Process Modeling Recommender Systems

Fellmann, Michael; Metzger, Dirk; Jannaber, Sven; Zarvic, Novica; Thomas, Oliver

doi:10.1007/s12599-018-0517-5

Cited by 15 publications

(5 citation statements)

References 26 publications

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“…As we will point out in the next section, our results stimulate future research on the usage of digital nudging in other BPM lifecycle phases. For example, Fellmann et al (2018) call for a "quicker approach for managing and modeling business processes" (p. 21). In our opinion, digital nudging may help extend recommender systems to model business processes more efficiently in the future.…”

Section: Discussionmentioning

confidence: 99%

Exploring potentials of digital nudging for business processes

Bammert

König

Roeglinger

et al. 2020

BPMJ

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PurposeBusiness process improvement is vital for organizations as business environments are becoming ever more volatile, uncertain, complex and ambiguous. Process improvement methods help organizations sustain competitiveness. Many existing methods, however, do not fit emerging business environments as they entail initiatives with long implementation times, high investments and limited involvement of process participants. What is needed are agile process improvement approaches. The purpose of this paper is to explore the potential of digital nudging – a concept offering tools that lead individuals to better decisions – to improve business processes.Design/methodology/approachUsing process deviance as theoretical lens, an online experiment with 473 participants is conducted. Within the experiment, business processes and digital nudges are implemented to examine whether digital nudging can mitigate the weaknesses of existing process improvement methods.FindingsDigital nudging can influence the decisions of process participants and entail positive process deviance that leads to process improvement opportunities. Further, the research gives a first hint on the effectiveness of different digital nudges and lays the foundation for future research.Research limitations/implicationsSince exploring a completely new field of research and conducting the experiment in a synthetic environment, the paper serves as a first step toward the combination of digital nudging, business process improvements and positive process deviance.Originality/valueThe major achievement reported in this paper is the exploration of a new field of research. Thus, digital nudging shapes up as a promising foundation for agile process improvement, a discovery calling for future research at the intersection of digital nudging and business process management.

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Section: Discussionmentioning

confidence: 99%

Exploring potentials of digital nudging for business processes

Bammert

König

Roeglinger

et al. 2020

BPMJ

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“…In this study, it is revealed that there exist methods in which recommendation is made during business process modeling to assist a designer in completing the process model designing 36–38 . This assistance can provide autocompleting mechanisms to choose the next best nodes to complete the workflow.…”

Section: Methodsmentioning

confidence: 99%

“…In this study, it is revealed that there exist methods in which recommendation is made during business process modeling to assist a designer in completing the process model designing. [36][37][38] F I G U R E 4 Venn diagram of the scope of this review study the workflow. This review is restricted by primary studies describing recommendation in PM not in business process management (BPM) area.…”

Section: Inclusion and Exclusion Criteriamentioning

confidence: 99%

A survey on recommendation in process mining

Eili

Rezaeenour

2022

Concurrency and Computation

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Recommender systems have been widely applied in several domains to make informed decisions by recommending items that might be of interest. Considering recommendation during business process execution is also highly advantageous as the efficient suggestions about possible activities or resources can impact process performance. However, the deployment of the recommendation frameworks in process mining still needs more investigations to identify the current challenges to enable the practical application of research findings and ensure a large-scale adoption of this technique. Accordingly, a systematic review is conducted to provide a taxonomy of the published studies on process-aware recommender systems based on specified criteria, including the type and perspective of recommendation, a list of datasets and evaluation metrics used in the setting of PARS, implementation environments, and different algorithms used in PARS. In this regard, there are various insights extracted from this study: (i) Most studies in the business process analysis domain are of descriptive and predictive nature, (ii) recommendation in process mining is an emerging research area that is being evolving; the majority of proposals relate to 2015 and after that, and (iii) due to the lack of common evaluation protocol, datasets, and metrics, most studies are validated through experiments and prototyping, with less tendency to the practical implementation of a solution regarding real scenarios.

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“…Gadatsch (2020) distinguishes between (1) tools for modeling, analyzing, and designing processes (BPM tools) and ( 2) tools for control, automation, and automated analysis of processes such as workflow management systems, robotic process automation tools, and process mining tools. Fellmann et al (2018) conducted a survey of 47 participants with practical modeling skills: The respondents have used 'the ARIS platform (40.4%), MS Visio (31.9%), Signavio (14.9%), Adonis (8.5%), and various office products. '…”

Section: How Tools Address Diversity In Conceptual Modelingmentioning

confidence: 99%

Informing Possible Future Worlds

2024

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For more than 35 years, Ulrich Frank has shaped Wirtschaftsinformatik as a scientific discipline through thoughtful and sophisticated research contributions and his numerous contributions to the scientific community.Informing Possible Future Worlds is the Festschrift in honour of Ulrich Frank on the occasion of his 65 th birthday. The Festschrift includes twenty-three essays written by friends, colleagues, and fellow researchers in recognition of Ulrich's contributions to Wirtschaftsinformatik research and the scientific community. Each essay is a personal and unique 'birthday present' to Ulrich Frank written exclusively for the Festschrift. From original research contributions to more personal reflections, the essays cover a wide range of topics, themes, and fields -just like Ulrich Frank's contributions.For more than 35 years, Ulrich Frank has shaped and promoted Wirtschaftsinformatik as a scientific discipline through his thoughtful and sophisticated research contributions and his numerous contributions to the scientific community. He has initiated, engaged in and promoted scientific discourse nationally and internationally, inspired, encouraged and guided young researchers, and played an outstanding part in the Wirtschaftsinformatik community.Starting with his Diplomarbeit in 1982 on 'Die Problematisierung von Zielbildungsprozessen in Unternehmungen durch die Betriebswirtschaftslehre unter besonderer Berücksichtigung des Verhältnisses von Wissenschaft und Praxis' (supervised by Erwin Grochla at the Universität zu Köln), Ulrich has cultivated his interest not only in Betriebswirtschaftslehre and Wirtschaftsinformatik, Software Engineering and Conceptual Modelling, but also in the Philosophy of Science, the Philosophy of Language, the Sociology of Knowledge and in Organisational Sociology. For his Diplomarbeit, he read Albert, Feyerabend, Mittelstrass, and Popper, among others, and reflected on organisational goal-setting ('Zielbildungsprozesse') from multiple, complementary perspectives -a lifelong leitmotiv he later incorporated in his Multi-Perspective Enterprise Modelling (MEMO) method.An avid reader and bibliophile, Ulrich must have learned about Niklas Luhmann, the German sociologist working at Universität Bielefeld, Ulrich's hometown, likely in his teens, and started his own personal discourse with Luhmann's writings, and from there on expanded his readings. At about the same time, Ulrich started to program computers, developed and sold his first software application, and, most importantly, discovered Smalltalk, the programming language created by Alan Kay and others at Xerox PARC's Learning Research Group -which has strongly influenced him to this day and which he has admired ever since.Following his discovery of Smalltalk, he took a deep dive into Object-Oriented Programming and Object-Oriented Modelling that took him to take a minor in Angewandte Informatik (Applied Informatics) at the Universität zu Köln during his graduate studies.vii His doctoral research with Alfred Kieser at Universität Mannheim ...

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Process Modeling Recommender Systems

Cited by 15 publications

References 26 publications

Exploring potentials of digital nudging for business processes

Exploring potentials of digital nudging for business processes

A survey on recommendation in process mining

Informing Possible Future Worlds

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