Developing a User Typology for the Analysis  of Participation in Enterprise Collaboration Systems

Schwade, Florian; Schubert, Petra

doi:10.24251/hicss.2019.056

Cited by 10 publications

(20 citation statements)

References 25 publications

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“…The last three user types refer to employees who are not active at all on a platform because they did not use it for a long time, never logged in or never possessed login information. Schwade and Schubert (2019) also revealed that scholars focused on the role and characteristics of lurkers, while the discussion of other user types is limited. Furthermore, there is no consensus on the definition of the individual types.…”

Section: Background: Enterprise Social Media User Typologymentioning

confidence: 99%

“…In conclusion, studies analyzing the factors that distinguish the different types of ESM users are still fragmented and provide partially contrasting results. In addition, most of the proposed typologies are inconsistent because they mix different dimensions, such as type of use, frequency of use and variety of purposes for use (Schwade and Schubert, 2019). In light of this, we proposed a bi-dimensional classification of ESM users and apply it to analyzing the case company that adopted an ESM platform to support employees' KM activities.…”

Section: Background: Enterprise Social Media User Typologymentioning

confidence: 99%

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A bi-dimensional classification and characterization of enterprise social media users

Kirchner

Jørgensen

Bolisani

et al. 2021

MBE

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Purpose Enterprise social media (ESM) platforms are rapidly diffusing in the business context because they can bring substantial benefits to companies by enhancing their knowledge management (KM) processes. However, such benefits materialize only if active employee participation is ensured. Therefore, it is crucial to understand how individual employees use an ESM platform to assist their knowledge-related activities. This paper contributes to this topic by proposing a classification of ESM users based on two dimensions: frequency and type (active or passive) of use. Design/methodology/approach The paper presents the results of a survey of 262 employees of an international engineering service company that has adopted an ESM platform to support its KM processes. Statistical methods (e.g. ANOVA, Tukey’s b) were applied to verify the usefulness of the proposed typology and identify the main aspects that characterize the different user groups. Findings The survey results confirm the existence of different types of ESM users and provide the empirical basis for developing a bi-dimensional classification from which four user groups were derived and characterized: frequent contributors, sporadic contributors, frequent lurkers and sporadic lurkers. Research limitations/implications The main limitation is that only one company in one sector with specific knowledge needs and capabilities was investigated. Practical implications The study provides useful suggestions for how to promote the use of an ESM and particularly for how to encourage less frequent and less active users to increase their participation in a platform. Originality/value The paper contributes to a better understanding of how employees approach ESM by identifying factors that characterize different user groups.

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Section: Background: Enterprise Social Media User Typologymentioning

confidence: 99%

Section: Background: Enterprise Social Media User Typologymentioning

confidence: 99%

A bi-dimensional classification and characterization of enterprise social media users

Kirchner

Jørgensen

Bolisani

et al. 2021

MBE

View full text Add to dashboard Cite

show abstract

“…The categories consumption, contribution and creation, for example, allow the identification of different users types e.g. creator, contributor, lurker, inactive and non-user [38].…”

Section: Structural Vs Transactional Viewmentioning

confidence: 99%

Metrics for Analyzing Social Documents to Understand Joint Work

Schubert¹,

Mosen²,

Schwade³

2020

Proceedings of the Annual Hawaii International Conference on System Sciences

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Social Collaboration Analytics (SCA) aims at measuring and interpreting communication and joint work on collaboration platforms and is a relatively new topic in the discipline of Information Systems. Previous applications of SCA are largely based on transactional data (event logs). In this paper, we propose a novel approach for the examination of collaboration based on the structure of social documents. Guided by the ontology for social business documents (SocDOnt) we develop metrics to measure collaboration around documents that provide traces of collaborative activity. For the evaluation, we apply these metrics to a large-scale collaboration platform. The findings show that group workspaces that support the same use case are characterized by a similar richness of their social documents (i.e. the number of components and contributing authors). We also show typical differences in the "collaborativity" of functional modules (containers).

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“…[22,41,75,76], and related user types (e.g. creator, contributor, lurker) [72] are measured. Muller et al [42] propose the return on contribution (ROC) construct, a ratio between production and consumption, and costs and benefits, respectively.…”

Section: Enterprise Collaboration Platform Outcomes and Benefits Resementioning

confidence: 99%

Monitoring and Understanding Enterprise Collaboration Platform Outcomes and Benefits Change

Nitschke

Williams

2020

Proceedings of the Annual Hawaii International Conference on System Sciences

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Enterprise collaboration platforms integrating traditional collaboration tools and enterprise social software are shaped and designed through use. To date, existing research has not studied in any depth how their outcomes and benefits change over time. In this paper, we develop the MoBeC framework for capturing and monitoring how outcomes and benefits of enterprise collaboration platforms are changing over time. The framework is applied in an empirical setting adopting a longitudinal case study design. The study findings contribute to the deeper understanding of the dynamic and evolving nature of such platforms.

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Developing a User Typology for the Analysis of Participation in Enterprise Collaboration Systems

Cited by 10 publications

References 25 publications

A bi-dimensional classification and characterization of enterprise social media users

A bi-dimensional classification and characterization of enterprise social media users

Metrics for Analyzing Social Documents to Understand Joint Work

Monitoring and Understanding Enterprise Collaboration Platform Outcomes and Benefits Change

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