Factors Affecting Individual Level ERP Assimilation in a Social Network Perspective

2017 ◽  
Vol 25 (3) ◽  
pp. 21-39 ◽  
Author(s):  
Luan Gao ◽  
Luning Liu ◽  
Yuqiang Feng
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Interactive Learning ◽  
Influential Factors ◽  
Three Dimensions ◽  
Organizational Level ◽  
Key Factors ◽  
Factors Affecting ◽  
Individual Level ◽  
The Social

Prior research on ERP assimilation has primarily focused on influential factors at the organizational level. In this study, the authors attempt to extend their understanding of individual level ERP assimilation from the perspective of social network theory. They designed a multi-case study to explore the relations between ERP users' social networks and their levels of ERP assimilation based on the three dimensions of the social networks. The authors gathered data through interviews with 26 ERP users at different levels in five companies. Qualitative analysis was used to understand the effects of social networks and interactive learning. They found that users' social networks play a significant role in individual level ERP assimilation through interactive learning among users. They also found five key factors that facilitate users' assimilation of ERP knowledge: homophily (age, position and rank), tie content (instrumental and expressive ties), tie strength, external ties, and centrality.

Multilevel Visualization Using Enhanced Social Network Analysis with Smartphone Data

2013 ◽  
Vol 5 (4) ◽  
pp. 34-54 ◽  
Author(s):  
Panagiotis Andriotis ◽  
Zacharias Tzermias ◽  
Anthi Mparmpaki ◽  
Sotiris Ioannidis ◽  
George Oikonomou
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Online Social Networks ◽  
Direct Marketing ◽  
Forensic Analysis ◽  
Three Dimensions ◽  
Fully Integrated ◽  
Aggregate Information ◽  
The Social ◽  
Correlated Information

While technology matures and becomes more productive, mobile devices can be affordable and, consequently, fully integrated in people's lives. After their unexpected bloom and acceptance, Online Social Networks are now sources of valuable information. The authors therefore use them for tasks varying from direct marketing to forensic analysis. The authors have already seen Social Network Forensics techniques focused on particular networks implementing methods that collect data from user accounts. During the forensic analysis it is common to aggregate information from different sources but, usually, this procedure causes correlation problems. Here, the authors present their method to correlate data gathered from various social networks in combination with smartphones creating a new form of social map of the user under investigation. In addition, the authors introduce a multi level graph that utilises the correlated information from the smartphone and the social networks and demonstrates in three dimensions the relevance of each contact with the suspect.

scholarly journals Factors Affecting Loyalty of Mobile Social Networks' Users

2017 ◽  
Vol 13 (1) ◽  
pp. 66-81 ◽  
Author(s):  
Nastaran Hajiheydari ◽  
Babak Hazaveh Hesar Maskan ◽  
Mahdi Ashkani
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Structural Equation ◽  
Online Survey ◽  
Equation Modeling ◽  
Mobile Social Networks ◽  
Mobile Social Network ◽  
Key Factors ◽  
Factors Affecting ◽  
Social Applications

Increasing world-wide trends of using mobile social networks and the rise of competition between different social applications makes it essential for social network providers and marketers to identify the key factors leading to user loyalty. The purpose of this paper is to identify the key factors that affect the loyalty of mobile social networks users. The proposed model was tested through structural equation modeling techniques and an online survey. The sample consisted of 388 mobile social networks users in Iran. The results indicate that sociability, entertainment and fashion are primary drivers of attitude toward a mobile social network. The results also show the significant role of attitude and satisfaction on consumer loyalty. This study helps both marketers and mobile social network providers know the key drivers of customer loyalty in order to tailor their marketing efforts and communication strategies.

Evaluation of Social Network Sites

2013 ◽  
Vol 3 (4) ◽  
pp. 28-42
Author(s):  
Francisco J. Miranda ◽  
Antonio Chamorro ◽  
Sergio Rubio
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Delphi Study ◽  
Active Form ◽  
Three Dimensions ◽  
Assessment Index ◽  
General Terms ◽  
The Social ◽  
Important Challenge ◽  
Marketing Tool

Social networks are one of the more notable sociological phenomena of the last years. Moreover, its apparition and acceptance by majority of the citizens also suppose an important challenge for the firms. Social networks are a new and relevant channel of communication and interaction with their consumers. For this, firms have to create his own place in the social network and manage of active form the content that shares and the dialogue that is supported by their followers. In the first part of this paper we explain the creation of an index to evaluate the presence of the companies in the social network more used to international level, Facebook. The Facebook Assessment Index (FAI) is formed by several indicators grouped in three dimensions: popularity, interactivity and content. The weights for each category were obtained as recommended by a Delphi study conducted with 10 independent experts (community managers and internet marketing experts). In the second part, we applied this index to the 150 largest firms according to Fortune 2011 ranking. At present, only 44% of these firms tested had an international official Facebook page. The results showed that the larger firms are those that in general terms best manage their presence on Facebook, have the greatest number of followers and a higher degree of interactivity with them. However, the most interesting contribution of this work lies not in identifying firms that achieve higher scores on the FAI, but in comparing the pages with each other and making suggestions of ideas and practices that may improve a firm's Facebook presence as a marketing tool.

Research on Traveling Behavior Based on Social Network Platform

2014 ◽  
Vol 687-691 ◽  
pp. 1762-1765
Author(s):  
Bao Ding Sun
Keyword(s):  
Social Networks ◽  
Social Media ◽  
Social Network ◽  
Influential Factors ◽  
The Social ◽  
Behavior Based ◽  
Network Platform ◽  
Tourism Enterprises ◽  
Developing Pattern

Due to the emergence of social media in the field of Internet , the structure of tourism as well as its developing pattern has changed a lot, the application of social media enabled the tourists who can take part in more traveling information to exchange ideas. It also can influence the character of the traditional traveling consumers' behavior by the subtle changes in tourism. In this paper, with the analysis of the consumer's behaving habits of using social network platform, it explored the influential factors that contributed to the tourism enterprises, which can be beneficial for making the traveling decisions through the social networks platform.

scholarly journals MAPPING FEAR OF CRIME THROUGH SOCIAL NETWORK MODEL

2020 ◽  
Vol 3 (2) ◽  
pp. 135-150
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Network Model ◽  
Criminal Behavior ◽  
Fear Of Crime ◽  
Control Mechanism ◽  
Binary Logistic Regression ◽  
Three Dimensions ◽  
The Social ◽  
Private And Public

The present study analyzes fear of crime through social network model. The social network model is delimited to three dimensions i.e., private social network (PrSN), parochial social network (PaSN), and public social network (PbSN). The association and contribution of each of the dimension is estimated through binary logistic regression. Data for the study is collected from 298 out of 1186 employees and students of the Main Campus of Abdul Wali Khan University Mardan, Khyber Pakhtunkhwa-Pakistan. Findings of the study show that the three dimensions are inversely related to the fear of crime. It means that improvement in private, parochial, and public social networks reduces fear of crime. Further, it is observed that private and public social networks are contributing more than parochial social network in reducing fear of crime in Pakhtun society of district Mardan. Thus, it is inferred that social networks through the development of a sense of empowerment among the members decrease fear of crime. Stronger social networks act as a social control mechanism and reduce the likelihood of the occurrence of deviant, and/or criminal behavior in a society

Facebook as a Marketing Tool

2014 ◽  
Vol 6 (4) ◽  
pp. 14-28 ◽  
Author(s):  
Antonio Chamorro-Mera ◽  
F. Javier Miranda ◽  
Sergio Rubio
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Three Dimensions ◽  
Assessment Index ◽  
General Terms ◽  
The Social ◽  
Interesting Contribution ◽  
Important Challenge ◽  
Marketing Tool ◽  
High Degree

Social networks are one of the more notable sociological phenomena of the last years. Moreover, its apparition and acceptance by majority of the citizens also suppose an important challenge for the firms. Social networks are a new and relevant channel of communication and interaction with their consumers. For this, firms have to create their own place in the social network and actively manage the content that shares and the dialogue that is supported by their followers. In the first part of this paper, the authors explain the creation of an index to evaluate the presence of the companies in the social network more used to international level, Facebook. The Facebook Assessment Index (FAI) is formed by several indicators grouped in three dimensions: popularity, interactivity, and content. In the second part, the authors applied this index to the 150 largest firms according to Fortune 2011 ranking. At present, only 44% of these firms tested had an international official Facebook page. The results showed that the larger firms are those that in general terms best manage their presence on Facebook, have the greatest number of followers and a high degree of interactivity with them. However, the most interesting contribution of this work lies not in identifying firms that achieve higher scores on the FAI, but in comparing the pages with each other and making suggestions of ideas and practices that may improve a firm's Facebook presence as a marketing tool.

Emotive Trending And Tracking of Tweets

2017 ◽  
Vol 7 (11) ◽  
pp. 25
Author(s):  
Sanjay Chhataru Gupta
Keyword(s):  
Social Networks ◽  
Social Media ◽  
Social Network ◽  
The Social ◽  
The World ◽  
Complex Events

Popularity of the social media and the amount of importance given by an individual to social media has significantly increased in last few years. As more and more people become part of the social networks like Twitter, Facebook, information which flows through the social network, can potentially give us good understanding about what is happening around in our locality, state, nation or even in the world. The conceptual motive behind the project is to develop a system which analyses about a topic searched on Twitter. It is designed to assist Information Analysts in understanding and exploring complex events as they unfold in the world. The system tracks changes in emotions over events, signalling possible flashpoints or abatement. For each trending topic, the system also shows a sentiment graph showing how positive and negative sentiments are trending as the topic is getting trended.

The Oxford Handbook of Social Networks

2020 ◽  
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Social Life ◽  
Information Science ◽  
Computational Social Science ◽  
The Social ◽  
Diverse Field ◽  
The Rich

Social networks fundamentally shape our lives. Networks channel the ways that information, emotions, and diseases flow through populations. Networks reflect differences in power and status in settings ranging from small peer groups to international relations across the globe. Network tools even provide insights into the ways that concepts, ideas and other socially generated contents shape culture and meaning. As such, the rich and diverse field of social network analysis has emerged as a central tool across the social sciences. This Handbook provides an overview of the theory, methods, and substantive contributions of this field. The thirty-three chapters move through the basics of social network analysis aimed at those seeking an introduction to advanced and novel approaches to modeling social networks statistically. The Handbook includes chapters on data collection and visualization, theoretical innovations, links between networks and computational social science, and how social network analysis has contributed substantively across numerous fields. As networks are everywhere in social life, the field is inherently interdisciplinary and this Handbook includes contributions from leading scholars in sociology, archaeology, economics, statistics, and information science among others.

Comparing the social networks of service users with long term mental health needs living in community with those in a general adult in-patient unit

2021 ◽  
pp. 002076402110175
Author(s):  
Roberto Rusca ◽  
Ike-Foster Onwuchekwa ◽  
Catherine Kinane ◽  
Douglas MacInnes
Keyword(s):  
Mental Health ◽  
Social Networks ◽  
Social Network ◽  
Patient Group ◽  
Mental Health Problems ◽  
Well Being ◽  
Health Problems ◽  
Practical Support ◽  
The Social

Background: Relationships are vital to recovery however, there is uncertainty whether users have different types of social networks in different mental health settings and how these networks may impact on users’ wellbeing. Aims: To compare the social networks of people with long-term mental illness in the community with those of people in a general adult in-patient unit. Method: A sample of general adult in-patients with enduring mental health problems, aged between 18 and 65, was compared with a similar sample attending a general adult psychiatric clinic. A cross-sectional survey collected demographic data and information about participants’ social networks. Participants also completed the Short Warwick Edinburgh Mental Well-Being Scale to examine well-being and the Significant Others Scale to explore their social network support. Results: The study recruited 53 participants (25 living in the community and 28 current in-patients) with 339 named as important members of their social networks. Both groups recorded low numbers in their social networks though the community sample had a significantly greater number of social contacts (7.4 vs. 5.4), more monthly contacts with members of their network and significantly higher levels of social media use. The in-patient group reported greater levels of emotional and practical support from their network. Conclusions: People with serious and enduring mental health problems living in the community had a significantly greater number of people in their social network than those who were in-patients while the in-patient group reported greater levels of emotional and practical support from their network. Recommendations for future work have been made.

scholarly journals The switching mechanisms of social network densification

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Teruyoshi Kobayashi ◽  
Mathieu Génois
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Social Context ◽  
Social Interactions ◽  
Regime Switching ◽  
Face To Face ◽  
The Social ◽  
Switching Property ◽  
Distinctive Type ◽  
Insight Into

AbstractDensification and sparsification of social networks are attributed to two fundamental mechanisms: a change in the population in the system, and/or a change in the chances that people in the system are connected. In theory, each of these mechanisms generates a distinctive type of densification scaling, but in reality both types are generally mixed. Here, we develop a Bayesian statistical method to identify the extent to which each of these mechanisms is at play at a given point in time, taking the mixed densification scaling as input. We apply the method to networks of face-to-face interactions of individuals and reveal that the main mechanism that causes densification and sparsification occasionally switches, the frequency of which depending on the social context. The proposed method uncovers an inherent regime-switching property of network dynamics, which will provide a new insight into the mechanics behind evolving social interactions.

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