Search results
1 – 10 of over 11000Huasi Xu, Yidi Liu, Bingqing Song, Xueyan Yin and Xin Li
Drawing on social network and information diffusion theories, the authors study the impact of the structural characteristics of a seller’s local social network on her promotion…
Abstract
Purpose
Drawing on social network and information diffusion theories, the authors study the impact of the structural characteristics of a seller’s local social network on her promotion effectiveness in social commerce.
Design/methodology/approach
The authors define a local social network as one formed by a focal seller, her directly connected users and all links among these users. Using data from a large social commerce website in China, the authors build econometric models to investigate how the density, grouping and centralization of local social networks affect the number of likes received by products posted by sellers.
Findings
Local social networks with low density, grouping and centralization are associated with more likes on sellers’ posted products. The negative effects of grouping and centralization are reduced when density is high.
Originality/value
The paper deepens the understanding of the determinants of social commerce success from a network structure perspective. In particular, it draws attention to the role of sellers’ local social networks, forming a foundation for future research on social commerce.
Details
Keywords
Miao Ye, Lin Qiang Huang, Xiao Li Wang, Yong Wang, Qiu Xiang Jiang and Hong Bing Qiu
A cross-domain intelligent software-defined network (SDN) routing method based on a proposed multiagent deep reinforcement learning (MDRL) method is developed.
Abstract
Purpose
A cross-domain intelligent software-defined network (SDN) routing method based on a proposed multiagent deep reinforcement learning (MDRL) method is developed.
Design/methodology/approach
First, the network is divided into multiple subdomains managed by multiple local controllers, and the state information of each subdomain is flexibly obtained by the designed SDN multithreaded network measurement mechanism. Then, a cooperative communication module is designed to realize message transmission and message synchronization between the root and local controllers, and socket technology is used to ensure the reliability and stability of message transmission between multiple controllers to acquire global network state information in real time. Finally, after the optimal intradomain and interdomain routing paths are adaptively generated by the agents in the root and local controllers, a network traffic state prediction mechanism is designed to improve awareness of the cross-domain intelligent routing method and enable the generation of the optimal routing paths in the global network in real time.
Findings
Experimental results show that the proposed cross-domain intelligent routing method can significantly improve the network throughput and reduce the network delay and packet loss rate compared to those of the Dijkstra and open shortest path first (OSPF) routing methods.
Originality/value
Message transmission and message synchronization for multicontroller interdomain routing in SDN have long adaptation times and slow convergence speeds, coupled with the shortcomings of traditional interdomain routing methods, such as cumbersome configuration and inflexible acquisition of network state information. These drawbacks make it difficult to obtain global state information about the network, and the optimal routing decision cannot be made in real time, affecting network performance. This paper proposes a cross-domain intelligent SDN routing method based on a proposed MDRL method. First, the network is divided into multiple subdomains managed by multiple local controllers, and the state information of each subdomain is flexibly obtained by the designed SDN multithreaded network measurement mechanism. Then, a cooperative communication module is designed to realize message transmission and message synchronization between root and local controllers, and socket technology is used to ensure the reliability and stability of message transmission between multiple controllers to realize the real-time acquisition of global network state information. Finally, after the optimal intradomain and interdomain routing paths are adaptively generated by the agents in the root and local controllers, a prediction mechanism for the network traffic state is designed to improve awareness of the cross-domain intelligent routing method and enable the generation of the optimal routing paths in the global network in real time. Experimental results show that the proposed cross-domain intelligent routing method can significantly improve the network throughput and reduce the network delay and packet loss rate compared to those of the Dijkstra and OSPF routing methods.
Details
Keywords
Hua Pang, Enhui Zhou and Yi Xiao
In light of the stimulus-organism-response (SOR) theoretical paradigm, this paper explores how information relevance and media richness affect social network exhaustion and…
Abstract
Purpose
In light of the stimulus-organism-response (SOR) theoretical paradigm, this paper explores how information relevance and media richness affect social network exhaustion and, moreover, how social network exhaustion ultimately leads to health anxiety and COVID-19-related stress.
Design/methodology/approach
The conceptual model is explicitly analyzed and estimated by using data from 309 individuals of different ages in mainland China. Confirmatory factor analysis (CFA) and structural equation modeling (SEM) were utilized to validate the proposed hypotheses through the use of online data.
Findings
The findings suggest that information relevance is negatively associated with social network exhaustion. In addition, social network exhaustion is a significant predictor of health anxiety and stress. Furthermore, information relevance and media richness can indirectly influence health anxiety and stress through the mediating effect of social network exhaustion.
Research limitations/implications
Theoretically, this paper verifies the causes and consequences of social network exhaustion during COVID-19, thus making a significant contribution to the theoretical construction and refinement of this emerging research area. Practically, the conceptual research model in this paper may provide inspiration for more investigators and scholars who are inclined to further explore the different dimensions of social network exhaustion by utilizing other variables.
Originality/value
Although social network exhaustion and its adverse consequences have become prevalent, relatively few empirical studies have addressed the deleterious effects of social network exhaustion on mobile social media users’ psychosocial well-being and mental health during the prolonged COVID-19. These findings have important theoretical and practical implications for the rational development and construction of mobile social technologies to cultivate proper health awareness and mindset during the ongoing worldwide COVID-19 epidemic.
Details
Keywords
Yafei Feng, Yan Zhang and Lifu Li
The privacy calculus based on a single stakeholder failed to explain users' co-owned information disclosure owing to the uniqueness of co-owned information. Drawing on collective…
Abstract
Purpose
The privacy calculus based on a single stakeholder failed to explain users' co-owned information disclosure owing to the uniqueness of co-owned information. Drawing on collective privacy calculus theory and impression management theory, this study attempts to explore the co-owned information disclosure of social network platform users from a collective perspective rather than an individual perspective.
Design/methodology/approach
Drawing on collective privacy calculus theory and impression management theory, this study explores the co-owned information disclosure of social network platform users from a collective perspective rather than an individual perspective based on a survey of 740 respondents.
Findings
This study finds that self-presentation and others presentation directly positively affect users' co-owned information disclosure. Also, self-presentation, others presentation and relationship presentation indirectly positively affect users' co-owned information disclosure via relationship support. Furthermore, personal privacy concern, others' privacy concern and relationship privacy concern indirectly negatively affect users' co-owned information disclosure via relationship risk.
Originality/value
The findings develop the theory of collective privacy calculus and impression management, which offer insights into the design of the collective privacy protection function of social network platform service providers.
Details
Keywords
Aysu Göçer, Ceren Altuntas Vural and Frida Lind
This study aims to explore how a start-up entering maritime logistics networks (MLNs) in the container shipping industry integrates resources underlying value cocreation patterns…
Abstract
Purpose
This study aims to explore how a start-up entering maritime logistics networks (MLNs) in the container shipping industry integrates resources underlying value cocreation patterns in these networks.
Design/methodology/approach
The paper is based on a single case study of a technological start-up, providing tracking, tracing and other information services to MLN members using internet-based software. An interorganizational theory perspective informs the case study to unveil the resource integration for value cocreation in the network.
Findings
The start-up holds multiple resource interaction roles and the start-up’s involvement enables the creation of new knowledge resources, which facilitate new revenue streams and manage resource dependencies. Hence, the findings indicate that the start-up changes value cocreation patterns in the network by reconfiguring and integrating existing resources so that the service is customized for various customers, including shippers and freight forwarders.
Practical implications
The results provide insights about how technological start-ups can unlock resources within MLNs.
Originality/value
The study extends previous studies on resource roles in business networks and shows how start-ups can perform multiple roles simultaneously within these networks. In addition, the study contributes to the literature by studying information and knowledge as resources configured in different ways in a unique network setting.
Details
Keywords
Yandong Hou, Zhengbo Wu, Xinghua Ren, Kaiwen Liu and Zhengquan Chen
High-resolution remote sensing images possess a wealth of semantic information. However, these images often contain objects of different sizes and distributions, which make the…
Abstract
Purpose
High-resolution remote sensing images possess a wealth of semantic information. However, these images often contain objects of different sizes and distributions, which make the semantic segmentation task challenging. In this paper, a bidirectional feature fusion network (BFFNet) is designed to address this challenge, which aims at increasing the accurate recognition of surface objects in order to effectively classify special features.
Design/methodology/approach
There are two main crucial elements in BFFNet. Firstly, the mean-weighted module (MWM) is used to obtain the key features in the main network. Secondly, the proposed polarization enhanced branch network performs feature extraction simultaneously with the main network to obtain different feature information. The authors then fuse these two features in both directions while applying a cross-entropy loss function to monitor the network training process. Finally, BFFNet is validated on two publicly available datasets, Potsdam and Vaihingen.
Findings
In this paper, a quantitative analysis method is used to illustrate that the proposed network achieves superior performance of 2–6%, respectively, compared to other mainstream segmentation networks from experimental results on two datasets. Complete ablation experiments are also conducted to demonstrate the effectiveness of the elements in the network. In summary, BFFNet has proven to be effective in achieving accurate identification of small objects and in reducing the effect of shadows on the segmentation process.
Originality/value
The originality of the paper is the proposal of a BFFNet based on multi-scale and multi-attention strategies to improve the ability to accurately segment high-resolution and complex remote sensing images, especially for small objects and shadow-obscured objects.
Details
Keywords
Thi Huyen Pham, Thuy-Anh Phan, Phuong-Anh Trinh, Xuan Bach Mai and Quynh-Chi Le
This study aims to ascertain the impact of data collecting awareness on perceived information security concerns and information-sharing behavior on social networking sites.
Abstract
Purpose
This study aims to ascertain the impact of data collecting awareness on perceived information security concerns and information-sharing behavior on social networking sites.
Design/methodology/approach
Based on communication privacy management theory, the study forecasted the relationship between information-sharing behavior and awareness of data collecting purposes, data collection tactics and perceived security risk using structural equation modeling analysis and one-way ANOVA. The sample size of 521 young social media users in Vietnam, ages 18 to 34, was made up of 26.7% men and 73.3% women. When constructing the questionnaire survey method with lone source respondents, the individual’s unique awareness and experiences with using online social networks (OSNs) were taken into account.
Findings
The results of the investigation demonstrate a significant relationship between information-sharing and awareness of data collecting, perceptions of information security threats and behavior. Social media users have used OSN privacy settings and paid attention to the sharing restriction because they are concerned about data harvesting.
Research limitations/implications
This study was conducted among young Vietnamese social media users, reflecting specific characteristics prevalent in the Vietnamese environment, and hence may be invalid in other nations’ circumstances.
Practical implications
Social media platform providers should improve user connectivity by implementing transparent privacy policies that allow users to choose how their data are used; have clear privacy statements and specific policies governing the use of social media users’ data that respect users’ consent to use their data; and thoroughly communicate how they collect and use user data while promptly detecting any potential vulnerabilities within their systems.
Originality/value
The authors ascertain that the material presented in this manuscript will not infringe upon any statutory copyright and that the manuscript will not be submitted elsewhere while under Journal of Information, Communication and Ethics in Society review.
Details
Keywords
Cong Liu, Jiming Cao, Kaifeng Duan and Guangdong Wu
This study investigates the impact of network positions on inter-team conflicts and project success in megaprojects.
Abstract
Purpose
This study investigates the impact of network positions on inter-team conflicts and project success in megaprojects.
Design/methodology/approach
Network position is measured with centrality and structural holes. Substantive conflict and affective conflict reflect inter-team conflicts. A questionnaire survey was implemented in Chinese megaprojects, and 309 valid questionnaires were collected. The data were analyzed using structural equation modeling and bootstrapping methods.
Findings
The results show that centrality negatively impacts project success, while the presence of a team in a structural hole has no significant impact on project success. Centrality is negatively related to substantive conflict and is positively related to affective conflict. The team in a structural hole has a positive effect on substantive conflict and a negative effect on affective conflict. Substantive conflict and affective conflict have positive and negative effects on project success, respectively. The effect of network position on project success is mediated by inter-team conflict.
Research limitations/implications
This research provides a reference for megaproject managers to better conduct network governance, manage inter-team conflict, and successfully manage projects. The study did not investigate the effects of changes in teams' network positions on project success. Future research should explore this facet of megaprojects.
Originality/value
This research adds to existing research on network position, and reveals that project network governance is important for megaproject success. This provides a new direction for megaproject management. Furthermore, the results validate constructive and non-constructive roles and the mediating role of inter-team conflict. This complements the literature on conflict management, providing a reference for megaproject managers when managing inter-team conflict.
Details
Keywords
The study investigates the information-related challenges as well as the practices adopted by early-career researchers during transitions between roles and institutions. Its…
Abstract
Purpose
The study investigates the information-related challenges as well as the practices adopted by early-career researchers during transitions between roles and institutions. Its primary goal is to delve into how information behaviors serve as scaffolding during significant life shifts. Moreover, the research aims to provide actionable insights based on this scaffolding concept for individuals navigating transitions.
Design/methodology/approach
This preliminary and exploratory study took a phenomenological approach to examine the role of information seeking and personal information management (PIM) behaviors during life transitions. In-depth semi-structured interviews were held with 15 early-career researchers from various disciplines, who were about to finish their PhDs or had recently graduated.
Findings
By employing information seeking and PIM practices, participants were able to address three main information challenges that arose during the transition process: the timing of information behavior, the nature of information and the social components of the transition. The use of networked and independent information seeking/validation practices enabled to establish a sustainable network of transition-related information, reducing uncertainty. PIM practices helped planning the transition, maintaining information over the long-term and gaining control over personal information.
Originality/value
This study underscores the significance of information behaviors, encompassing both information seeking and PIM, as scaffolding mechanisms during crucial life transitions. It offers essential insights that can guide the creation of impactful interventions and resources. Additionally, the research illuminates the pressing demand for more in-depth exploration in this domain.
Details
Keywords
Yongwon Kim, Inwook Song and Young Kyu Park
Using overlapped portfolio data on public equity funds in Korea, the authors construct several types of fund-stock weighted bipartite networks and measure fund network centrality…
Abstract
Using overlapped portfolio data on public equity funds in Korea, the authors construct several types of fund-stock weighted bipartite networks and measure fund network centrality. The authors also examine the relationship between network centrality and fund investment performance. The authors' results are three-fold. First, the authors find that the fund centrality of the network in which funds and stocks are connected based on the most active investing behavior positively affects the fund performance. Second, the funds with a high centrality level based on the same network generate higher returns by holding stocks with high value uncertainty. Third, the authors find that fund centrality is not associated with herd behavior. Based on these results, the authors argue that fund centrality is a proxy of information advantage and skill of fund managers. The authors' paper shows that network analysis could be a new way to identify funds with better performance and measure the skill and information advantage to construct an optimal portfolio.
Details