Analysis of Task Management in Virtual Academic Teams

Social Collaboration Analytics (SCA) aims at measuring collaboration in Enterprise Collaboration Systems (ECS). In this paper, we apply SCA to investigate the use of Task Management (TM) features in virtual academic teams on a collaboration platform. This paper contributes to theory by developing the TM Catalog describing the elements and characteristics of TM. Our literature review identified only three studies analyzing the use of TM features in ECS. These studies base their analyses on transactional data (event logs). We propose to analyze both the structure and characteristics of tasks, as well as how tasks are used. In our paper, we show how SCA can be applied to gain insights on the use of TM features. Based on data from an academic collaboration platform, we demonstrate the characteristics of tasks and how different types of virtual academic teams make use of TM features

Forced Adoption: A new Phenomenon of Information Systems Adoption

The adoption of Information Systems (IS) in an organizational context often follows a mandated process: management decides to implement the IS and the employees are supposed to adopt the IS. The regulations enforcing remote work during the COVID-19 pandemic have changed this process. Organizations around the world saw themselves forced to adopt new IS overnight. This “forced adoption” unfolded unprepared and unstructured, induced by an uncontrollable external factor instead of a traditional management mandate. Consequently, forced adoption challenges existing knowledge about IS adoption. We provide a first conceptualization of the term “forced adoption” and outline our research approach for examining forced adoption of IS, work practices and leadership styles in the context of the COVID-19 pandemic

Social Collaboration Analytics for Enterprise Collaboration Systems: Providing Business Intelligence on Collaboration Activities

The success of public Social Media has led to the emergence of Enterprise Social Software (ESS), a new type of collaboration software for organizations that incorporates “social features”. Surveys show that many companies are trying to implement ESS but that adoption is slower than expected. We believe that in order to understand the issues with its implementation we need to first examine and understand the “social” interactions that are taking place in this new kind of collaboration software. We propose Social Collaboration Analytics (SCA), a specialized form of examination of log files and content data, to gain a better understanding of the actual usage of ESS. Our research was guided by the CRISP-DM approach. We first analyzed the data available in a leading ESS. Together with leading user companies of this ESS, we then developed a framework for Social Collaboration Analysis, which we present in this paper

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

In this paper, we propose a user typology for Enterprise Collaboration Systems (ECS). We draw on and extend findings from previous research in the area of CSCW and Social Collaboration Analytics. The proposed typology includes: (1) a definition of user types, (2) dimensions of ECS use and (3) a classification of action (event) types. The typology contains the following user types: creator, contributor, lurker, inactive and non-user. These types are characterized by differences in the following dimensions: type of use, frequency of use, variety of use, choice of content type and platform preferences. The definition of user types along these dimensions facilitates the implementation of database queries (scripts) for Social Collaboration Analytics (SCA), with the aim of determining the dis-tribution of types of users in an Enterprise Collaboration System. We present selected results of such SCA for an integrated collaboration platform and discuss the findings. We successfully demonstrate that our classification of user types allows us to draw conclusions on (1) the form and degree of participation of users in the ECS and, derived from that, (2) the likely purpose of the examined communities

Metrics for Analyzing Social Documents to Understand Joint Work

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)

Measuring and visualising boundary spanning in enterprise collaboration systems

Enterprise Collaboration Systems (ECS) facilitate computer-supported collaboration and communication among employees, often across boundaries of multiple organisational units or departments. Consequently, ECS have become the core of the digital workplace in many companies. In ECS, diverse project teams from different organisational units collaborate on projects. The phenomenon of collaboration and communication across organisational boundaries is also referred to as boundary-spanning. Although in the digital workplace in companies, the connectedness of organisational units and boundary-spanning are becoming more and more important, research on how ECS support boundary spanning is scarce. This paper describes the development and application of an interactive dashboard for measuring and visualising boundary-spanning activities based on ECS log data. The dashboard is evaluated by applying it based on log data from an ECS. It is demonstrated how the dashboard can be used to gain insights into how different organisational units engage in boundary spanning in ECS

A Semantic Data Lake for Harmonizing Data from Cross-Platform Digital Workspaces using Ontology-Based Data Access

Most organizations provide a portfolio of multiple applications from different vendors (with different data structures) for supporting computer-mediated collaboration among their employees. The heterogeneous format of the activity logs and the content data is challenging for the analysis of cross-platform collaboration and for comparing results from the different systems. To address these issues, we develop and demonstrate a prototype for a semantic data lake. Our prototype is based on Hadoop and ingests data from the source systems in near real-time. Ontology-based data access is implemented based on a mapping between an ontology and the ingested data. Thus, an analyst only needs to be familiar with the ontology and can use identical SPARQL queries to obtain the same information from the source systems. We demonstrate the ontology-database mapping and show how concepts from Web Science can solve practical problems in the Information Systems discipline, specifically for the area of Business Intelligence

A Survey on the Status Quo of Social Collaboration Analytics in Practice

This paper aims to identify and document the status quo and the perceived barriers of Social Collaboration Analytics in practice. The study is part of a publicly funded longitudinal research project on Enterprise Collaboration Systems (ECS) involving 29 early-adopter user companies. Our paper draws on and extends findings from previous research. The key themes identified from a structured literature review and the documented findings from previous workshops with practitioners were used to develop an online questionnaire. Longitudinal case studies on the same companies helped to inform and interpret the findings. The survey shows that most of the participants have implemented some form of Collaboration Analytics, however, the outputs are mostly on a high abstraction level and the methods quite simplistic. Complex analyses that could help in assessing the degree of cooperation, structures or dynamics in the use of ECS are not (yet) applied. We identified three important reasons for this situation: (1) The analytics tools provided by standard collaboration software do not provide sufficient functionality, (2) there is a lack of awareness and knowledge about more complex forms of analyses and (3) some concepts from the academic literature are not perceived as relevant by practitioners. The survey also confirmed that there are financial, regulatory, data and HR barriers for Social Collaboration Analytics