An Overview of Methods for Acquiring and Generating Decision Models

Etikala, Vedavyas; Vanthienen, Jan

doi:10.1007/978-3-030-82153-1_17

Cited by 9 publications

(2 citation statements)

References 28 publications

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“…Furthermore, decision logic is defined as: "a collection of business DIGITAL RESTRUCTURING AND HUMAN (RE)ACTION rules, business decision tables, or executable analytic models to make individual business decisions". There are multiple ways for an organization to discover decisions and the underlying decision logic (Etikala & Vanthienen, 2021). The most common way is to acquire knowledge from domain experts and manually model the gained information to decisions and the underlying decision logic.…”

Section: Background and Related Workmentioning

confidence: 99%

“…The most common way is to acquire knowledge from domain experts and manually model the gained information to decisions and the underlying decision logic. However, many other sources exist to gather decisions and the underlying business logic such as event logs, text documents, and decision logs (Etikala & Vanthienen, 2021). These sources can be used to automatically discover the decisions and underlying decision logic, which minimizes the cost and time spent on manual modeling with the help of domain experts.…”

Section: Background and Related Workmentioning

confidence: 99%

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35 th Bled eConference Digital Restructuring and Human (Re)action

2022

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There is widespread recognition that, during the process of digitalisation, much greater care is necessary in relation to the needs of individuals and society. One key area in which tensions exist is identity management. People think that their identities are intrinsic to themselves. Yet organisations represent themselves as 'provisioning' people with their 'identities'. In addition, the model of identity that organisations typically use evidences some important deficiencies. A fresh approach is needed to the model that underpins organisations' management of their relationships with people. This needs to be based on a deeper appreciation by designers of the nature of the phenomena that they seek to document and to exercise control over. A model of those phenomena is needed that is pragmatic, in the sense of fulfilling the needs of information systems (IS) practitioners and organisations, but also of the people whose data the organisation handles. It also needs to reflect metatheoretic insights. This paper presents such a model. It commences by drawing on ontology, epistemology and axiology in order to establish an outline metatheoretic model. The model is articulated, at the conceptual level and at the data modelling level. Initially, a relatively simple model is established, sufficient for inanimate objects and artefacts. The more complex requirements of humans are then addressed. It is contended that the resulting model provides a robust framework for identification and authentication in IS. 2 35 TH BLED ECONFERENCE DIGITAL RESTRUCTURING AND HUMAN (RE)ACTION R. Clarke: A Reconsideration of the Foundations of Identity Management 3 6 35 TH BLED ECONFERENCE DIGITAL RESTRUCTURING AND HUMAN (RE)ACTION EpistemologyThis section summarises analysis in Clarke ( 2021). Epistemology is the study of knowledge. Two contrasting conceptions of knowledge exist. The proposition of the first, 'empiricism', is that knowledge is derived from sensory experience, and is a body of facts and principles accumulated by humankind over the course of time, that are capable of being stored in the equivalent of a warehouse. This works well in circumstances where the Things represented by Entities are real rather than imaginary, and are inanimate, and their handling is largely mechanical. Examples include aircraft guidance systems and robotic production-lines.The other, 'apriorist' view is that that knowledge is internal and personal, and the concept is not applicable outside the mind of an individual human. Within this school of thought, knowledge is the matrix of impressions within which an individual situates newly acquired information.In order to cater for these two extremes, the term 'Knowledge' is best avoided, except when qualified by one of two adjectives:

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Section: Background and Related Workmentioning

confidence: 99%

Section: Background and Related Workmentioning

confidence: 99%

35 th Bled eConference Digital Restructuring and Human (Re)action

2022

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Discovering operational decisions from data—a framework supporting decision discovery from data

Leewis,

Smit,

Versendaal

2024

Decision

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Analyzing historical decision-related data can help support actual operational decision-making processes. Decision mining can be employed for such analysis. This paper proposes the Decision Discovery Framework (DDF) designed to develop, adapt, or select a decision discovery algorithm by outlining specific guidelines for input data usage, classifier handling, and decision model representation. This framework incorporates the use of Decision Model and Notation (DMN) for enhanced comprehensibility and normalization to simplify decision tables. The framework's efficacy was tested by adapting the C4.5 algorithm to the DM45 algorithm. The proposed adaptations include (1) the utilization of a decision log, (2) ensure an unpruned decision tree, (3) the generation DMN, and (4) normalize decision table. Future research can focus on supporting on practitioners in modeling decisions, ensuring their decision-making is compliant, and suggesting improvements to the modeled decisions. Another future research direction is to explore the ability to process unstructured data as input for the discovery of decisions.

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Factors Shaping the Cashless Payment Ecosystem: Understanding the Role of Participating Actors

Khando¹,

Islam²,

Gao³

2022

35 Th Bled eConference Digital Restructuring and Human (Re)action

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Cashless payments have become increasingly popular around the world because of their numerous advantages. More so, the cashless payment adoption has been escalated during the Covid-19 pandemic. However, there is a lack of holistic studies on the adoption and contemporary practices of cashless payments. The purpose of this study is, therefore, to provide a comprehensive understanding by identifying the participating actors and their crucial role in the payment ecosystem. Thus, the paper aims to address two research questions: i) Who are the participating actors in the cashless payment ecosystem? and ii) What are the determinant factors for the actors to adopt the cashless payment ecosystem? Through scoping literature review of 63 articles published in the last seven years (2015-2021), six participating ecosystem actors are identified with their determinant factors. The study contributes towards addressing adoption issues and serves as a basis for future empirical investigation.

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An Overview of Methods for Acquiring and Generating Decision Models

Cited by 9 publications

References 28 publications

35 th Bled eConference Digital Restructuring and Human (Re)action

35 th Bled eConference Digital Restructuring and Human (Re)action

Discovering operational decisions from data—a framework supporting decision discovery from data

Factors Shaping the Cashless Payment Ecosystem: Understanding the Role of Participating Actors

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