Internet-based digitalmarketing strategies fordata-rich environments

2018 ◽  
Vol 31 (2) ◽  
pp. 98-113 ◽  
Author(s):  
Faiqa Kiran ◽  
Ahsan Zubair ◽  
Irum Shahzadi ◽  
Aamir Abbas
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Longitudinal Design ◽  
Negative Relationship ◽  
Small Sample ◽  
Strategic Decision ◽  
Cross Sectional ◽  
Content Type ◽  
Rated Performance

Purpose The purpose of this paper is to first bring to light the essential digital strategies to study organizations. Second, how businesses can improve their strategic capabilities by using the information gathered from internet sources or networks. Third, this study investigates how employees in an organization tend to engage in positive and/or negative gossip and how gossips affect coworker-rated informal influence in organization and supervisor-rated performance. Social network analysis is used to find the underlying relationships between gossips, coworker-rated influence and supervisor-rated performance. Design/methodology/approach This research paper is divided into two parts. The first study based on profound synthesis of literature. Major digital sources to study organizations are identified. The strategies requirement for each channel is identified. Suggestions are given to managers to improve strategic decision-making based on big data. The second study is a cross-sectional study where questionnaires (survey) are used to elicit data. Social network analysis is used to analyze the data using ucinet 6 software. Findings The findings of the study pinpoint the skills required to analyze large data, available in organizations. The second study finds out that close friends are more engaged in gossips than coworkers who have only working relationships. The friends having high structural embeddedness are more likely to be involved in negative gossips. Coworker perceives those employees who are engaged in negative gossips as having high informal influence. However, there is negative relationship between negative gossips and supervisor-rated influence. Research limitations/implications The research study is cross-sectional in design; however, longitudinal design can be used to gain more insights about negative gossips and their effects. Second, a very small sample is used in this study. Practical implications This study can be used to understand informal communication network in the organization. Managers can use this channel to pass information quickly, as informal channels are faster than formal communication channels. This research can be used to understand the underling relationships between the coworkers in organizations Originality/value This paper provides guidelines to organizational life and information on how the informal networks within organization can be studied.

scholarly journals A case study of university student networks and the COVID-19 pandemic using a social network analysis approach in halls of residence

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
José Alberto Benítez-Andrades ◽  
Tania Fernández-Villa ◽  
Carmen Benavides ◽  
Andrea Gayubo-Serrenes ◽  
Vicente Martín ◽  
...  
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
University Students ◽  
Methodological Approach ◽  
Centrality Measures ◽  
Structural Behaviour ◽  
Cross Sectional ◽  
Depth Analysis ◽  
The University

AbstractThe COVID-19 pandemic has meant that young university students have had to adapt their learning and have a reduced relational context. Adversity contexts build models of human behaviour based on relationships. However, there is a lack of studies that analyse the behaviour of university students based on their social structure in the context of a pandemic. This information could be useful in making decisions on how to plan collective responses to adversities. The Social Network Analysis (SNA) method has been chosen to address this structural perspective. The aim of our research is to describe the structural behaviour of students in university residences during the COVID-19 pandemic with a more in-depth analysis of student leaders. A descriptive cross-sectional study was carried out at one Spanish Public University, León, from 23th October 2020 to 20th November 2020. The participation was of 93 students, from four halls of residence. The data were collected from a database created specifically at the university to "track" contacts in the COVID-19 pandemic, SiVeUle. We applied the SNA for the analysis of the data. The leadership on the university residence was measured using centrality measures. The top leaders were analyzed using the Egonetwork and an assessment of the key players. Students with higher social reputations experience higher levels of pandemic contagion in relation to COVID-19 infection. The results were statistically significant between the centrality in the network and the results of the COVID-19 infection. The most leading students showed a high degree of Betweenness, and three students had the key player structure in the network. Networking behaviour of university students in halls of residence could be related to contagion in the COVID-19 pandemic. This could be described on the basis of aspects of similarities between students, and even leaders connecting the cohabitation sub-networks. In this context, Social Network Analysis could be considered as a methodological approach for future network studies in health emergency contexts.

Social network analysis applications in sustainable construction and built environment management: a review

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Nandun Madhusanka Hewa Welege ◽  
Wei Pan ◽  
Mohan Kumaraswamy
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Built Environment ◽  
Methodological Approach ◽  
Relevant Literature ◽  
Sustainable Construction ◽  
Centrality Measures ◽  
Environment Management ◽  
Content Type

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.

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.

scholarly journals Nursing Students’ Subjective Happiness: A Social Network Analysis

2021 ◽  
Vol 18 (21) ◽  
pp. 11612
Author(s):  
Eun-Joo Kim ◽  
Ji-Young Lim ◽  
Geun-Myun Kim ◽  
Seong-Kwang Kim
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Nursing Students ◽  
Network Analysis ◽  
Group Dynamics ◽  
Future Research ◽  
Subjective Happiness ◽  
Cross Sectional Survey ◽  
Cross Sectional ◽  
High Level

Improving nursing students’ subjective happiness is germane for efficiency in the nursing profession. This study examined the subjective happiness of nursing students by applying social network analysis (SNA) and developing a strategy to improve the subjective happiness of nursing. The study adopted a cross sectional survey to measure subjective happiness and social network of 222 nursing students. The results revealed that the centralization index, which is a measure of intragroup interactions from the perspective of an entire network, was higher in the senior year compared with the junior year. Additionally, the indegree, outdegree, and centrality of the social network of students with a high level of subjective happiness were all found to be high. This result suggests that subjective happiness is not just an individual’s psychological perception, but can also be expressed more deeply depending on the subject’s social relationships. Based on the study’s results, to strengthen self-efficacy and resilience, it is necessary to utilize strategies that activate group dynamics, such as team activities, to improve subjective happiness. The findings can serve as basic data for future research focused on improving nursing students’ subjective happiness by consolidating team-learning social networks through a standardized program approach within a curriculum or extracurricular programs.

FinTech innovation and knowledge flows in Hong Kong’s financial sector: a social network analysis approach

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Anson Au
Keyword(s):  
Hong Kong ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Commercial Banks ◽  
Financial Sector ◽  
Knowledge Flows ◽  
Foreign Firms ◽  
Content Type ◽  
Network Position

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.

Social network analysis and data visualization of MIS international collaboration in Taiwan

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Yung-Ting Chuang ◽  
Yi-Hsi Chen
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
International Collaboration ◽  
Research Productivity ◽  
Research Collaboration ◽  
Clustering Algorithms ◽  
The United States ◽  
Content Type ◽  
Collaboration Patterns

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.

Who is the boss? Identifying key roles in telecom fraud network via centrality-guided deep random walk

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
Keyword(s):  
Social Network ◽  
Random Walk ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Random Walks ◽  
Interpersonal Relationships ◽  
Interaction Network ◽  
Data Set ◽  
Content Type ◽  
Structural Equivalence

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.

Obstacles and opportunities for networked practice: a social network analysis of an inter-organizational STEM ecosystem

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Yi-Hwa Liou ◽  
Alan J. Daly
Keyword(s):  
Higher Education ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Geographic Region ◽  
Central Position ◽  
Content Type ◽  
Related Information ◽  
Stem Pipeline ◽  
And Mathematics

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.

Social network analysis: organizational implications in tourism management

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Marco Valeri ◽  
Rodolfo Baggio
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Single Case ◽  
Effective Interaction ◽  
Organizational Structures ◽  
Review Literature ◽  
Future Research ◽  
Economic Sectors ◽  
Content Type

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.

Mapping knowledge structure by keyword co-occurrence and social network analysis

2018 ◽  
Vol 36 (4) ◽  
pp. 636-650 ◽  
Author(s):  
Fei-Fei Cheng ◽  
Yu-Wen Huang ◽  
Hsin-Chun Yu ◽  
Chin-Shan Wu
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Academic Library ◽  
Knowledge Structure ◽  
Visual Exploration ◽  
Bibliographic Databases ◽  
Research Issues ◽  
Content Type ◽  
The Usa

Purpose The purpose of this paper is to present the knowledge structure based on the articles published in Library Hi Tech. The research hotspots are expected to be revealed through the keyword co-occurrence and social network analysis. Design/methodology/approach Data sets based on publications from Library Hi Tech covering the time period from 2006 to 2017 were extracted from Web of Science and developed as testbeds for evaluation of the CiteSpace system. Highly cited keywords were analyzed by CiteSpace which supports visual exploration with knowledge discovery in bibliographic databases. Findings The findings suggested that the percentage of publications in the USA, Germany, China, and Canada are high. Further, the most popular keywords identified in Library Hi Tech were: “service,” “technology,” “digital library,” “university library,” and “academic library.” Finally, four research issues were identified based on the most-cited articles in Library Hi Tech. Originality/value While keyword plays an important role in scientific research, limited studies paid attention to the keyword analysis in librarian research. The contribution of this study is to systematically explore the knowledge structure constructed by the keywords in Library Hi Tech.

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