Search citation statements
Paper Sections
Citation Types
Year Published
Publication Types
Relationship
Authors
Journals
The innovation process typically follows a predefined sequence of phases: idea generation, screening, evaluation/selection, development, and launch/diffusion. This process exhibits a dynamic and cyclic structure. At each stage, potential ideas may undergo elimination or redefinition based on considerations such as their problem–solution fit or product–market fit. Consequently, the idea evaluation phase can be conducted continuously, involving varying numbers of potential ideas. To address the challenges associated with this process, a systematic approach for selecting the best new project ideas is essential. This study introduces the IF-ABAC method, which extends the alternative-by-alternative comparison-based (ABAC) method to the intuitionistic fuzzy (IF) environment. The proposed approach represents the first combination of fuzzy sets and ABAC within a group decision-making environment. The IF-ABAC method is employed during the evaluation phase, with the best–worst method determining the criteria weights. The study describes how the IF-ABAC approach adeptly manages changes in the set of alternatives after the decision process, addressing the dynamics inherent in decision-making environments. The study further includes an analysis of innovative business ideas in a real case study from Turkey, demonstrating the feasibility and efficiency of the proposed approach. A comprehensive sensitivity analysis is conducted to illustrate the stability and utility of the method. Finally, the results are compared with three other IF-based multi-criteria decision-making methods from the literature. The study concludes by asserting that the proposed IF-ABAC method provides a comprehensive and practical approach to select innovation project ideas in an environment of uncertainty and complexity.
The innovation process typically follows a predefined sequence of phases: idea generation, screening, evaluation/selection, development, and launch/diffusion. This process exhibits a dynamic and cyclic structure. At each stage, potential ideas may undergo elimination or redefinition based on considerations such as their problem–solution fit or product–market fit. Consequently, the idea evaluation phase can be conducted continuously, involving varying numbers of potential ideas. To address the challenges associated with this process, a systematic approach for selecting the best new project ideas is essential. This study introduces the IF-ABAC method, which extends the alternative-by-alternative comparison-based (ABAC) method to the intuitionistic fuzzy (IF) environment. The proposed approach represents the first combination of fuzzy sets and ABAC within a group decision-making environment. The IF-ABAC method is employed during the evaluation phase, with the best–worst method determining the criteria weights. The study describes how the IF-ABAC approach adeptly manages changes in the set of alternatives after the decision process, addressing the dynamics inherent in decision-making environments. The study further includes an analysis of innovative business ideas in a real case study from Turkey, demonstrating the feasibility and efficiency of the proposed approach. A comprehensive sensitivity analysis is conducted to illustrate the stability and utility of the method. Finally, the results are compared with three other IF-based multi-criteria decision-making methods from the literature. The study concludes by asserting that the proposed IF-ABAC method provides a comprehensive and practical approach to select innovation project ideas in an environment of uncertainty and complexity.
Assessing earthquake vulnerability is important for comprehending the potential consequences of seismic events on human life and property. In Türkiye, where earthquakes pose a significant threat, earthquake hazard analysis is especially critical. Multi-criteria decision-making (MCDM) methods play a crucial role in earthquake vulnerability assessments by providing a structured and transparent approach to decision-making, considering several criteria such as building conditions, population density, accessibility, and more. The integration of Geographic Information Systems (GIS) with MCDM methods provides a powerful approach to earthquake vulnerability assessment. GIS enables the management of geographic data and facilitates the rank of alternatives. In this study, a novel MCDM method called Dominance Based Decision Making (DBDM) was introduced and the DBDM method was applied to rank renewable energy sources. Besides, we focused on assessing earthquake vulnerability in Elazığ, Türkiye with DBDM. The research evaluates the earthquake vulnerability of Elazığ's districts and its' central district neighborhoods (NH) by considering building conditions and GIS-based risk and hazard factors with DBDM. This research offers a systematic and structured approach to earthquake vulnerability assessment, providing valuable insights for disaster preparedness and risk mitigation strategies. The integration of MCDM methods with GIS enhances decision-making processes and contributes to better-informed choices in the face of seismic risks. The study's results reveal that Sivrice is the most earthquake vulnerable district and Sali Baba, Esentepe, Fevzi Çakmak, Olgunlar, and Aksaray are among the NHs most vulnerable to earthquakes in the Central District of Elazığ.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.