Search results

Network analysis is a well consolidated research area in several disciplines. Within management and organizational studies, network scholars consolidated a set of research practices that allowed ease of data collection, high inter case comparability, establishment of nomological laws and commitment to social capital motivation. This paper aims to elicit the criticism it has received and highlight the unsettled lacunae.

This paper sheds light on Network Analysis’s breakthroughs, while showing how its scholars innovated by responding to critics, and identifying outstanding debates.

The paper identifies and discusses three streams of criticism that are still outstanding: the role of human agency, the meaning of social ties and the treatment of temporality.

This paper brings to fore current debates within the Network Analysis community, highlighting areas where future studies might contribute.

Technological innovations provide huge opportunities to expand and revolutionize the scope of products and services offered. This is particularly true for tourism, which is undergoing significant changes due to the development of new technologies. The level of technology diffusion depends on several factors like the exchange of information among peers, and the attitude and shared perception among the contributors. The aim of the study is to explore the diffusion of technology in tourism with a specific focus on the social media discourse around new technologies. Thus, the paper investigates the level of interest in these new technologies analysing the information exchange occurring between individuals on Twitter in order to explore the influence of reciprocal networking.

To capture the attitudes expressed in the industry, the study analyses the ongoing discourse on Twitter as a proxy for the participants “interest in new technologies. Through a social network analysis of the tweets and retweets conducted over a period of nine months, the research maps the level of information exchange about the diffusion of new technologies. Moreover, the sentiment analysis provides an interesting overview of the individuals” attitudes towards the awareness or the adoption of new technologies.

Our analysis has provided several insights: (1) the information network on blockchain in tourism consists of participants who change very quickly over time (high turnover of accounts); (2) some contributors have an extremely important role in influencing the flow of information in the system (information centralization), they can have a generalist (discussing several topics) or a specialist (focusing on a specific topic) behaviour and this strategic choice influences their network's structure; (3) these central nodes also have an impact on the definition of positive and negative sentiment towards a topic (sentiment influencer).

The paper contributes to the literature on technology diffusion, by focusing on one of the preconditions of diffusion that is the shared positive attitude towards technological innovation. More specifically, we adopt a network-based approach, which is useful to explain the level of information exchange and the public discourse that can impact the shared perception and attitude towards technological innovation. The study also highlights the role of knowledge brokers in influencing this public discourse. Future studies can deepen the association between positive perception, higher levels of information exchange and increasing usage of specific technologies. Our results also suggest further exploring the opportunity to combine social media data and other sources of information to shed more light on the technological innovation diffusion processes.

This paper shows how practitioners can benefit from the analysis of information exchange about new technologies in tourism adopting a network perspective with the aim of understanding the level of influence among contributors. Moreover, the increasing interest in blockchain technology and the potential combination between social media data and other sources of information can offer promising insights.

The present study explores the level of technology diffusion through the analysis of information exchange on social media (Twitter). Furthermore, the dynamics of individual user behaviour offers a better understanding about media effects.

While previous research is focused on the users' perception towards the development of new technologies in tourism, the aim of this study is to investigate the dynamics behind the level of diffusion of information and awareness about these new technologies, which still represents an unexplored area of research.

Social relationships play an important role in organizational entrepreneurship. They are crucial to entrepreneurs’ decisions because, despite the bleeding-edge technological advancements observed nowadays, entrepreneurs as human beings will always strive to be social. During the COVID-19 pandemic many companies moved activities into the virtual world and as a result offline Social relationships became rarer, but as it turns out, even more valuable, likewise, the inter-organizational cooperation enabling many companies to survive.

This chapter aims to develop knowledge about entrepreneurs’ SR and their links with inter-organizational cooperation. The results of an integrative systematic literature review show that the concept of Social relationships, although often investigated, lacks a clear definition, conceptualization, and operationalization. This chapter revealed a great diversity of definitions for Social relationships, including different scopes of meaning and levels of analysis. The authors identify 10 building blocks and nine sources of entrepreneurs’ Social relationships. The authors offer an original typology of Social relationships using 12 criteria. Interestingly, with regard to building blocks, besides those frequently considered such as trust, reciprocity and commitment, the authors also point to others more rarely and narrowly discussed, such as gratitude, satisfaction and affection. Similarly, the authors discuss the varied scope of sources, including workplace, family/friendship, past relationships, and ethnic or religious bonds. The findings of this study point to a variety of links between Social relationships and inter-organizational cooperation, including their positive and negative influences on one another. These links appear to be extremely dynamic, bi-directional and highly complex.

This chapter examines the structure and sentiment of the Twitter response to Nathan Broad's naming as the originator of an image-based sexual abuse incident following the 2017 Australian Football League Grand Final. Employing Social Network Analysis to visualize the hierarchy of Twitter users responding to the incident and Applied Thematic Analysis to trace the diffusion of differing streams of sentiment within this hierarchy, we produced a representation of participatory social media engagement in the context of image-based sexual abuse. Following two streams of findings, a model of social media user engagement was established that hierarchized the interplay between institutional and personal Twitter users. In this model, it was observed that the Broad incident generated sympathetic and compassionate discourses among an articulated network of social media users. This sentiment gradually diffused to institutional Twitter users – or Reference accounts – through the process of intermedia agenda-setting, whereby the narrative of terrestrial media accounts was altered by personal Twitter users over time.

The purpose of this paper is to use the practical application of tools provided by social network theory for the detection of potential influencers from the point of view of marketing within online communities. It proposes a method to detect significant actors based on centrality metrics.

A matrix is proposed for the classification of the individuals that integrate a social network based on the combination of eigenvector centrality and betweenness centrality. The model is tested on a Facebook fan page for a sporting event. NodeXL is used to extract and analyze information. Semantic analysis and agent-based simulation are used to test the model.

The proposed model is effective in detecting actors with the potential to efficiently spread a message in relation to the rest of the community, which is achieved from their position within the network. Social network analysis (SNA) and the proposed model, in particular, are useful to detect subgroups of components with particular characteristics that are not evident from other analysis methods.

This paper approaches the application of SNA to online social communities from an empirical and experimental perspective. Its originality lies in combining information from two individual metrics to understand the phenomenon of influence. Online social networks are gaining relevance and the literature that exists in relation to this subject is still fragmented and incipient. This paper contributes to a better understanding of this phenomenon of networks and the development of better tools to manage it through the proposal of a novel method.

In recent years, the proliferation of free trade agreements (FTA) has led to rapid economic boons and political security among nations. This study investigates whether the percentage of expats or permanent foreign residents plays a role in deciding which countries to partner with in bi-lateral FTAs. Previously, the reasons for FTA formation were believed to be primarily based upon economic, geographic, and political reasons. However, through the use of social network analysis, a larger picture can be mapped which allows for a more comprehensive understanding of key players in the current state of FTA formation in relation to the immigrant network that they share between them. More specifically, through computerized social network analysis, centrality can be calculated to determine the key players and the most central immigrant populations. When analyzing both the immigrant centrality in relation to FTA centrality, it becomes evident that there is a high correlation between the two factors. Thus, the findings highlight that immigration trends can be used as a predictor of FTA formation. As a result, it emphasizes the weight of immigration policy on the formation of bi-lateral FTAs.

Digital markets are increasingly constructed by an interplay between (non)human market actors, i.e. through algorithms, but, simultaneously, fragmented through platformization. This study aims to explore how interactional dynamics between (non)human market actors co-codify markets through expressive and networked content across social media platforms.

This study applies digital methods as cross-platform analysis to analyze two data sets retrieved from YouTube and Instagram using the keywords “sustainable fashion” and #sustainablefashion, respectively.

The study shows how interactional dynamics between (non)human market actors, co-codify markets across two social media platforms, i.e. YouTube and Instagram. The authors introduce the notion of sticky market webs of connection, illustrating how these dynamics foster cross-platform market codification through relations of exteriority.

Research implications highlight the necessity to account for all involved entities, including digital infrastructure in digital markets and the methodological potential of cross-platform analyses.

Practical implications highlight considerations managers should take into account when designing market communication for digital markets composed of (non)human market actors.

Social implications highlight the possible effects of (non)human market co-codification on markets and consumer culture, and corresponding countermeasures.

This study contributes to an increased understanding of digital market dynamics by illuminating interdependent market co-codification dynamics between (non)human market actors, and how these dynamics (de)territorialize digital market assemblages through relations of exteriority across platforms.

The purpose of this paper is to have a review on the analysis of information diffusion based on evolutionary game theory. People now get used to interact over social networks, and one of the most important functions of social networks is information sharing. Understanding the mechanisms of the information diffusion over social networks is critical to various applications including online advertisement and rumor control.

It has been shown that the graphical evolutionary game theory (EGT) is a very efficient method to study this problem.

By applying EGT to information diffusion, the authors could predict every small change in the process, get the detailed dynamics and finally foretell the stable states.

In this paper, the authors provide a general review on the evolutionary game-theoretic framework for information diffusion over social network by summarizing the results and conclusions of works using graphical EGT.

Technology-based incubators depend on high-level knowledge to constantly meet the demands of the market. Incubators offer a variety of specialized services to help startups increase the chances of crossing the valley of death. These services include infrastructure, access to a professional network of mentors and an intensive support of a consultant team to help with managerial and legal challenges. Therefore, it is critical to incubators to develop both highly skilled teams of consultants and social environment that facilitates communication. The purpose of this paper is to understand how innovation-oriented social networks created within technology-based incubators are shaped.

Data were collected in five incubators participating connected to federal universities from the state of Minas Gerais. The network attributes collected in the survey were placed in a matrix form. The mapping and measurement of the relationships between individuals were developed using the Ucinet software. Ucinet enables the analysis of attributes (attitudes, behaviors and characteristics) characterized as relational (contacts, ties and relationships). The software also includes the Netdraw network visualization tool, which enables the creation of matrices and graphical network maps. The measurements of centrality, closeness and intermediation were analyzed to assess the intra-organizational social network.

The results indicate that although the flow of communication does not follow the formal hierarchy, the interaction between team members to spontaneously exchange ideas, information and experiences is rare. The workers are so concerned about their timely tasks, that they have few opportunities to exchange information and knowledge. The coordination is carried out by university professors, who also perform other tasks (e.g. teaching, research and administration activities) besides those related to the incubators. The results also suggest that in the technology-based incubators studied, besides dealing in an innovative environment, the distribution of tasks and responsibilities are still rigid and traditional.

By analyzing the degree of the relationship between team members, the proximity and the level of intermediation of co-workers, it is possible to see how the incubators workers interact, thereby identifying the flow of information. This study offers implications for theory and practice. To the theory, this study adds to the discussion of intra-organizational social network of technology-based companies in the Brazilian context. To practitioners, this research sheds light on the importance of the social network built within the organization to promote effective communication and knowledge sharing.

This study aims to examine the associations of social networks with the sense of community (SOC) construct and spatial colocation or having an office. The study site was an institute for health-care policy research formed in 2011 by bringing together scientists from more than 20 different university units. Only 30% of the scientists were had an office or physical presence at the institute. Therefore, the institute was an ideal site to examine whether SOC was correlated with different dimensions of network position – connectedness, reachability and brokerage – even when the authors account for the lack of spatial colocation for the off-site scientists.

A two-part (sociometric and workplace) internet survey instrument was administered in 2014 to the institute’s population of 411 individuals. The sociometric data were used to create an undirected interaction network and the following dependent variables (DVs) or network centralities: normalized degree to measure connectedness; average reciprocal distance to capture reachability; and normalized betweenness to proxy brokerage. Separate node-level network regressions were then run with random permutations (N = 10,000) and listwise deletion for each of the DVs with SOC and spatial colocation as the independent variables, and variables that controlled for gender, organizational affiliation and job category.

SOC and spatial colocation are both positively and significantly correlated with network connectedness and reachability. The results suggest that both SOC and spatial colocation have a larger impact on reachability than connectedness. However, neither SOC nor spatial colocation are significantly associated with network brokerage. Finally, the findings show that SOC and spatial colocation are more reliable predictors of network connectedness and reachability than are key individual- and unit-level control variables, specifically the individual’s sex, job category and organizational affiliation. The controls were not significantly associated with any of the three network centralities, namely, connectedness, reachability and brokerage.

This exploratory study used social network analysis and node-level network regressions to examine the associations from SOC and spatial colocation to dimensions of network position. SOC is positively and significantly associated with network connectedness and reachability, suggesting that SOC is an important consideration when individuals are disadvantaged from the absence of spatial colocation. The findings have implications for work in the context of the COVID-19 pandemic as they imply that interventions based on the SOC construct could potentially lessen the negative effects of remote work on workplace social networks due to factors such as the reduction of social contacts.