Decision Support for Succession Management Conferences Using Mobile Applications – Results from the 3rd Iteration of a Design Science Research Project

Author(s):  
Christian Tornack ◽  
Björn Pilarski ◽  
Matthias Schumann
Author(s):  
Philip Huysmans ◽  
Jan Verelst

In this paper, the authors present the results of a design science research project to develop a method for the evaluation of enterprise architecture projects. The methodology is based on the SAAM methodology, and applies concepts from the Normalized Systems theory to provide a more systematic way of performing architectural evaluations. They first discuss the problem statement, the objectives of our solution and the design of the method. The authors then demonstrate how the method has been applied in a real-life organization. Finally, they evaluate the proposed method using the criteria formulated in our problem statement.


Author(s):  
Ilia Bider ◽  
◽  
Erik Perjons ◽  
Paul Johannesson ◽  
◽  
...  

Author(s):  
Shah J Miah ◽  
Michael McGrath ◽  
Don Kerr

This paper presents a contemporary literature review of design science research (DSR) studies in the domain of decision support systems (DSS) development. The latest studies in the DSS design domain claim that DSR methodologies are the most popular design approach, but many details are still yet to be revealed for supporting this claim. In particular, it is important to thoroughly investigate the trends in either the form or deeper insights in use of DSR in this field. The aim of this study is to analyse the existing DSS design science studies to reveal insights into the use of DSR, so that we can outline research agenda for a special issue, based on findings of analysis. We selected articles (from 2005 to 2014) that were published in seven selected premier IS journals (ranked as A* in the ABDC journal ranking). The selected 57 sample articles are representative of DSS design studies that used DSR in theorising, designing, implementing, and evaluating DSS solutions. We discuss the theoretical positions of DSR for DSS development through six categories: DSS artefacts, DSR methods, DSR views, user involvement, DSS design innovations and problem domains. The findings indicate that new studies are needed to fill the knowledge gap in DSS design science, for more solid theoretical basis in near future.


2014 ◽  
Vol 27 (3) ◽  
pp. 259-279 ◽  
Author(s):  
Shah J. Miah ◽  
Don Kerr ◽  
Liisa von Hellens

Purpose – The knowledge of artefact design in design science research can have an important application in the improvement of decision support systems (DSS) development research. Recent DSS literature has identified a significant need to develop user-centric DSS method for greater relevance with respect to context of use. The purpose of this paper is to develop a collective DSS design artefact as method in a practical industry context. Design/methodology/approach – Under the influence of goal-directed interaction design principles the study outlines the innovative DSS artefact based on design science methodology to deliver a cutting-edge decision support solution, which provides user-centric provisions through the use of design environment and ontology techniques. Findings – The DSS artefact as collective information technology applications through the application of design science knowledge can effectively be designed to meet decision makers’ contextual needs in an agricultural industry context. Research limitations/implications – The study has limitations in that it was developed in a case study context and remains to be fully tested in a real business context. It is also assumed that the domain decisions can be parameterised and represented using a constraint programming language. Practical implications – The paper concludes that the DSS artefact design and this development successfully overcomes some of the limitations of traditional DSS such as low-user uptake, system obsolescence, low returns on investment and a requirement for continual re-engineering effort. Social implications – The design artefact has the potential of increasing user uptake in an industry that has had relevancy problems with past DSS implementation and has experienced associated poor uptake. Originality/value – The design science paradigm provides structural guidance throughout the defined process, helping ensure fidelity both to best industry knowledge and to changing user contexts.


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