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Predictive Process Monitoring is becoming more prevalent as an aid for organizations to support their operational processes. However, most software applications available today require extensive technical know-how by the operator and are therefore not suitable for most real-world scenarios. Therefore, this work presents a prototype implementation of a Predictive Process Monitoring dashboard in the form of a web application. The system is based on the PPM Camunda Plugin presented by Bartmann et al. (2021) and allows users to easily create metrics, visualizations to display these metrics, and dashboards in which visualizations can be arranged. A usability test is with test users of different computer skills is conducted to confirm the application’s user-friendliness.
Remote Working Study 2022
(2022)
The Remote Working Study 2022 is focused on the transition to work from home (WFH) triggered by the stay at home directives of 2020. These directives required employees to work in their private premises wherever possible to reduce the transmission of the coronavirus. The study, conducted by the Center for Enterprise Information Research (CEIR) at the University of Koblenz from December 2021 to January 2022, explores the transition to remote working.
The objective of the survey is to collect baseline information about organisations’ remote work experiences during and immediately following the COVID-19 lockdowns. The survey was completed by the key persons responsible for the implementation and/or management of the digital workplace in 19 German and Swiss organisations.
The data presented in this report was collected from member organisations of the IndustryConnect initiative. IndustryConnect is a university-industry research programme that is coordinated by researchers from the University of Koblenz. It focuses on research in the areas of the digital workplace and enterprise collaboration technologies, and facilitates the generation of new research insights and the exchange of experiences among user companies.
Enterprise collaboration platforms are increasingly gaining importance in organisations. Integrating groupware functionality and enterprise social software (ESS), they have substantially been transforming everyday work in organisations. While traditional collaboration systems have been studied in Computer Supported Cooperative Work (CSCW) for many years, the large-scale, infrastructural and heterogeneous nature of enterprise collaboration platforms remains uncharted. Enterprise collaboration platforms are embedded into organisations’ digital workplace and come with a high degree of complexity, ambiguity, and generativity. When introduced, they are empty shells with no pre-determined purposes of use. They afford interpretive flexibility, and thus are shaping and being shaped by and in their social context. Outcomes and benefits emerge and evolve over time in an open-ended process and as the digital platform is designed through use. In order to make the most of the platform and associated continuous digital transformation, organisations have to develop the necessary competencies and capabilities.
Extant literature on enterprise collaboration platforms has proliferated and provide valuable insights on diverse topics, such as implementation strategies, adoption hurdles, or collaboration use cases, however, they tend to disregard their evolvability and related multiple time frames and settings. Thus, this research aims to identify, investigate, and theorise the ways that enterprise collaboration platforms are changing over time and space and the ways that organisations build digital transformation capabilities. To address this research aim two different case study types are conducted: i) in-depth longitudinal qualitative case study, where case narratives and visualisations capturing hard-to-summarise complexities in the enterprise collaboration platform evolution are developed and ii) multiple-case studies to capture, investigate, and compare cross-case elements that contribute to the shaping of enterprise collaboration platforms in different medium-sized and large organisations from a range of industries. Empirical data is captured and investigated through a multi-method research design (incl. focus groups, surveys, in-depth interviews, literature reviews, qualitative content analysis, descriptive statistics) with shifting units of analysis. The findings reveal unique change routes with unanticipated outcomes and transformations, context-specific change strategies to deal with multiple challenges (e.g. GDPR, works council, developments in the technological field, competing systems, integration of blue-collar workers), co-existing platform uses, and various interacting actors from the immediate setting and broader context. The interpretation draws on information infrastructure (II) as a theoretical lens and related sociotechnical concepts and perspectives (incl. inscriptions, social worlds, biography of artefacts). Iteratively, a conceptual model of the building of digital transformation capabilities is developed, integrating the insights gained from the study of enterprise collaboration platform change and developed monitoring change tools (e.g. MoBeC framework). It assists researchers and practitioners in understanding the building of digital transformation capabilities from a theoretical and practical viewpoint and organisations implement the depicted knowledge in their unique digital transformation processes.
Enterprise Collaboration Systems (ECS) have become substantial for computer-mediated communication and collaboration among employees in organisations. As ECS combine features from social media and traditional groupware, a growing number of organisations implement ECS to facilitate collaboration among employees. Consequently, ECS form the core of the digital workplace. Thus, the activity logs of ECS are particularly valuable since they provide a unique opportunity for observing and analysing collaboration in the digital workplace.
Evidence from academia and practice demonstrates that there is no standardised approach for the analysis of ECS logs and that practitioners struggle with various barriers. Because current ECS analytics tools only provide basic features, academics and practitioners cannot leverage the full potential of the activity logs. As ECS activity logs are a valuable source for understanding collaboration in the digital workplace, new methods and metrics for their analysis are required. This dissertation develops Social Collaboration Analytics (SCA) as a method for measuring and analysing collaboration activities in ECS. To address the existing limitations in academia and practice and to contribute a method and structures for applying SCA in practice, this dissertation aims to answer two main research questions:
1. What are the current practices for measuring collaboration activities in Enterprise Collaboration Systems?
2. How can Social Collaboration Analytics be implemented in practice?
By answering the research questions, this dissertation seeks to (1) establish a broad thematic understanding of the research field of SCA and (2) to develop SCA as a structured method for analysing ac-tivity logs of ECS. As part of the first research question, this dissertation documents the status quo of SCA in the academic literature and practice. By answering the second research question, this dissertation contributes the SCA framework (SCAF), which guides the practical application of SCA. SCAF is the main contribution of this dissertation. The framework was developed based on findings from an analysis of 86 SCA studies, results from 6 focus groups and results from a survey among 27 ECS user companies. The phases of SCAF were derived from a comparison of established process models for data mining and business intelligence. The eight phases of the framework contain detailed descriptions, working steps, and guiding questions, which provide a step by step guide for the application of SCA in practice. Thus, academics and practitioners can benefit from using the framework.
The constant evaluation of the research outcomes in focus groups ensures both rigour and relevance. This dissertation employs a qualitative-dominant mixed-methods approach. As part of the university-industry collaboration initiative IndustryConnect, this research has access to more than 30 leading ECS user companies. Being built on a key case study and a series of advanced focus groups with representatives of user companies, this dissertation can draw from unique insights from practice as well as rich data with a longitudinal perspective.
Within the field of Business Process Management, business rules are commonly used to model company decision logic and govern allowed company behavior. An exemplary business rule in the financial sector could be for example:
”A customer with a mental condition is not creditworthy”. Business rules are
usually created and maintained collaboratively and over time. In this setting,
modelling errors can occur frequently. A challenging problem in this context is
that of inconsistency, i.e., contradictory rules which cannot hold at the same
time. For instance, regarding the exemplary rule above, an inconsistency would
arise if a (second) modeller entered an additional rule: ”A customer with a mental condition is always creditworthy”, as the two rules cannot hold at the same
time. In this thesis, we investigate how to handle such inconsistencies in business
rule bases. In particular, we develop methods and techniques for the detection,
analysis and resolution of inconsistencies in business rule bases
Advanced Auditing of Inconsistencies in Declarative Process Models using Clustering Algorithms
(2021)
To have a compliant business process of an organization, it is essential to ensure a onsistent process. The measure of checking if a process is consistent or not depends on the business rules of a process. If the process adheres to these business rules, then the process is compliant and efficient. For huge processes, this is quite a challenge. Having an inconsistency in a process can yield very quickly to a non-functional process, and that’s a severe problem for organizations. This thesis presents a novel auditing approach for handling inconsistencies from a post-execution perspective. The tool identifies the run-time inconsistencies and visualizes them in heatmaps. These plots aim to help modelers observe the most problematic constraints and help them make the right remodeling decisions. The modelers assisted with many variables can be set in the tool to see a different representation of heatmaps that help grasp all the perspectives of the problem. The heatmap sort and shows the run-time inconsistency patterns, so that modeler can decide which constraints are highly problematic and should address a re-model. The tool can be applied to real-life data sets in a reasonable run-time.
The industry standard Decision Model and Notation (DMN) has enabled a new way for the formalization of business rules since 2015. Here, rules are modeled in so-called decision tables, which are defined by input columns and output columns. Furthermore, decisions are arranged in a graph-like structure (DRD level), which creates dependencies between them. With a given input, the decisions now can be requested by appropriate systems. Thereby, activated rules produce output for future use. However, modeling mistakes produces erroneous models, which can occur in the decision tables as well as at the DRD level. According to the Design Science Research Methodology, this thesis introduces an implementation of a verification prototype for the detection and resolution of these errors while the modeling phase. Therefore, presented basics provide the needed theoretical foundation for the development of the tool. This thesis further presents the architecture of the tool and the implemented verification capabilities. Finally, the created prototype is evaluated.
To construct a business process model manually is a highly complex and error-prone task which takes a lot of time and deep insights into the organizational structure, its operations and business rules. To improve the output of business analysts dealing with this process, different techniques have been introduced by researchers to support them during construction with helpful recommendations. These supporting recommendation systems vary in their way of what to recommend in the first place as well as their calculations taking place under the hood to recommend the most fitting element to the user. After a broad introduction into the field of business process modeling and its basic recommendation structures, this work will take a closer look at diverse proposals and descriptions published in current literature regarding implementation strategies to effectively and efficiently assist modelers during their business process model creation. A critical analysis of presentations in the selected literature will point out strengths and weaknesses of their approaches, studies and descriptions of those. As a result, the final concept matrix in this work will give a precise and helpful overview about the key features and recommendation methods used and implemented in previous research studies to pinpoint an entry into future works without the downsides already spotted by fellow researchers.
Engineering criminal agents
(2019)
This PhD thesis with the title "Engineering Criminal Agents" demonstrates the interplay of three different research fields captured in the title: In the centre are Engineering and Simulation, both set in relation with the application field of Criminology - and the social science aspect of the latter. More precisely,
this work intends to show how specific agent-based simulation models can be created using common methods from software engineering.
Agent-based simulation has proven to be a valuable method for social science since decades, and the trend to increasingly complex simulation models is apparent, not at least due to advancing computational and simulation techniques. An important cause of complexity is the inclusion of 'evidence' as basis of simulation models. Evidence can be provided by various stakeholders, reflecting their different viewpoints on the topic to model.
This poses a particular burden by interrelating the two relevant perspectives on the topic of simulation: on the one hand the user of the simulation model who provides the requirements and is interested in the simulation results, on the other hand the developer of the simulation model who has to program a verified and validated formal model. In order to methodically link these two perspectives, substantial efforts in research and development are needed, where this PhD thesis aims to make a contribution.
The practical results - in terms of software - were achieved by using the multi-faceted approach mentioned above: using methods from software engineering, in order to become able to apply methods from computational social sciences, in order to gain insights into social systems, such as in the internal dynamics of criminal networks.
The PhD thesis shows the research involved to create these practical results, and gives technical details and specifications of the developed software.
The frame for research and development to achieve these results was provided mainly by two research projects: OCOPOMO and GLODERS.
Business Process Querying (BPQ) is a discipline in the field of Business Process Man- agement which helps experts to understand existing process models and accelerates the development of new ones. Its queries can fetch and merge these models, answer questions regarding the underlying process, and conduct compliance checking in return. Many languages have been deployed in this discipline but two language types are dominant: Logic-based languages use temporal logic to verify models as finite state machines whereas graph-based languages use pattern matching to retrieve subgraphs of model graphs directly. This thesis aims to map the features of both language types to features of the other to identify strengths and weaknesses. Exemplarily, the features of Computational Tree Logic (CTL) and The Diagramed Modeling Language (DMQL) are mapped to one another. CTL explores the valid state space and thus is better for behavioral querying. Lacking certain structural features and counting mechanisms it is not appropriate to query structural properties. In contrast, DMQL issues structural queries and its patterns can reconstruct any CTL formula. However, they do not always achieve exactly the same semantic: Patterns treat conditional flow as sequential flow by ignoring its conditions. As a result, retrieved mappings are invalid process execution sequences, i.e. false positives, in certain scenarios. DMQL can be used for behavioral querying if these are absent or acceptable. In conclusion, both language types have strengths and are specialized for different BPQ use cases but in certain scenarios graph-based languages can be applied to both. Integrating the evaluation of conditions would remove the need for logic-based languages in BPQ completely.
The Internet of Things (IoT) is a fast-growing, technological concept, which aims to integrate various physical and virtual objects into a global network to enable interaction and communication between those objects (Atzori, Iera and Morabito, 2010). The application possibilities are manifold and may transform society and economy similarly to the usage of the internet (Chase, 2013). Furthermore, the Internet of Things occupies a central role for the realisation of visionary future concepts, for example, Smart City or Smart Healthcare. In addition, the utilisation of this technology promises opportunities for the enhancement of various sustainability aspects, and thus for the transformation to a smarter, more efficient and more conscious dealing with natural resources (Maksimovic, 2017). The action principle of sustainability increasingly gains attention in the societal and academical discourse. This is reasoned by the partly harmful consumption and production patterns of the last century (Mcwilliams et al., 2016). Relating to sustainability, the advancing application of IoT technology also poses risks. Following the precautionary principle, these risks should be considered early (Harremoës et al., 2001). Risks of IoT for sustainability include the massive amounts of energy and raw materials which are required for the manufacturing and operation of IoT objects and furthermore, the disposal of those objects (Birkel et al., 2019). The exact relations in the context of IoT and sustainability are insufficiently explored to this point and do not constitute a central element within the discussion of this technology (Behrendt, 2019). Therefore, this thesis aims to develop a comprehensive overview of the relations between IoT and sustainability.
To achieve this aim, this thesis utilises the methodology of Grounded Theory in combination with a comprehensive literature review. The analysed literature primarily consists of research contributions in the field of Information Technology (IT). Based on this literature, aspects, solution approaches, effects and challenges in the context of IoT and sustainability were elaborated. The analysis revealed two central perspectives in this context. IoT for Sustainability (IoT4Sus) describes the utilisation and usage of IoT-generated information to enhance sustainability aspects. In contrast, Sustainability for IoT (Sus4IoT) fo-cuses on sustainability aspects of the applied technology and highlights methods to reduce negative impacts, which are associated with the manufacturing and operation of IoT. Elaborated aspects and relations were illustrated in the comprehensive CCIS Framework. This framework represents a tool for the capturing of relevant aspects and relations in this context and thus supports the awareness of the link between IoT and sustainability. Furthermore, the framework suggests an action principle to optimise the performance of IoT systems regarding sustainability.
The central contribution of this thesis is represented by the providence of the CCIS Framework and the contained information regarding the aspects and relations of IoT and sustainability.
The goal of this thesis is to create a recommender system (RS) for business processes, based on the existing ProM plugin RegPFA. To accomplish this task, firstly an interface must be created that sets up and expands a database receiving probabilistic finite automata (PFA) created by RegPFA in tsml format as input. Secondly, a Java program must be designed that uses said database to recommend the process elements that are most likely to follow a given sequence of process elements.
The status of Business Process Management (BPM) recommender systems is not quite clear as research states. The use of recommenders familiarized itself with the world during the rise of technological evolution in the past decade.Ever since then, several BPM recommender systems came about. However, not a lot of research is conducted in this field. It is not well known to what broad are the technologies used and how are they used. Moreover, this master’s thesis aims at surveying the BPM recommender systems existing. Building on this, the recommendations come in different shapes. They can be positionbased where an element is to be placed at an element’s front, back or to autocomplete a missing link. On the other hand, Recommendations can be textual, to fill the labels of the elements. Furthermore, the literature review for BPM recommender systems took place under the guides of a literature review framework. The framework suggests 5stages of consecutive stages for this sake. The first stage is defining a scope for the research. Secondly, conceptualizing the topic by choosing key terms for literature research. After that in the third stage, comes the research stage.As for the fourth stage, it suggests choosing analysis features over which the literature is to be synthesized and compared. Finally, it recommends defining the research agenda to describe the reason for the literature review. By invoking the mentioned methodology, this master’s thesis surveyed 18 BPM recommender systems. It was found as a result of the survey that there
are not many different technologies for implementing the recommenders. It was also found that the majority of the recommenders suggest nodes that are yet to come in the model, which is called forward recommending. Also, one of the results of the survey indicated the scarce use of textual recommendations to BPM labels. Finally, 18 recommenders are considered less than excepted for a developing field therefore as a result, the survey found a shortage in the number of BPM recommender systems. The results indicate several shortages in several aspects in the field of BPM recommender systems. On this basis, this master’s thesis recommends the future work on it the results.
Business rules have become an important tool to warrant compliance at their business processes. But the collection of these business rules can have various conflicting elements. This can lead to a violation of the compliance to be achieved. This conflicting elements are therefore a kind of inconsistencies, or quasi incon- sistencies in the business rule base. The target for this thesis is to investigate how those quasi inconsistencies in business rules can be detected and analyzed. To this aim, we develop a comprehensive library which allows to apply results from the scientific field of inconsistency measurement to business rule formalisms that are actually used in practice.
The Internet of Things (IoT) is a concept in which connected physical objects are integrated into the virtual world to become active partakers of businesses and everyday processes (Uckelmann, Harrison and Michahelles, 2011; Shrouf, Ordieres and Miragliotta, 2014). It is expected to have a major impact on businesses (Council, Nic and Intelligence, 2008), but small and medium enterprises’ business models are threatened if they do not adopt the new concept (Sommer, 2015). Thus, this thesis aims to showcase a sample implementation of connected devices in a small enterprise, demonstrating its added benefits for the business.
Design Science Research (DSR) is used to develop a prototype based on a use case provided by a carpentry. The prototype comprises a hardware sensor and a web application which can be used by the wood shop to improve their processes. The thesis documents the iterative process of developing a prototype from the grounds up to useable hard- and software.
This contribution provides an example of how IoT can be used and implemented at a small business.
During the last couple of years the extension of the internet into the real world, also referred to as the Internet of Things (IoT), was positively affected by an ongoing digitalization (Mattern and Floerkemeier, 2010; Evans, 2013). Furthermore, one of the most active IoT domains is the personal health ecosystem (Steele and Clarke, 2013). However, this thesis proposes a gamification framework which is supported and enabled by IoT to bring personal health and IoT together in the context of health-insurances. By examining gamification approaches and identifying the role of IoT in such, a conceptual model of a gamification approach was created which indicates where and how IoT is ap-plicable to it. Hence, IoT acts as enabler and furthermore as enhancer of gamified activities. Especial-ly the necessity of wearable devices was highlighted. A stakeholder analysis shed light on respective benefits which concluded in the outcome, that IoT enabled two paradigm shifts for both, the insur-ance and their customer. While taking the results of the examination and the stakeholder analysis as input, the previously made insights were used to develop an IoT supported gamification framework. The framework includes a multi-level structure which is meant to guide through the process of creat-ing an approach but also to analyze already existing approaches. Additionally, the developed frame-work was instantiated based on the application Pokémon Go to identify occurring issues and explain why it failed to retain their customer in the long term. The thesis provides a foundation on which fur-ther context related research can be orientated.
This thesis connects the endeavors of the winemaker’s intention in perfect and profitable wine making with an innovative technological application to use Internet of Things. Thereby the winemaker’s work may be supported and enriched – and enables until recent years still unthinkable optimization of managing and planning of his business, including close state control of different areas of his vineyard, and more than that, not ending up with the single grapevine. It is exemplarily shown in this thesis how to measure, transmit, store and make data available, exemplarily demonstrated with “live” temperature, air and soil humidity values from the vineyard. A modular architecture was designed for the system presented, which allows the use of current sensors, and similar low-voltage sensors, which will be developed in the future.
By using IoT devices in the vineyard, the winemaker advances to a new quality of precision of forecasted data, starting from live data of his vineyard. Of more and more importance, the winemaker can start immediate action, when unforeseen heavy weather conditions occur. Immediate use of current data enabled by a Cloud Infrastructure. For this system, an open service infrastructure is employed. In contrast to other published commercial approaches, the described solution is based on open source.
As an alone-standing part of this work, a physical prototype for measuring relevant parameters in the vineyard was de-novo designed and developed until fulfilling the set of specifications. The outlined features and requirements for a functioning data collection and autonomously transmitting device was developed, described, and the fulfilment by the prototype device were demonstrated. Through literature research and supportive orientationally live interviews of winemakers, the theory and the practical application were synchronized and qualified.
For the development of the prototype the general principles of development of an electronic device were followed, in particular the Design Science Research development rules, and principles of Quality Function Deployment. As a characteristic of the prototype, some principles like re-use of approved construction and material price of the building blocks of the device were taken into consideration as well (e.g. housing; Arduino; PCB). Parts reduction principles, decomplexation and simplified assembly, testing and field service were integrated to the development process by the modular design of the functional vineyard device components, e.g. with partial reference to innovative electrical cabinet construction system Modular-3.
The software architectural concept is based on a three-layer architecture inclusive the TTN infrastructure. The front end is realized as a rich web client, using a WordPress plugin. WordPress was chosen due to the wide adoption through the whole internet, enabling fast and easy user familiarization. Relevant quality issues have been tested and discussed in the view of exemplary functionality, extensibility, requirements fulfilment, as usability and durability of the device and the software.
The prototype was characterized and tested with success in the laboratory and in field exposition under different conditions, in order to allow a measurement and analysis of the fulfilment of all requirements by the selected and realized electronic construction and layout.
The solution presented may serve as a basis for future development and application in this special showcase and within similar technologies. A prognosis of future work and applications concludes this work.
Social Business Documents: An Investigation of their Nature, Structure and Long-term Management
(2018)
Business documents contain valuable information. In order to comply with legal requirements, to serve as organisational knowledge and to prevent risks they need to be managed. However, changes in technology with which documents are being produced introduced new kinds of documents and new ways of interacting with documents. Thereby, the web 2.0 led to the development of Enterprise Collaboration Systems (ECS), which enable employees to use wiki, blog or forum applications for conducting their business. Part of the content produced in ECS can be called Social Business Documents (SBD). Compared to traditional digital documents SBD are different in their nature and structure as they are, for example, less well-structured and do not follow a strict lifecycle. These characteristics bring along new management challenges. However, currently research literature lacks investigations on the characteristics of SBD, their peculiarities and management.
This dissertation uses document theory and documentary practice as theoretical lenses to investigate the new challenges of the long-term management of SBD in ECS. By using an interpretative, exploratory, mixed methods approach the study includes two major research parts. First, the nature and structure of Social Business Documents is addressed by analysing them within four different systems using four different modelling techniques each. The findings are used to develop general SBD information models, outlining the basic underlying components, structure, functions and included metadata, as well as a broad range of SBD characteristics. The second phase comprises a focus group, a case study including in-depth interviews and a questionnaire, all conducted with industry representatives. The focus group identified that the kind of SBD used for specific content and the actual place of storage differ between organisations as well as that there are currently nearly no management practices for SBD at hand. The case study provided deep insights into general document management activities and investigated requirements, challenges and actions for managing SBD. Finally, the questionnaire consolidated and deepened the previous findings. It provides insights about the value of SBD, their current management practices as well as management challenges and needs. Despite all participating organisations storing information worth managing in SBD most are not addressing them with management activities and many challenges remain.
Together, the investigations enable a contribution to practice and theory. The progress in practice is summarised through a framework, addressing the long-term management of Social Business Documents. The framework identifies and outlines the requirements and challenges of and the actions for SBD management. It also indicates the dependencies of the different aspects. Furthermore, the findings enable the progress in theory within documentary practice by discussing the extension of document types to include SBD. Existing problems are outlined along the definitions of records and the newly possible characteristics of documents emerging through Social Business Documents are taken into account.
Companies try to utilise Knowledge Management (KM) to gain more efficiency and effectiveness in business. The major problem is that most of these KM projects are not or rarely based on sustainable analyses or established theories about KM. Often there is a big gap between the expectations and the real outcome of such KM initiatives. So the research question to be answered is: What challenges arise in KM projects, which KM requirements can be derived from them and which recommendations support the goal of meeting the requirements for KM? As theoretical foundation a set of KM frameworks is examined. Subsequently KM challenges from literature are analysed and best practices from case studies are used to provide recommendations for action on this challenges. The main outcome of this thesis is a best practice guideline,which allows Chief Knowledge Officers (CKOs) and KM project managers to examine the challenges mentioned in this thesis closely, and to find a suitable method to master these challenge in an optimal way. This guideline shows that KM can be positively and negatively influenced in a variety of ways. Mastering Knowledge Management (KM) in a company is a big and far-reaching venture and that technology respectively Information Technology (IT) is only a part of the big picture.
With global and distributed project teams being increasingly common Collaborative Project Management is becoming the prevalent paradigm for the work in most organisations. Software has for many years been one of the most used tools for supporting Project Management and with the focus on Collaborative Project Management and accompanied by the emergence of Enterprise Collaboration Systems (ECS), Collaborative Project Management Software (CPMS) is gaining increased attention. This thesis examines the capabilities of CPMS for the long-term management of information which not only includes the management of files within these systems, but the management of all types of digital business documents, particularly social business documents. Previous research shows that social content in collaboration software is often poorly managed which poses challenges to meeting performance and conformance objectives in a business. Based on literature research, requirements for the long-term management of information in CPMS are defined and 7 CPMS tools are analysed regarding the content they contain and the functionalities for the long-term management of this content they offer. The study shows that CPMS by and large are not able to meet the long-term information management needs of an organisation on their own and that only the tools geared towards enterprise customers have sufficient capabilities to support the implementation of an Enterprise Information Management strategy.