A Framework to Interface Enterprise Social Network into Running Business Process

2017 ◽  
Author(s):  
Amjed Al-Thuhli ◽  
Mohammed Al-Badawi
Keyword(s):  
Social Network ◽  
Business Process ◽  
Enterprise Social Network

Enterprise social network (ESN) systems and knowledge sharing: what makes it work for users?

2019 ◽  
Vol 50 (2) ◽  
pp. 305-327
Author(s):  
Abhishek Kalra ◽  
Rupashree Baral
Keyword(s):  
Social Network ◽  
Knowledge Sharing ◽  
Structural Equation ◽  
Least Squares Method ◽  
Equation Modeling ◽  
Top Management ◽  
Management Support ◽  
Cross Sectional ◽  
Content Type ◽  
Enterprise Social Network

Purpose Enterprise Social Network (ESN) systems have emerged as the technology of choice to bolster and support organizational efforts for harnessing embedded knowledge. However, a lack of understanding about it limits the optimization of its potential. Hence, this paper aims to assess the role of hedonic motivation, network externalities (NE) and top management support in conjugation with the unified theory of acceptance and use of technology theory to understand ESN’s usage for knowledge sharing. Design/methodology/approach Data were collected from 187 ESN users through a survey questionnaire and subsequently analyzed using variance-based structural equation modeling using the partial least squares method. Findings ESNs are used both for utilitarian and hedonic purposes. Furthermore, the results also bring out the importance of externalities arising from an extensive network of users and complimentary services, as well as support regarding resources and recognition from the top management toward reinforcing the benefits of using ESNs. Research limitations/implications This study advances earlier knowledge by assessing the actual usage of ESNs for knowledge sharing. It takes into consideration multiple input variables, namely, performance expectancy, effort expectancy, NE amongst others to best resonate with the key factors driving its adoption and usage by an individual. However, because of the cross-sectional research design, causality can only be inferred. Practical implications The organizations are recommended to have in place the measures for attaining optimal usage of ESNs, and in turn, witness knowledge moves around in ways unfathomable. Steps should be taken to develop tools and ecosystems to provide users affordances for both increasing productivity, as well as opportunities for gaining pleasure. Originality/value This study is one of its kind effort to synthesize the knowledge about the ESNs in an Indian context. It provides fascinating insights into the determinants of intention and usage of ESNs for knowledge sharing.

scholarly journals Social Network Supported Process Recommender System

2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
Yanming Ye ◽  
Jianwei Yin ◽  
Yueshen Xu
Keyword(s):  
Social Network ◽  
Structure Analysis ◽  
Business Process ◽  
Recommender System ◽  
Process Modeling ◽  
Network System ◽  
The Social ◽  
Social Features ◽  
Matching Degree ◽  
Process Structure

Process recommendation technologies have gained more and more attention in the field of intelligent business process modeling to assist the process modeling. However, most of the existing technologies only use the process structure analysis and do not take the social features of processes into account, while the process modeling is complex and comprehensive in most situations. This paper studies the feasibility of social network research technologies on process recommendation and builds a social network system of processes based on the features similarities. Then, three process matching degree measurements are presented and the system implementation is discussed subsequently. Finally, experimental evaluations and future works are introduced.

Identifying target audience on enterprise social network

2019 ◽  
Vol 119 (1) ◽  
pp. 111-128 ◽  
Author(s):  
Jianhong Luo ◽  
Xuwei Pan ◽  
Shixiong Wang ◽  
Yujing Huang
Keyword(s):  
Social Media ◽  
Social Network ◽  
Latent Dirichlet Allocation ◽  
Topic Model ◽  
Information Service ◽  
Target Audience ◽  
Business Practices ◽  
Content Type ◽  
Enterprise Social Media ◽  
Enterprise Social Network

Purpose Delivering messages and information to potentially interested users is one of the distinguishing applications of online enterprise social network (ESN). The purpose of this paper is to provide insights to better understand the repost preferences of users and provide personalized information service in enterprise social media marketing. Design/methodology/approach It is accomplished by constructing a target audience identification framework. Repost preference latent Dirichlet allocation (RPLDA) topic model topic model is proposed to understand the mass user online repost preferences toward different contents. A topic-oriented preference metric is proposed to measure the preference degree of individual users. And the function of reposting forecasting is formulated to identify target audience. Findings The empirical research shows the following: a total of 20 percent of the repost users in ESN represent the key active users who are particularly interested in the latent topic of messages in ESN and fits Pareto distribution; and the target audience identification framework can successfully identify different target key users for messages with different latent topics. Practical implications The findings should motivate marketing managers to improve enterprise brand by identifying key target audience in ESN and marketing in a way that truthfully reflects personalized preferences. Originality/value This study runs counter to most current business practices, which tend to use simple popularity to seek important users. Adaptively and dynamically identifying target audience appears to have considerable potential, especially in the rapidly growing area of enterprise social media information service.

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