Search results

Current models of transaction credit in the e-commerce network face many problems, such as the one-sided measurement, low accuracy and insufficient anti-aggression solutions. This paper aims to address these problems by studying the transaction credit problem in the crowd transaction network.

This study divides the transaction credit into two parts, direct transaction credit and recommended transaction credit, and it proposes a model based on the crowd transaction network. The direct transaction credit comprehensively includes various factors influencing the transaction credit, including transaction evaluation, transaction time, transaction status, transaction amount and transaction times. The recommendation transaction credit introduces two types of recommendation nodes and constructs the recommendation credibility for each type. This paper also proposes a “buyer + circle of friends” method to store and update the transaction credit data.

The simulation results show that this model is superior with high accuracy and anti-aggression.

The direct transaction credit improves the accuracy of the transaction credit data. The recommendation transaction credit strengthens the anti-aggression of the transaction credit data. In addition, the “buyer + circle of friends” method fully uses the computing of the storage ability of the internet, and it also solves the failure problem of using a single node.

This paper aims to investigate how actors in the farmer’s network influence the adoption of smart farming technology (SFT) and to understand how social media affects this adoption process, in particular focusing on the influence of social media on trust in knowledge dissemination within the network.

The methodology used a two-stage process, with semi-structured interviews of farmers, augmented by a netnographic approach appropriate to the social media context.

The analysis illustrates the key role of the farmer network in the dissemination of SFT knowledge, bringing insight into an important B2B context. While social media emerges as a valuable way to connect farmers and promote discussion, it remains underused in knowledge dissemination on SFT. Also, farmers exhibit more trust in the content from peers online rather than from SFT vendors.

Novel insights are gained into the influence of the farming network on the accelerated adoption of SFT, including the potential role of social media in mitigating the homophilous nature of peer-to-peer interactions among farmers through exposure to more diverse actors and information. The use of a social network theory lens has provided new insights into the role of trust in shaping social media influence on the farmer, with variances in farmer trust of information from technology vendors and from peers.

In this study, the authors sought to investigate how the implicit social ties of both project owners and potential backers are associated with crowdfunding project success.

Drawing on social ties theory and factors that affect crowdfunding success, in this research, the authors developed a model to study how project owners' and potential backers' implicit social ties are associated with crowdfunding projects' degrees of success. The proposed model was empirically tested with crowdfunding data collected from Kickstarter and social media data collected from Twitter. The authors performed the test using an ordinary least squares (OLS) regression model with fixed effects.

The authors found that project owners' implicit social ties (specifically, their social media activities, degree centrality and betweenness centrality) are significantly and positively associated with crowdfunding projects' degrees of success. Meanwhile, potential project backers' implicit social ties (their social media activities and degree centrality) are negatively associated with crowdfunding projects' degrees of success. The authors also found that project size moderates the effects of project owners' social media activities on projects' degrees of success.

This work contributes to the literature on crowdfunding by investigating how the implicit social ties of both potential backers and project owners on social media are associated with crowdfunding project success. This study extends the previous research on social ties' roles in explaining crowdfunding project success by including implicit social ties, while the literature explored only explicit social ties.

This paper aims to investigate the influence of trust on adopting and implementing blockchain technology in higher education institutions (HEIs) in Brazil.

This study uses an exploratory qualitative approach to understand the construct of trust in the context of the educational sector. Data were collected through semistructured questionnaires and online interviews.

The research identified that, for most potential blockchain users, trust positively influences the HEIs, because benefits such as secure data sharing and transaction transparency could optimize the daily routine and avoid fraud in academic documents, providing a cooperative and reliable working environment. In addition, the results suggest that trust is needed to overcome challenges related to issues such as costs and privacy.

This study contributes to the advances in the emerging literature on blockchain in the educational sector as a system with the potential to generate trust, as well as the literature on the technology acceptance models.

For HEI managers and practitioners, this study highlights the need for a greater understanding of the influence of trust in the relationships between HEIs and other stakeholders.

This work shows that adopting blockchain technologies would allow users to build social relationships of trust in a cooperative work environment and develop trusted behavior by sharing data securely and transparently.

To the best of the authors’ knowledge, this is one of the first studies on the adoption and implementation of blockchain in the education sector in Brazil.

The study aims to demonstrate that farmers' markets can represent a model of environmental, social and governance reference for modern agri-food systems facing the challenge of post COVID-19 pandemic reconstruction, responding to consumer expectations in terms of health, safety and wholesomeness of agri-food products.

A sample of consumers was surveyed in farmers' markets and social network analysis (SNA) was adopted as a methodological approach to reconstruct the links between the worlds of production and consumption and to derive the relative importance attributed to various factors that promote relational structures.

The work demonstrates the importance of sustainability – as a productive and behavioural model of firms – for the construction of efficient and durable relationship systems in two farmer markets in Sicily. In particular, four fundamental components emerge in the construction of networks represented by consumer sensitivity to sustainability processes, the individual behavioural model of purchasing and consumption, the expectation of political direction and the level and factors of knowledge of the firm. The clustering elements of the relationships were found to be the territory and local products, the environmentalist attitude and the protection of resources, as well as the adoption of a rational waste disposal policy, the fight against food waste, the encouragement of healthier and more sustainable consumption styles, clear and transparent communication and the activation of sustainable supply chain processes in line with the Sustainable Development Goals (SDGs).

The paper aims to demonstrate how alternative food systems can become a useful model for large enterprises, which are committed to rebuilding their business strategy to overcome the current crisis.

The purpose of the study is to explore, with anchorage in theories about the normalization of corruption, under what conditions blockchain technology can mitigate corruptive practices of multinational enterprises (MNEs) in emerging markets (EMs).

By synthesizing a technological perspective and theory on corruption, the authors examine the feasibility of blockchain for fighting corruption in MNEs’ business operations in EMs.

Blockchain technology is theorized to have varying mitigating effects on the rationalization, socialization and institutionalization of corruption. The authors provide propositions describing the effects and the limitations of blockchain for mitigating corruption in EMs.

This paper offers a perspective for how to tackle acute business problems and social problems pronounced in international business but also prevailing elsewhere.

The study contributes to literature in international management by systematically exploring how and under what conditions blockchain can mitigate the normalization of corruption.

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.

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 this article we aim to understand how the network formed by fitness tracking devices and associated apps as a subset of the broader health-related Internet of things is capable of spreading information.

The authors used a combination of a content analysis, network analysis, community detection and simulation. A sample of 922 health-related apps (including manufacturers' apps and developers) were collected through snowball sampling after an initial content analysis from a Google search for fitness tracking devices.

The network of fitness apps is disassortative with high-degree nodes connecting to low-degree nodes, follow a power-law degree distribution and present with low community structure. Information spreads faster through the network than an artificial small-world network and fastest when nodes with high degree centrality are the seeds.

This capability to spread information holds implications for both intended and unintended data sharing.

The analysis confirms and supports evidence of widespread mobility of data between fitness and health apps that were initially reported in earlier work and in addition provides evidence for the dynamic diffusion capability of the network based on its structure. The structure of the network enables the duality of the purpose of data sharing.

This study describes and analyzes the output of academic research on the topic of social capital. The concept of social capital has attracted the interest of scholars from a range of academic disciplines, and it has been applied to explain a variety of phenomena.

Using the bibliographic approach, I analyzed aggregate data obtained from the Web of Science database. The analyses were carried out using VOSviewer software.

The results show social capital to be a topic of interest in multiple fields of academic research. The findings highlight the important role that journals, including those from disciplines other than the social sciences, have played in divulging this concept, and show that some countries and institutions are more productive and engage in more collaborative research efforts than others.

The main implications of this study regard research on social capital. The results demonstrate how social capital continues to interest scholars from a variety of academic disciplines. Future bibliometric research should include other sources (literature databases) and be expanded to consider other types of publication.

This paper furthers previous research by exclusively focusing on the concept of social capital. It analyzes the international trend in publications up until the end of 2021, thus expanding the publication period considered in previous studies. The results of this study highlight the relevance of bibliometric tools for assessing research performance.