratic, market or collaborative (networked) – key actors, roles and strategies that influence network structure, and collective and individual results. Network data can provide information on the relationship between context, organizations' roles and characteristics, and the effectiveness of public policies.Practical implicationsInformation regarding patterns of exchange relationships such as services, resources, influence, knowledge and personnel, are relevant for policymaking processes and may subsidize new approaches and policy instruments that seek to optimize, develop and prescribe structural arrangements for better coordination and effective provision of public services.Originality/valueThe paper advances current literature by presenting a general methodological approach to large interorganizational networks, useful for the consistent theoretical development of governance network theory in the public administration field.

2014 ◽  
Vol 10 (3) ◽  
pp. 382-408 ◽  
Author(s):  
R. Drew Sellers ◽  
Timothy J. Fogerty ◽  
Larry M. Parker

Purpose – This paper aims to, using evidence from a former office of the public accounting firm Arthur Andersen, to study the importance of the relational content and structure of individuals’ social connections as they transitioned to subsequent employment. The paper also examines the maintenance of their social networks through time. Implications for careers in the accounting field are offered. Practicing accountants’ connections with other individuals have often been recognized as an important resource that influences career success. However, these social networks have escaped systematic academic study in accounting. Design/methodology/approach – Social network analysis, built on survey data. Findings – The results show that who one was connected to in a previous employment was more important than one’s overall network position when deciding whether to stay or exit public accounting. However those who exited public accounting did not demonstrate a handicap in maintaining network structures after the disbanding of the firm. Research limitations/implications – This study is limited to firm members, and to a single office of a firm. Social network analysis was used as a research tool for the sociology of public accounting. Practical implications – Implications are for careers in public accounting, and the management of human resources in public accounting is offered. Social implications – The paper has implications for the successfulness of professional service provision in a general sense. Originality/value – Almost a decade of social connection is studied with a method that has not appeared in the discipline but is well regarded in management studies.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Nandun Madhusanka Hewa Welege ◽  
Wei Pan ◽  
Mohan Kumaraswamy

PurposeApplications 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.Design/methodology/approach95 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.FindingsA 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.Originality/valueCloser 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.


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.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Anson Au

Purpose This paper aims to examine how financial technology (FinTech) knowledge from foreign firms flows into and among elite commercial banks in Hong Kong’s financial sector to drive innovation. Design/methodology/approach Using social network analysis and regression analysis on a novel database of patents held by Hong Kong’s elite commercial banks, this paper examines the relationships between network position and FinTech knowledge flow. Findings This paper finds four untold patterns of innovation and inequality in Hong Kong’s financial sector: only three banks are responsible for all the FinTech knowledge entering Hong Kong; most foreign FinTech comes from the USA through Hong Kong and Shanghai Banking Corporation, whereas most FinTech from China enters through Fubon Bank and Development Bank of Singapore; older banks and banks with more connections to firms inside Asia are more likely to import FinTech; the most beneficial sources of FinTech for a bank’s network position are firms from outside Asia. Originality/value Despite the well-documented volumes of cross-border and cross-continental movement of financial institutions in Hong Kong, there is little work on the knowledge flows that underwrite this mobility. This paper addresses this gap by using FinTech knowledge flows to map the distribution of innovation, network position and competitive advantage in Hong Kong’s financial sector.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Yung-Ting Chuang ◽  
Yi-Hsi Chen

PurposeThe purpose of this paper is to apply social network analysis (SNA) to study faculty research productivity, to identify key leaders, to study publication keywords and research areas and to visualize international collaboration patterns and analyze collaboration research fields from all Management Information System (MIS) departments in Taiwan from 1982 to 2015.Design/methodology/approachThe authors first retrieved results encompassing about 1,766 MIS professors and their publication records between 1982 and 2015 from the Ministry of Science and Technology of Taiwan (MOST) website. Next, the authors merged these publication records with the records obtained from the Web of Science, Google Scholar, IEEE Xplore, ScienceDirect, Airiti Library and Springer Link databases. The authors further applied six network centrality equations, leadership index, exponential weighted moving average (EWMA), contribution value and k-means clustering algorithms to analyze the collaboration patterns, research productivity and publication patterns. Finally, the authors applied D3.js to visualize the faculty members' international collaborations from all MIS departments in Taiwan.FindingsThe authors have first identified important scholars or leaders in the network. The authors also see that most MIS scholars in Taiwan tend to publish their papers in the journals such as Decision Support Systems and Information and Management. The authors have further figured out the significant scholars who have actively collaborated with academics in other countries. Furthermore, the authors have recognized the universities that have frequent collaboration with other international universities. The United States, China, Canada and the United Kingdom are the countries that have the highest numbers of collaborations with Taiwanese academics. Lastly, the keywords model, system and algorithm were the most common terms used in recent years.Originality/valueThis study applied SNA to visualize international research collaboration patterns and has revealed some salient characteristics of international cooperation trends and patterns, leadership networks and influences and research productivity for faculty in Information Management departments in Taiwan from 1982 to 2015. In addition, the authors have discovered the most common keywords used in recent years.


2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Yi-Chun Chang ◽  
Kuan-Ting Lai ◽  
Seng-Cho T. Chou ◽  
Wei-Chuan Chiang ◽  
Yuan-Chen Lin

PurposeTelecommunication (telecom) fraud is one of the most common crimes and causes the greatest financial losses. To effectively eradicate fraud groups, the key fraudsters must be identified and captured. One strategy is to analyze the fraud interaction network using social network analysis. However, the underlying structures of fraud networks are different from those of common social networks, which makes traditional indicators such as centrality not directly applicable. Recently, a new line of research called deep random walk has emerged. These methods utilize random walks to explore local information and then apply deep learning algorithms to learn the representative feature vectors. Although effective for many types of networks, random walk is used for discovering local structural equivalence and does not consider the global properties of nodes.Design/methodology/approachThe authors proposed a new method to combine the merits of deep random walk and social network analysis, which is called centrality-guided deep random walk. By using the centrality of nodes as edge weights, the authors’ biased random walks implicitly consider the global importance of nodes and can thus find key fraudster roles more accurately. To evaluate the authors’ algorithm, a real telecom fraud data set with around 562 fraudsters was built, which is the largest telecom fraud network to date.FindingsThe authors’ proposed method achieved better results than traditional centrality indices and various deep random walk algorithms and successfully identified key roles in a fraud network.Research limitations/implicationsThe study used co-offending and flight record to construct a criminal network, more interpersonal relationships of fraudsters, such as friendships and relatives, can be included in the future.Originality/valueThis paper proposed a novel algorithm, centrality-guided deep random walk, and applied it to a new telecom fraud data set. Experimental results show that the authors’ method can successfully identify the key roles in a fraud group and outperform other baseline methods. To the best of the authors’ knowledge, it is the largest analysis of telecom fraud network to date.


2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Yi-Hwa Liou ◽  
Alan J. Daly

PurposeThis study responds to major administrative and policy priorities to support science, technology, engineering and mathematics (STEM) education by investigating a multi-sector ecosystem of regional organizations that support a STEM pipeline for education and careers.Design/methodology/approachWe use social network analysis to investigate an entire region within a geographic region of California which included 316 organizations that represent different stakeholder groups, including educational institutions (school districts, schools and higher education), government, private companies, museums, libraries and multiple community-based organizations. This STEM ecosystem reflects a systems-level analysis of a region from a unique social network perspective.FindingsResults indicate that organizations have a surface-level access to STEM-related information, but the deeper and more intense relationship which involves strategic collaboration is limited. Further, interactions around information and collaboration between organizations were purportedly in part to be about education, rarely included PK-12 schools and district as central actors in the ecosystem. In addition, while institutions of higher education occupy a central position in connecting and bridging organizations within the ecosystem, higher education's connectivity to the PK-12 education sector is relatively limited in terms of building research and practice partnerships.Originality/valueThis research has implications for how regional-level complex systems are analyzed, led and catalyzed and further reflects the need to intentionally attend to the growth of STEM networks.


2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Marco Valeri ◽  
Rodolfo Baggio

Purpose The purpose of this paper is to provide an overview of how quantitative analysis methods have been and can be used to improve the competitiveness of tourism destination. The focus of the study is social network analysis (SNA). Design/methodology/approach The research methodology is qualitative and consists of the review literature relevant to this thesis. This methodology is necessary to give an account of the methods and the techniques adopted for the data collection used in other economic sectors. Findings SNA is needed to analyze the creation and configuration of communities of practice within destination and to identify possible barriers to effective interaction. Essentially, it is a complex adaptive socio-economic system. It shares many (if not all) of the characteristics usually associated with such entities, namely, non-linear relationships among the components, self-organization and emergence of organizational structures, robustness to external shocks. Research limitations/implications The most important limit of this paper is that all the results presented here do not concern a single case study. Future research studies will provide a larger number of cases and examples to give the necessary validation to the findings presented here. Practical implications This paper provides a view into the network of relationships that may give tourism organization managers a strong leverage to improve the flow of information and to target opportunities where this flow may have the most impact on regulatory or business activities. Originality/value SNA can help to detect actual expertise and consequently project the potential losses deriving from an inefficient flow of knowledge. In addition, the authors will be able to define roles in the organizational networks and make an evaluation of informal organizational structures over the formal ones. Traditional organizational theories lack a concrete correspondence with mathematical studies and in this respect the authors sought to identify a correspondence.


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