The Nature of the Relationships between Social Networks, Interpersonal Trust, Management Support, and Knowledge Sharing

Purpose – Past research has shown that, by implementing knowledge sharing, an organisation can maintain its long-term competitive advantage. Hence, this research will explore the nature of the relationships between social networks, interpersonal trust, management support, and knowledge sharing. Methodology/approach – In order to achieve the above purpose, semi-structured interviews were used to gather qualitative data. Interviewee participants included top and middle managers and frontline employees. The total number of participants included in the research was 25, equally representing five companies. The core business of all the companies was large-scale manufacturing. A grounded theory approach was used to analyse the data, augmented by the computer-assisted qualitative data analysis software, Nvivo. Findings – The results reveal that social networks facilitate knowledge sharing in diverse ways. These ways are: the use of multiple communication styles, brainstorming and problem solving, learning and teaching, training, employee rotation, and consultation. In addition, the data from the interviews suggests that, through various factors, the level of interpersonal trust, influences the extent to which employees are willing to share knowledge. These factors are organisational, relational, and individual factors. Furthermore, this study shows that both middle and top managers can play significant roles in facilitating knowledge sharing between employees. These roles are: encouragement of participation in decision-making, provision of recognition, breaking down of barriers, building up of teams, providing training or assigning others to do training, encouragement of training, communication, learning, putting knowledge into practice in the form of processes, and movement of employees. Research contributions – Six models were developed from the qualitative analysis of the field data. The brainstorming and problem solving model identifies various steps for brainstorming and problem solving which influence social networks and knowledge sharing. The model of learning and teaching explains how social networks can be built based on the receivers’ levels of knowledge, namely, the novice, competent, expert, and proficient levels. The model of factors influencing social networks and knowledge sharing illustrates various factors. These are: using multiple communication strategies, brainstorming and problem solving, learning and teaching, training, employee rotation, and consultation. The model of factors influencing interpersonal trust describes three factors for achieving such trust: organisational, relational, and individual factors. This model also elaborates on three factors that negatively influence interpersonal trust. These are division between departments, team conflict, and a sense of vulnerability. The model of the role of management teams in encouraging participation in decision-making elaborates on levels of decision-making among employees and the way in which knowledge flows between top and middle management and frontline employees. The integrative model deciphers the relationships between social networks, interpersonal trust, management support, openness, and knowledge sharing. In addition, the relationships between each area of emphasis and knowledge sharing are included in the model. Based on this model, a survey questionnaire was developed. These models provide new insights into the relationships between social networks, interpersonal trust, management support, and knowledge sharing. By applying these models to appropriate field situations, both practitioners and academics may be able to improve current practices relating to how knowledge is shared and evolves within organisations

Enhance Data Security Protection for Data Sharing in Cloud Storage System

Cloud computing technology can be used in all types of organizations. There are many benefits to use cloud storage. The most notable is data accessibility. Data stored in the cloud can be accessed at any time any place. Another advantage of cloud storage is data sharing between users. By sharing storage and networks with many users it is also possible for unauthorized users to access our data. To provide confidentiality of shared sensitive data, the cryptographic techniques are applied. So protect the data from unauthorized users, the cryptographic key is main challenge. In this method a data protection for cloud storage 1) The key is protected by two factors: Secret key is stored in the computer and personal security device 2) The key can be revoked efficiently by implementing proxy re-encryption and key separation techniques. 3) The data is protected in a fine grained way by adopting the attribute based encryption technique. So our proposed method provides confidentiality on data

A Systematic Identification and Analysis of Scientists on Twitter

Metrics derived from Twitter and other social media---often referred to as altmetrics---are increasingly used to estimate the broader social impacts of scholarship. Such efforts, however, may produce highly misleading results, as the entities that participate in conversations about science on these platforms are largely unknown. For instance, if altmetric activities are generated mainly by scientists, does it really capture broader social impacts of science? Here we present a systematic approach to identifying and analyzing scientists on Twitter. Our method can identify scientists across many disciplines, without relying on external bibliographic data, and be easily adapted to identify other stakeholder groups in science. We investigate the demographics, sharing behaviors, and interconnectivity of the identified scientists. We find that Twitter has been employed by scholars across the disciplinary spectrum, with an over-representation of social and computer and information scientists; under-representation of mathematical, physical, and life scientists; and a better representation of women compared to scholarly publishing. Analysis of the sharing of URLs reveals a distinct imprint of scholarly sites, yet only a small fraction of shared URLs are science-related. We find an assortative mixing with respect to disciplines in the networks between scientists, suggesting the maintenance of disciplinary walls in social media. Our work contributes to the literature both methodologically and conceptually---we provide new methods for disambiguating and identifying particular actors on social media and describing the behaviors of scientists, thus providing foundational information for the construction and use of indicators on the basis of social media metrics

Removal of Cross Talk in Omega Switch Network by Using Improve Windowing Technique

An optical computer network is a network that relies primarily on the computing power and bandwidth of the participants in the network rather than concentrating it in a relatively low number of servers. Such networks are useful for many purposes. Sharing content files (see file sharing) containing audio, video, data or anything in digital format is very common, and real time data, such as telephony traffic, is also passed using Optical technology. The proposed work is about to handle the network fault in case of cross talk in a switched network. In this work we are presenting the complete work with Omega Network. The work includes the analysis of existing methodologies to detect the confliction in cross talk. As the confliction is detected the next work is perform the talk with a smaller delay such that it will avoid the cross talk over the networ