Dynamic impact of social network on knowledge contribution loafing in mobile collaboration: a hidden Markov model

Purpose Social loafing in knowledge contribution (namely, knowledge contribution loafing [KCL]) usually happens in group context, especially in the mobile collaboration tasks. KCL shows dynamic features over time. However, most previous studies are based on static assumption, that is, KCL will not change over time. This paper aims to reveal the dynamics of KCL in mobile collaboration and analyze how network centrality influences KCL states considering the current loafing state. Design/methodology/approach This study is based on empirical study design. Real mobile collaboration behavioral data related to knowledge contribution were collected to investigate the dynamic relationship between network centrality and KCL. In total, 4,127 chat contents were collected through Slack (a mobile collaboration APP). The text data were first analyzed using the text analysis method and then analyzed by a machine learning method called hidden Markov model. Findings First, the results reveal the inner structure of KCL, showing that it has three states (low, medium and high). Second, it is found that network centrality positively influences individuals involved in medium and high loafing state, while it has a negative influence on individuals with low loafing state. Research limitations/implications The limitations are related to the single machine learning method and no subdivision of social network. First, this paper only uses one kind of text classification model (TF-IDF) to divide chat contents, which may not be superior to other classification models. This paper considers the eigenvector centrality, and not further divides the social network into advice network and expressive network. Practical implications This study helps companies infer tendency of different KCL and dynamically re-organize a mobile collaborative team for better knowledge contribution. Originality/value First, previous studies based on static assumptions regarding KCL as static and the relationship between loafing reducing mechanisms and team members KCL does not change over time. This study relaxes static assumptions and allows KCL to change during the process of collaboration. Second, this study allows the impact of network centrality to be different when members are in different KCL states.

CEAF Implementation Roadmap

Working collaboratively and providing Citizen Services on a whole-of-government model require intensive resources, planning a methodology, and support by senior executives. This, in turn, requires extensive electronic and mobile collaboration. The rapidity of global communications has certainly influenced the world's view of leadership toward seeing collaboration as an effective and efficient way to provide necessary services to citizens. This is also an intelligent way of looking at governments. Open-data initiatives will require a higher level of cooperation within and among government departments. The extent of changes and avoidance of various pitfalls for this implementation need to be thought through within governments and with external organisations.

Key Enterprise Architectural Challenges in Local Government

The many enterprise applications of government require a substantial level of collaboration. The impact of one decision on other aspects of the business requires analysis, including statistical (predictive) analytics, sentiment analytics, and cultural and skills analytics.Further, the shift from purely cost-centered decision making to that of “whole-of-government 1 is palpable. Accordingly, extensive electronic and mobile collaboration is required, even though such collaboration is counterintuitive to the mindset of prioritising according to departmental policies. In addition, the challenges governments face range from the time taken to approve an initiative, considering the complexity of processes, to its organisational structure and ever-changing technology in this age.