A visual analysis of the process of process modeling

Claes, Jan; Vanderfeesten, Irene; Pinggera, Jakob; Reijers, Hajo A.; Weber, Barbara; Poels, Geert

doi:10.1007/s10257-014-0245-4

Cited by 36 publications

(32 citation statements)

References 50 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Their analysis shows that most approaches use the modeling results as their objects of investigation and omit the process of modeling itself. This diagnosis remains true also in more recent research (Nelson et al 2011;Claes et al 2013). In this light, Gemino and Wand (2004) propose to also to assess the effectiveness of the process of model creation and model interpretation.…”

Section: Related Workmentioning

confidence: 81%

“…Examining the process of conceptual modeling is an area of research that has gained momentum in the last years (Claes et al 2013;Soffer et al 2012). Research in the area of process management traditionally has taken the existence of appropriate models for granted (Hjalmarsson et al 2015), and has hardly addressed the questions of how models should be created, who should be involved during creation, and how an appropriate representation of the real world could be assessed.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Evaluation of collaborative modeling processes for knowledge articulation and alignment

Oppl

2016

Inf Syst E-Bus Manage

View full text Add to dashboard Cite

The evaluation of modeling processes for years has focused on assessing the outcome of modeling, while the process of modeling itself hardly has been subject of examination. Only in recent years, with rising interest in collaborative conceptual modeling approaches, the process of modeling has gained more attention. Different streams of research have focused on examining the sequence of model manipulations or have considered the collaborative modeling to be a negotiation process and shaped evaluation criteria accordingly. This article proposes to add the perspective of articulation and alignment of the topic of modeling to the potential foci of evaluation. Its contribution is to show, how existing research originating in theories of co-construction of knowledge can be adapted for this purpose and how the adopted perspective is complementary to those already available in related work. A comparative field study applying different evaluation methods on a single real world showcase is presented to show the practical applicability of the approach and allows to identify potential for the combination of previously unrelated analytical dimensions.

show abstract

Section: Related Workmentioning

confidence: 81%

Section: Introductionmentioning

confidence: 99%

Evaluation of collaborative modeling processes for knowledge articulation and alignment

Oppl

2016

Inf Syst E-Bus Manage

View full text Add to dashboard Cite

show abstract

“…Sedrakyan, et al performed a process mining analysis on observational data and concluded that process modeling seems to require more effort than data modeling, and that in general it seems to be a successful tactic to start with the essence and iteratively add details to your model, which results in a quick growth of the model at the start and a slower pace of adding elements later on when thinking about the more challenging details [21]. To conclude, Claes, et al described various patterns of process modeling, ranging from timing and spread of creation, movement and deletion of model elements to more general modeling patterns such as the process modeling styles discussed in Section 3.1 [9,11].…”

Section: 2mentioning

confidence: 99%

“…This approach consists of three phases. First, a set of more than 1.000 observations of modeling sessions was collected and analyzed [8,9]. Second, we are currently completing the knowledge generation phase guided by the work of Gregor, et al about theory building [10].…”

Section: Introductionmentioning

confidence: 99%

Towards a Structured Process Modeling Method: Building the Prescriptive Modeling Theory

Claes

Vanderfeesten

Gailly

et al. 2017

Business Process Management Workshops

Self Cite

View full text Add to dashboard Cite

Abstract. In their effort to control and manage processes, organizations often create process models. The quality of such models is not always optimal, because it is challenging for a modeler to translate her mental image of the process into a formal process description. In order to support this complex human processing task, we are developing a smart process modeling method. This paper describes how we have built the underlying prescriptive theory, which is constructed from existing evidence about successful information processing techniques in cognitive psychology.Keywords: business process management, business process modeling, human aspects of bpm, smart bpm, process of process modeling IntroductionIn an ever-increasing competitive market and in the context of globalization, masscustomization and risk management, it is currently considered important for organizations to manage and control their core processes. One of the instruments developed to support process management are process models, i.e., representations of certain aspects of the process that abstract from individual process executions [1].Process models are typically constructed to support communication, documentation, analysis, simulation, execution, etc.[1]. Quality of process models can thus be seen as a measure of how well the model succeeds in supporting the goal: i.e. the fit-for-purpose. Hence, various process model quality variables and metrics have been studied and developed, related to different goals [2,3] As such, the business process management community has developed a good understanding of what constitutes a 'good' process model. In contrast, far less is

show abstract

“…From the perspective of creating BP models, some works focus on investigating the way a process modeler creates a process model and link the implemented modeling approach to the syntactic and semantic quality and the understandability of the resulting model (e.g., [4], [15]). One of the main conclusions from these works is that modelers have various styles of modeling and that a structured approach (i.e.…”

Section: Related Workmentioning

confidence: 99%