TY - JOUR
T1 - Extending Choosing-by-Advantages Decision-Making Model with Case-Based Reasoning
AU - Scholtenhuis, Léon L. olde
AU - Naderpajouh, Nader
AU - Goh, Kai Chen
AU - Hayes, Jan
AU - Dorée, André
PY - 2025/5/7
Y1 - 2025/5/7
N2 - Choosing by advantages (CbyA) is increasingly used in multicriteria decision contexts to anchor group decisions to facts and ensure sound decision processes. However, limitations may arise in highly uncertain decision contexts that require extensive expert knowledge. For example, in the adoption of innovative technologies to ensure safety, decision-makers are challenged by the complexity and variety of information regarding novel technologies that they can mobilize to avoid major safety hazards. To overcome this problem, we propose extending the CbyA decision-making model with a case-based reasoning expert system that captures encoded technical expert knowledge. Using design science, we empirically investigated the use of this extended model in a case where safety engineers jointly review and select an innovative pipeline safety technology. We used interviews and reviewed the technological innovation literature to define the decision problem and relevant decision factors for this case. In subsequent design iterations, we created a prototype system and validated it through three rounds of user workshops. The designed prototype guides the selection of effective technologies and anchors this selection to the implementation advantages of the technologies. By prescribing a sequence of decision steps, this study further complements the innovation literature with a procedural model that guides innovation adoption decisions in practice. The proposed model is the first step in automating CbyA decision-making, thereby indicating how the integration of expert systems facilitates complex group decisions. This study encourages broader use of CbyA in highly uncertain contexts by demonstrating the applicability of this new decision paradigm.
AB - Choosing by advantages (CbyA) is increasingly used in multicriteria decision contexts to anchor group decisions to facts and ensure sound decision processes. However, limitations may arise in highly uncertain decision contexts that require extensive expert knowledge. For example, in the adoption of innovative technologies to ensure safety, decision-makers are challenged by the complexity and variety of information regarding novel technologies that they can mobilize to avoid major safety hazards. To overcome this problem, we propose extending the CbyA decision-making model with a case-based reasoning expert system that captures encoded technical expert knowledge. Using design science, we empirically investigated the use of this extended model in a case where safety engineers jointly review and select an innovative pipeline safety technology. We used interviews and reviewed the technological innovation literature to define the decision problem and relevant decision factors for this case. In subsequent design iterations, we created a prototype system and validated it through three rounds of user workshops. The designed prototype guides the selection of effective technologies and anchors this selection to the implementation advantages of the technologies. By prescribing a sequence of decision steps, this study further complements the innovation literature with a procedural model that guides innovation adoption decisions in practice. The proposed model is the first step in automating CbyA decision-making, thereby indicating how the integration of expert systems facilitates complex group decisions. This study encourages broader use of CbyA in highly uncertain contexts by demonstrating the applicability of this new decision paradigm.
KW - Choosing by advantages
KW - Innovation
KW - Pipeline
KW - Case based reasoning
KW - Group decision making
KW - Safety
UR - http://www.scopus.com/inward/record.url?scp=86000476006&partnerID=8YFLogxK
U2 - 10.1061/JMENEA.MEENG-6229
DO - 10.1061/JMENEA.MEENG-6229
M3 - Article
SN - 0742-597X
VL - 41
JO - Journal of management in engineering
JF - Journal of management in engineering
IS - 3
M1 - 05025001
ER -