Template-Type: ReDIF-Article 1.0 Author-Name: Abdulai Inusah Author-X-Name-First: Abdulai Author-X-Name-Last: Inusah Author-Name: Esko Turunen Author-X-Name-First: Esko Author-X-Name-Last: Turunen Title: Strengthening preference ranking organisation method for enrichment evaluation with features of paraconsistent Pavelka style fuzzy logic Abstract: In this study, a new technique of complete ranking is proposed to augment the efficiency of the preference ranking organisation method for enrichment evaluation (PROMETHEE) methodology. The technique employs some ideas of the PROMETHEE method and paraconsistent Pavelka style fuzzy logic. To illustrate the effectiveness and efficiency of this novel technique, data on the performance of five mobile phone operators in Ghana is analysed and the results compared with the ranking of the conventional PROMETHEE I and II. Journal: Int. J. of Multicriteria Decision Making Pages: 211-232 Issue: 3 Volume: 8 Year: 2021 Keywords: paraconsistent logic; Pavelka logic; leaving and entering flows; evidence couple; evidence matrices; PROMETHEE; paraconsistent Pavelka style fuzzy logic; MV-algebra; complete ranking. File-URL: http://www.inderscience.com/link.php?id=119438 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijmcdm:v:8:y:2021:i:3:p:211-232 Template-Type: ReDIF-Article 1.0 Author-Name: Maksim Goman Author-X-Name-First: Maksim Author-X-Name-Last: Goman Author-Name: Stefan Koch Author-X-Name-First: Stefan Author-X-Name-Last: Koch Title: Multiplicative aggregation in managerial multi-attribute decision making Abstract: This paper focuses on aggregated performance of alternatives for management decision making. Assuming non-comparable criteria, we propose a composite indicator (CI) based on weighted product instead of commonly applied weighted average (WA). We extensively compare WA and CI in a real-world example of strategic decision making problem regarding enterprise resource planning system upgrade. The CI shows robustness to data scale change. User preference for a decision support method was examined based on complexity perception and willingness to use. The users are more likely to understand simple methods and apply them rather than methods that they do not comprehend, and the proposed approach is rated 'statistically not worse' than WA in this regard. Our findings should help managers in practical multi-attribute problems where alternative ranking based on a number of non-comparable properties is required. The alternative's rank is obtained in a mathematically correct way, and the aggregation does not need data normalisation. Journal: Int. J. of Multicriteria Decision Making Pages: 233-255 Issue: 3 Volume: 8 Year: 2021 Keywords: multi-attribute decision making; MADM; strategic decision making; software selection. File-URL: http://www.inderscience.com/link.php?id=119439 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijmcdm:v:8:y:2021:i:3:p:233-255 Template-Type: ReDIF-Article 1.0 Author-Name: Zghidi Imen Author-X-Name-First: Zghidi Author-X-Name-Last: Imen Title: MAOAM: multiple-aspect outstandingness appraisement methodology Abstract: In this contribution, we devise and apply a method for ranking multi-attribute alternatives. The suggested method is founded, inter alia, on the so-called positive and negative outstandingness predicates. This method, herein called multiple-aspect outstandingness appraisement method (MAOAM), employs in the aggregation phase a family of multivariate generalised weighted Heronian means having as special cases the Beliakov et al.'s (2008) generalised Heronian means as well as that of Chu and Liu (2015). With positive and negative outstandingness predicates and multivariate generalised weighted Heronian means, we are better equipped to rank rationally pre-specified alternatives. The feasibility and accuracy of the proposed method are shown in a practical application. Journal: Int. J. of Multicriteria Decision Making Pages: 256-275 Issue: 3 Volume: 8 Year: 2021 Keywords: multi-criteria decision making; MCDM; positive outstandingness predicate; negative outstandingness predicate; weighted generalised Heronian mean operator. File-URL: http://www.inderscience.com/link.php?id=119445 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijmcdm:v:8:y:2021:i:3:p:256-275 Template-Type: ReDIF-Article 1.0 Author-Name: Apostolos Arsenopoulos Author-X-Name-First: Apostolos Author-X-Name-Last: Arsenopoulos Author-Name: Vangelis Marinakis Author-X-Name-First: Vangelis Author-X-Name-Last: Marinakis Author-Name: Haris Doukas Author-X-Name-First: Haris Author-X-Name-Last: Doukas Title: Participatory multi-criteria decision analysis for sustainable energy planning Abstract: Public participation is constantly gaining attention in the context of decision-making process at local level, given that citizens are the main beneficiaries of the implemented policy measures. In this respect, stakeholder engagement has found itself at the core of the dialogue process for integrating multiple perspectives in sustainable energy planning, with the minimum social disruption. This paper aims to present a multi-criteria decision analysis (MCDA) framework for enhancing stakeholder engagement in the policy-making process, enabling decision-makers together with experts, citizens and other beneficiaries to jointly prioritise sustainable energy and climate actions to be implemented. The proposed framework allows marginalised population groups to express their views on issues of the everyday life, which are eventually incorporated in an MCDA analysis along with the experts' assessments. The proposed methodology is applied in a Greek municipality to showcase its functionalities and highlight future challenges that will make it even more integrated. Journal: Int. J. of Multicriteria Decision Making Pages: 276-290 Issue: 3 Volume: 8 Year: 2021 Keywords: stakeholder engagement; public participation; sustainable energy planning; decision-making; multi-criteria analysis; TOPSIS. File-URL: http://www.inderscience.com/link.php?id=119451 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijmcdm:v:8:y:2021:i:3:p:276-290