Towards a System Support of Collaborative Knowledge Work [original]

Towards a System Support of

Collaborative Knowledge Work

Nicolas Mundbrod, Jens Kolb and Manfred Reichert

Institute of Databases and Information Systems

Ulm University, Germany

{nicolas.mundbrod,jens.kolb,manfred.reichert}@uni-ulm.de

http://www.uni-ulm.de/dbis

Abstract. Knowledge work is becoming the predominant type of work

in developed countries. Leveraging their expertise, skills, and experiences,

knowledge workers daily deal with demanding situations. Therefore, they

widely work autonomously, but usually collaborate in multiple contexts.

Further, their work is influenced by dynamic factors like time constraints,

costs, and available resources, and thereby it cannot be pre-specified like

routine work. The lack of an appropriate context and process support,

in turn, reduces their productivity and hinders the reuse as well as the

continuous improvement of elaborated solutions. This paper structures

collaborative knowledge work and presents its characteristics and di-

mensions. Moreover, we introduce a lifecycle methodology to support

collaborative knowledge workers holistically.

Key words: Knowledge Work, Knowledge Workers, Collaboration, Life-

cycle Support, CSCW

1 Introduction

A change from an industrial towards a knowledge-based society is taking place

in developed countries: knowledge work is becoming the predominant type of

work [1]. Utilizing their distinguished skills, gained experiences, and expertise,

knowledge workers (e.g., doctors, engineers, or researchers) daily solve demand-

ing and sophisticated tasks. Hence, knowledge work represents an important

part of today’s corporate business processes. Contemporary process-aware infor-

mation systems (PAISs) are not able to support knowledge workers adequately

as pre-specified business process models are required. These models cannot be

provided since knowledge work’s tasks and their order are not predictable in

detail. Instead, knowledge workers have to manually interrelate process-related

information encapsulated in a variety of heterogeneous software systems (e.g., so-

cial and special-purpose software). Hence, there is no knowledge work assistance

comparable to the support a PAIS can provide for routine work.

Based on [2], this paper discussed how collaborative knowledge work (CKW)

can be supported by an adaptive information system (CKW system) (objective

I). For this purpose, a sound definitional framework of CKW is established and

2 Nicolas Mundbrod, Jens Kolb and Manfred Reichert

CKW characteristics and dimensions are presented based on a case study (objec-

tive II ). The remainder of this paper is structured as follows: Section 2 introduces

the fundamentals of CKW. Subsequently, Section 3 presents representative CKW

use cases. Section 4 provides CKW characteristics and dimensions. Section 5 in-

troduces a lifecycle methodology for CKW. Finally, Section 6 summarizes the

results and gives insights into future research.

2 Fundamentals of Collaborative Knowledge Work

2.1 Knowledge

Generally, the term of knowledge does not obtain a unique definition [3]. How-

ever, from the perspective of computer science, it is desirable to classify the terms

of data,information and knowledge as those are often used synonymously by

mistake. Data represents syntactic entities comprising a set of symbols (with no

meaning), whereas information represents the output from data interpretation

and hence data with meaning (i.e., semantics) [4]. Finally, knowledge is learned

information, incorporated in an agent’s reasoning resources (cf. Definition 1).

Definition 1. Knowledge is a fluid mix of framed experiences, values, contex-

tual information, and expert insights that provides a framework for evaluating

and incorporating new experiences and information. It originates and is applied

in the minds of knowers. In organizations, it often becomes embedded, not only

in documents or repositories, but also in organizational routines, processes, prac-

tices, and norms. [5]

For every collaboration, it is crucial that knowledge is communicable, en-

abling knowledge workers to easily share it. Already implied in Definition 1,

epistemological scientist Polanyi shaped a distinction between tacit and explicit

knowledge through the phrase “We can know more than we can tell” [6]. One

can hold tacit knowledge without having the capability to explicitly express the

quintessence, e.g., the capability to hold the balance on a bicycle. In contrast,

explicit knowledge is expressible in a formal, systematic language and therefore

it can be regarded as communicable knowledge (i.e., information). The differ-

entiation provides the basis for Nonaka’s and Takeuchi’s theory of (corporate)

knowledge creation [7]. Four different conversion modes between tacit and ex-

plicit knowledge are described: socialization (i.e., from tacit to tacit knowledge),

externalization (i.e., tacit to explicit), combination (i.e., explicit), and internal-

ization (i.e., explicit to tacit). A constant repetition of the different conversions

provides the basis of the individual and organizational knowledge generation

process: knowledge is spirally advanced and transferred from being individually

obtained to organizationally or even inter-organizationally shared (cf. Figure 1).

Towards a System Support of Collaborative Knowledge Work 3

Ontological

Dimension

Epistemological

Dimension

Inter-Organization

Internalization

Socialization

Explicit

Knowledge

Knowledge Level

Tacit

Knowledge

Combination

Externalization

OrganizationGroupIndividual

Fig. 1: Organizational Knowledge Creation Spiral [7]

2.2 Knowledge Work

Hube assessed 16 definitions of knowledge work in relation to four self-established

criteria: applicability,process description,context relation, and distinction [8]. He

suggests Definition 2 as the most appropriate one for knowledge work1[8].

Definition 2. Knowledge work is comprised of objectifying intellectual activ-

ities, addressing novel and complex processes and (work) results, which require

external means of control and a dual field of action.

Hube separates the term of knowledge work from the related term of intel-

lectual work. While intellectual work generally contains mental work, knowledge

work comprises only activities addressing novel and complex processes as well

as work results. Hence, routine mental work is excluded. Based on the theory of

action regulation, an individual performing knowledge work is supposed to use a

referential and an actual field of action [9]. In the referential field of action, one

merely deals with a problem theoretically. Thereby, one can deliberately act and

test different approaches, not causing any impact on the assignment. In com-

parison, necessary instruments, actions and resources are used in the actual field

of action to properly manage the complex processes. Further, the results of the

referential field of action are transferred to finally achieve the work’s objective.

2.3 Knowledge Work Process

Due to knowledge work’s focus on novelty and complexity, obviously, there is no

pre-specified process an individual can perform. However, a generic and ideal-

typical knowledge work process is described as shown in Figure 2. Note that

each of the process steps can be executed multiple times and might be skipped

as well. First, an individual performing knowledge work deducts an assignment

from an ambition and available information (Step 1). Subsequently, orientation

(2) and planning (3) in the actual field of action take place, the assignment is

1Definition 2 is translated from German.

4 Nicolas Mundbrod, Jens Kolb and Manfred Reichert

concretized, and possible resources are evaluated. Then, theoretical solutions are

reviewed (4) and a solution strategy is designed (5). Consequently, the plan is

put into operation (6), and the intermediate work result is constantly assessed.

On the one hand the result is evaluated considering its formal quality (7), on

the other hand the original plan might be adapted (8). Additionally, it is even

possible that the whole assignment has to be re-evaluated (9).

Objective and information

Assignment(s)

Output

Deduction (1)

Adaption (9)

Evaluation (7)

Evaluation (8)

Orientation (2)

Referential Field of Action

Actual Field of Action

Orientation (4)

Planning (3)

Planning (5)

Action (6)

Fig. 2: Generic Knowledge Work Process [8]

2.4 Knowledge Workers

Naturally, a knowledge work process highly depends on the knowledge of the in-

dividuals who perform knowledge work. There are various definitions addressing

the question who exactly is a knowledge worker or not (cf. [8, 10, 11]). Conclud-

ing, Definition 3 introduces the term of a knowledge worker [12].

Definition 3. Knowledge workers have high degrees of expertise, education,

or experience, and the primary purpose of their jobs involves the process and

accomplishment of knowledge work.

Obviously, whether an individual rates a task to be routine or rather novel

and challenging, depends on his personal degree of foreknowledge. Knowledge

workers exposing high degrees of expertise, education, and experience usually

deal better with novel and complex situations as others without respective fore-

knowledge. This coherence rounds out the connection between Definitions 2 and

3. Generally, knowledge workers comprise various professions: A manager of liter-

ally any company is supposed to perform knowledge work in order to successfully

manage and improve a company’s business [12]. Further, Definition 3 underlines

that knowledge workers hold responsible positions, i.e., their productivity is a

crucial concern for any company.

Usually, the processing of novel and complex problems is split into man-

ageable parts, which are assigned to knowledge workers who feature the needed

expertise and experiences [8]. However, based on their expertise and experiences,

knowledge workers are concurrently requested in multiple contexts, where they

need to adopt different roles. This exposes the main issues knowledge workers

face these days: they have to manually filter, classify and manage context-related

Towards a System Support of Collaborative Knowledge Work 5

information to project their thoughts into the corresponding context. Further-

more, they must cope with the related issue of attention fragmentation, while

trying to keep track of any progress being made in different context. In order to

adequately inspect the properties of CKW, Definition 4 defines it formally.

Definition 4. Collaborative knowledge work (CKW) is described as knowl-

edge work jointly performed by two or more knowledge workers in order to achieve

a common business goal.

3 Collaborative Knowledge Work Use Cases

To validate the definitions, three different CKW use cases are introduced.2Based

on these, CKW characteristics and dimensions are derived in Section 4.

UC1: Development Project. This use case is based on a development project

for an embedded system in the automotive sector. It features multidisciplinary

collaboration of knowledge workers, e.g., vehicles require complex mechatronic

systems developed by engineers of various professions. Typically, a best prac-

tice (e.g., a V-model) is used to systematically synchronize results of concurrent

development teams (i.e., qualitative development course) and to provide an un-

derstandable overview whereby knowledge workers can orientate. Moreover, a

virtual system prototype is created and gradually enhanced. Development, re-

search, and implementation projects can be generally considered to deal with

the well-organized creation of solutions (i.e., explicit knowledge) considering a

pre-defined problem. Complex problems are extensively studied, analyzed, and

evaluated up-front to collaboratively develop a solution based on a deployed

project methodology (e.g., a domain-related best practice).

UC2: Criminal Investigations. Criminal investigations are addressed in this

use case: “an investigation is the examination, study, tracking, and gathering of

factual information that answers questions or solves problems” [13]. Investigative

work often contains several concurrently emerging angles with dedicated inves-

tigative staff members ascertaining. While there are standardized investigative

actions (e.g., securing of evidence), investigators in charge have to individually

determine which of the standard procedures need to be applied. Comparably,

the work of attorneys, judges and researchers is naturally connected to the work

of public investigation authorities. Moreover, companies are increasingly obliged

to provide information on requests of customers, citizens, regulators, or board

members (e.g., audit requests or fraud detection).

UC3: Complex Financial Service Request. Business processes in the fi-

nancial service sector are highly standardized today. However, there are still

exceptional situations which have to be handled individually. Presumably, a

financial service company receives a request for a large-scale combination of

2Detailed descriptions of the use cases are available in [2].

6 Nicolas Mundbrod, Jens Kolb and Manfred Reichert

financial products from a key customer. Therefore, financial experts, who are

specialized to specific products, are involved on demand by the responsible key

account manager to meet the customer’s needs. In this case, related use cases are

insurance claim handling, product change requests, loan origination, customer

onboarding, and intensive patient care. All these have in common that they are

dependent on human assessment and decisions based on expertise and experi-

ences, continuously gained information and the proper handling of unexpected

events and occurring problems.

4 Characteristics and Dimensions

Based on the use cases (cf. Section 3), characteristics (cf. Section 4.1) and di-

mensions (cf. Section 4.2) are presented. Figure 3 gives an overview of the CKW

characteristics and their coherence.

4.1 CKW Characteristics

C1: Uncertainty. The notion of complexity, implicitly addressed by knowl-

edge work, refers to problems or situations comprising an unmanageable set of

influencing factors intertwined via dynamic correlations [8]. Consequently, the

generic knowledge work process (cf. Section 2.3) includes three feedback loops

that are motivated by the need to continuously assess the planned and finally

conducted actions. The course of actions is dynamically determined by the in-

volved knowledge workers and based on their expertise and experiences. Consid-

ering the collaboration of knowledge workers, obviously, labor division comprises

interdependencies and mutual interference between involved knowledge workers

which further increase the general dynamics.

C2: Goal Orientation. Acommon goal, e.g., to meet customer’s needs (cf.

UC3), can be considered as the integrative factor for knowledge workers. In

relation, Drucker stated that the crucial question in a knowledge worker’s pro-

ductivity is “what is the task?” [14]. In UC2, investigators collaborate to solve

a crime and thereby derive the required tasks. Ideally, knowledge workers’ indi-

vidual goals are well integrated into the scope of a common goal. To adequately

cope with complex and unpredictable CKW, sub-goals3are derived that are

achievable in a shorter period of time. While a common goal in CKW should

remain rather stable, sub-goals can be modified or even removed.

C3: Emergence. While pursuing a common goal and addressing uncertainty,

knowledge workers continually adapt activities to successfully achieve their sub-

goals. As a result of C1, knowledge workers have to focus on the planning of

activities conducted any time soon (proximity of time). Activities scheduled

later on might be brought up in principle, but not defined in detail yet. This

3Also commonly known as milestones.

Towards a System Support of Collaborative Knowledge Work 7

Common Goal

Subgoal 1

Subgoal 2

Individual Goal

Individual

Knowledge Base

Individual

Knowledge Base

Time and Progress

Common Growing Knowledge Base

Key

State achieved by two Knowledge Workers

State achieved by one Knowledge Worker

Possible states Knowledge Workers can achieve

...

Inf. Factor

Action performed by a Knowledge Worker

Influencing Factor

Knowledge Worker A Knowledge Worker‘s individual Knowledge Base

Possible actions a Knowledge Worker can

choose in a current state

Individual

Knowledge Base

Fig. 3: CKW Characteristics and their Coherence

agile planning and working implicates that CKW processes gradually emerge:

knowledge workers constantly evaluate possible activities on the basis of their

current state and in consideration of influencing factors. At every point, they

have the choice between several performable actions to achieve further states

and to further approach their common goal (cf. Figure 3).

C4: Growing Knowledge Base. Externalization of knowledge in the shape of

communicable information is crucially needed to achieve organizationally shared

knowledge—a prerequisite for collaboration (cf. Section 2.1). CKW’s explicit

knowledge base usually comprises heterogeneous information, which has to be

managed properly (e.g., office documents, e-mails, and handwritten notes). In

general, the progress of a use case towards its goal is strongly connected to the

advancement of the tacit and explicit knowledge base. For instance, information

like schedules, responsibilities and methodologies is stepwise created to orga-

nize the project at the beginning of UC1. Afterwards, a prototype or developed

components can represent the current state of development.

4.2 Dimensions

Naturally, countless dimensions can be considered by which CKW scenarios

could be differentiated. Hence, this section focuses on dimensions clearly ex-

posing significant implications for the system support of CKW.

8 Nicolas Mundbrod, Jens Kolb and Manfred Reichert

D1: Knowledge Action Type. CKW can be differentiated by the predom-

inant way the knowledge workers deal with knowledge and information. In re-

lation, Davenport distinguishes between the knowledge actions acquisition,ap-

plication,creation,dissemination,documentation, and packaging of knowledge

[15]. Further types are presented in [16, 17]. Although there are different ap-

proaches, pragmatic analyses of the main knowledge actions can yield benefits

as the support of CKW can be adjusted accordingly.

D2: Methodology. The degree of adherence to a common methodology dis-

cernibly varies in UC1-UC3. The automotive development team (UC1), for ex-

ample, decides to apply a V-model to organize CKW and to ensure a qualitative

development progress. While individual activities are still subject to the different

knowledge workers, an overall defined methodology is given. Methodologies do

not have to be explicitly illustrated, renowned or even described to be success-

fully applied: a team can follow a tacit methodology, known and accepted by all

knowledge workers as well as robust in the face of varying conditions.

D3: Interdisciplinarity. The use cases UC1-UC3 additionally unveiled that

CKW varies from domain-specific to interdisciplinary work. CKW involving

different domains can lead to misunderstandings, discords (e.g., about com-

mon procedures), or even severe inconsistencies. In this context, synonyms and

homonyms can result in high effort to synchronize contributions. However, es-

pecially interdisciplinary work is highly promising for novel and complex issues.

D4: Organizational Frame. CKW is not compulsorily bound to organiza-

tional units or hierarchical structures. It can be distinguished by the surrounding

organizational frame as well. In general, knowledge workers usually collaborate

either spontaneously (i.e., without a dedicated organizational frame), or based on

organizational frames like a case or project. Especially coordination aspects (i.e.,

responsibilities, organizational models, work allocations, and synchronizations)

are influenced by the surrounding organizational frame.

D5: Spatial Proximity. Apart from preferred knowledge actions and organi-

zational frames, CKW depends on the fact whether knowledge workers can di-

rectly communicate with each other, or not. Physical closeness empowers knowl-

edge workers to directly communicate face to face, whereas physically separated

knowledge workers obviously have to rely on communication and collaboration

tools to virtually bridge a spatial gap. Hence, CKW can be distinguished by the

degree of spatial proximity the knowledge workers have during their collabora-

tion.

D6: Involved Knowledge Workers. The number of involved knowledge work-

ers can vary between CKW projects as well. The complexity of CKW is a driver

of the knowledge workers’ headcount. Moreover, the corporate importance of

CKW may be another reason to include more knowledge workers. In general,

the number of involved knowledge workers results in an increased demand for

appropriate support, especially for the systematic allocation and synchronization

of work (coordination).

Towards a System Support of Collaborative Knowledge Work 9

D7: Temporal Constraints. Time constraints [18] may also distinguish CKW

projects. For example, fixed deadlines can be initially connected with objectives

(i.e., fixed time frames). Considering UC2, there are sometime only relative or

even no fixed deadlines, but investigators still suffer from a time pressure to solve

the crime. In general, some CKW projects may be scheduled for months or even

years whereas others have to be finished within hours or days.

D8: Information Interdependency. The acquisition of information to de-

tect causal relationships can be regarded as the main purpose of investigative

activities (cf. use case UC2). Closely related to dimension D1 and characteristic

C4, CKW can also be distinguished by the complexity and importance of infor-

mation interdependencies. Apart from internal information interdependencies in

a company, CKW projects can also feature coordinative and information inter-

dependencies between each other. Furthermore, the degree of interdependencies

also raises coordination efforts.

D9: Number of Repetitions. The number of repetitive occurrences provides

another dimension to distinguish CKW. As CKW is characterized to be emer-

gent and rather unique, the dimension might sound curious. However, when

common goals are considered in detail, a repetitive occurrence of CKW can be

observed. Apart from a common goal, the presented dimensions D1-D8 can also

be utilized to determine whether CKW projects share common properties. In

general, the provision of a specific support for CKW depends on the possibility

to determine the level of similarity an ongoing collaboration shares with already

finished CKW. Thereby, it has to be assessed which parts of past scenarios can be

leveraged for the support of the ongoing collaboration (i.e., sustainable support).

5 Collaborative Knowledge Work Lifecycle

In order to systematically support CKW by a dedicated information system

(CKW system), the availability, advancement and communication of knowledge

have to be ensured. If knowledge workers are empowered to quickly retrieve

context-relevant information as well as experiential knowledge in the right shape

and at the right point of time, their efficiency and effectiveness can be increased

[8]. To establish a context- and process-aware support, the BPM lifecycle [19] can

be leveraged: the Collaborative Knowledge Work Lifecycle (CKWL) (cf. Figure

4) describes integral phases, a CKW system has to provide.

The lifecycle consistently draws on the generic knowledge work process (cf.

Section 2.3) as it features the phases Orientation4,Template Design,Collabora-

tion Run Time, and Records Evaluation. Further, it includes action regulation

(cf. Section 2.2) implemented by a feedback loop (i.e., knowledge retrieval). The

subsequent sections discuss the different lifecycle phases in detail.

4The CKWL is entered in the orientation phase

10 Nicolas Mundbrod, Jens Kolb and Manfred Reichert

Records Evaluation

Orientation

Template Design

Collaboration

Run Time

Knowledge Retrieval Knowledge

Retrieval

Collaboration

Instance

Collaboration

Instance

Collaboration

Instance

CIn-n

CIn-1

CIn-0 ...

Collaboration

Instance

Collaboration

Instance

Collaboration

Instance

CI0-n

CI0-1

CI0-0 ... Interviews

Collaboration

Records

Collaboration

Templates

Literature

Analytics

CTn

CT1

CT0

CR0-n

CR0-y

CR0-x

CR0-z

CR0-y

CRn-x

Fig. 4: The Collaborative Knowledge Work Lifecycle

Orientation Phase. Information about how knowledge workers usually collab-

orate in a certain context has to be gathered in the orientation phase. Dimension

D9 implies that CKW can be regarded to occur multiple times and hence be

aggregated to a dedicated collaboration type. To perform a sound aggregation,

dimensions D1-D8 can be utilized. Moreover, records of finalized collaborations

are leveraged, involved knowledge workers systematically interviewed, or subject-

related literature and expert experiences taken into consideration. In general,

while the flow of activities is the main subject in the design phase of the BPM

lifecycle, the orientation phase focuses on the knowledge workers’ information

flow. So, data sources and relevant information systems need to be explicitly doc-

umented and integrated [20]. Besides identifying information sources, the main

knowledge actions of knowledge workers have to be considered as well (cf. D1).

Further, their communication structure has to be addressed, especially in case

that knowledge workers are distributed and need to communicate remotely (cf.

D5). Coordination aspects also have to be taken into account: for instance, com-

monly used methodologies, organizational frames and frequently arising tasks

must be documented. Finally, awareness information knowledge workers require

to initiate, perform and manage communication and coordination has to be cov-

ered, as well.

Template Design Phase. Based on a thorough examination of collaboration

types and their implicit information flows, collaboration templates (CT) need to

be created. Thereby, a CT is comparable to a process model supporting stan-

dardizable work. A certain CT is then leveraged as a blueprint for a range of

collaboration instances (CIs). A CI refers to a virtual unit supporting CKW, e.g.,

a specific development project. The involved knowledge workers are initially sup-

ported by providing access to the content they likely require when performing

their work. However, in comparison to a process model, a CT neither prescribes

a set of activities nor their ordering. Predominantly, it is supposed to provide

information access, communication, and coordination support embedded in an

Towards a System Support of Collaborative Knowledge Work 11

adaptable and growing CKW system. Further, a CT features a goal for the

optimal collaboration between knowledge workers in relation to their current

context. Logically, a CT has to be highly adaptable and carefully designed in

order to support knowledge workers without obtruding or even restraining them.

Collaboration Run Time Phase. Knowledge workers can instantiate a CT

according to their preferences and within their current CKW context. If there is

no adequate CT available, knowledge workers can choose a rather generic CT.

Moreover, CTs have to be highly adaptive to empower knowledge workers to

conduct a wide range of changes without being overstrained by technical details

and issues. Knowledge workers are supposed to fully utilize the defined CT to

collaborate towards the achievement of their common goal in CKW. On the

basis of available information, knowledge workers can communicate and coordi-

nate using communication and coordination features of a supportive system, or

additionally available, context-related integrated systems. Finally, the effective-

ness and efficiency of knowledge workers’ collaboration depends on the provision

of experiential knowledge as well. Knowledge workers need to be able to ac-

cess collaboration records (CR; i.e., finalized CIs) in order to retrieve important

information, i.e., knowledge that can substantially facilitate and speed up the

achievement of a common goal.

Records Evaluation Phase. CRs can be considered as an important common

knowledge base for CIs and knowledge workers involved. Knowledge workers can

look up details about past CKW and benefit from documentations. Furthermore,

information and their interdependencies from a particular CI can be compared

with information and connections available in the archived CRs. In addition,

CRs can be used for advancing existing CTs as well as for developing new ones.

Moreover, a finished and archived CI can also be used as starting point for a

succeeding CI, drawing upon the achieved results and established knowledge

base. Naturally, a CKW system should check which parts of a specific CT have

been adapted during run time or not been used. Moreover, involved knowledge

workers may be interviewed to rate the importance and relevance of information

for future endeavors.

6 Conclusion

This paper provides sound definitions in terms of knowledge work,knowledge

worker and CKW for future use in the scope of BPM (objective II). The def-

initions are validated by assessing representative use cases, resulting in CKW

characteristics and dimensions that can be leveraged to underpin future CKW

support. For the latter, a generic CKW methodology is introduced by the CKWL

(objective I) aiming at significant improvement of knowledge workers’ produc-

tivity.

As a conclusion, the holistic and process-oriented support for collaborative

knowledge workers is a challenge in the literal sense. Although there is a broad

12 Nicolas Mundbrod, Jens Kolb and Manfred Reichert

range of available technologies targeting single aspects, the integration of those

into a utilizable support implies high efforts and distinguished concepts for the

interplay of these technologies. However, the provided aspects may be used as a

vision to gradually extend and interconnect concepts and technologies towards

an intended holistic support according to the CKWL.

References

1. Pfiffner, M., Stadelmann, P.: Wissen wirksam machen. Haupt Verlag, Bern (1998)

2. Mundbrod, N.: Business Process Support for Collaborative Knowledge Workers.

Master thesis, Ulm University (2012)

3. Alavi, M., Leidner, D.E.: Review: Knowledge Management and Knowledge Man-

agement Systems: Conceptual Foundations and Research Issues. MIS Quarterly

25(1) (2001) 107–136

4. Aamodt, A., Nygard, M.: Different Roles and Mutual Dependencies of Data, In-

formation, and Knowledge - An AI Perspective on their Integration. Data and

Knowledge Engineering 16(3) (1995) 191–222

5. Davenport, T.H., Prusak, L.: Working Knowledge. Harvard Business School Press,

Boston (2000)

6. Polanyi, M.: Tacit Dimension. Peter Smith Publisher Inc, Gloucester, Mass. (1983)

7. Nonaka, I., Takeuchi, H.: The Knowledge-Creating Company. Oxford University

Press, New York (1995)

8. Hube, G.: Beitrag zur Beschreibung und Analyse von Wissensarbeit. PhD thesis,

University of Stuttgart, Stuttgart (2005)

9. Resch, M.: Die Handlungsregulation geistiger Arbeit. Huber, Bern (1988)

10. Tiemann, M.: Wissensintensive Berufe. Bundesinstitut f¨ur Berufsbildung, Bonn

(2010)

11. Swenson, K.D.: The Nature of Knowledge Work. In Swenson, K.D., ed.: Mastering

the Unpredictable. How Adaptive Case Management Will Revolutionize the Way

That Knowledge Workers Get Things Done. Meghan-Kiffer-Press (2010) 5–28

12. Davenport, T.H.: Thinking for a Living: How to Get Better Performance and

Results from Knowledge Workers. Harvard Business School Press (2005)

13. Sennewald, C.A., Tsukayama, J.K.: The Process of Investigation. Butterworth-

Heinemann ET - 3 TS - WorldCat, Burlington, MA (2006)

14. Drucker, P.F.: Management Challenges for the 21st Century. Elsevier Science &

Technology, Oxford (2007)

15. Davenport, T.O.: Human Capital. Jossey-Bass, San Francisco (1999)

16. Holsapple, C.W., Jones, K.: Exploring Primary Activities of the Knowledge Chain.

Knowledge and Process Management 11(3) (2004) 155–174

17. Reinhardt, W., Schmidt, B., Sloep, P., Drachsler, H.: Knowledge Worker Roles and

Actions-Results of Two Empirical Studies. Knowledge and Process Management

18(3) (2011) 150–174

18. Lanz, A., Weber, B., Reichert, M.: Workflow Time Patterns for Process-aware

Information Systems. In: BPMDS 2010 and EMMSAD 2010, Hammamet, Tunisia,

Springer Heidelberg (June 2010) 94–107

19. Reichert, M., Weber, B.: Enabling Flexibility in Process-Aware Information Sys-

tems: Challenges, Methods, Technologies. Springer, Berlin Heidelberg (2012)

20. Michelberger, B., Mutschler, B., Reichert, M.: A Context Framework for Process-

oriented Information Logistics. In: 15th Int’l Conference on Business Information

Systems (BIS 2012), Vilnius, Lithuania, Springer Heidelberg (May 2012) 201–212