A Fuzzy Group Prioritization Method for Deriving Weights and its Software Implementation

Several Multi-Criteria Decision Making (MCDM) methods involve pairwise comparisons to obtain the preferences of decision makers (DMs). This paper proposes a fuzzy group prioritization method for deriving group priorities/weights from fuzzy pairwise comparison matrices. The proposed method extends the Fuzzy Preferences Programming Method (FPP) by considering the different importance weights of multiple DMs . The elements of the group pairwise comparison matrices are presented as fuzzy numbers rather than exact numerical values, in order to model the uncertainty and imprecision in the DMs’ judgments. Unlike the known fuzzy prioritization techniques, the proposed method is able to derive crisp weights from incomplete and fuzzy set of comparison judgments and does not require additional aggregation procedures. A prototype of a decision tool is developed to assist DMs to implement the proposed method for solving fuzzy group prioritization problems in MATLAB. Detailed numerical examples are used to illustrate the proposed approach

Analysis of Takaful vs. Conventional insurance firms’ efficiency: Two-stage DEA of Saudi Arabia’s insurance market

Despite the remarkable growth in the insurance industry over the past two decades, few studies evaluate the performance of Takaful vs. conventional insurance firms with focus on the standard structure of production as a two-stage process, that is, operations and profitability. Thus, this research examines the performance of Saudi Arabia’s insurance market using a two-stage data envelopment analysis to assess the efficiency of the two production stages and accordingly, define the leader stage. The empirical results obtained using data for 26 conventional and seven Takaful insurance firms for 2014–2017 indicate declining average efficiency scores for both firm types. In other words, Saudi Arabia’s insurance market warrants new consolidation and foreign participation regulations to assist firms in becoming dynamic and strong. This study makes a significant contribution given the dearth of an exclusive analysis on the two-stage efficiency of Saudi Arabia’s Takaful and conventional insurance firms. Further, it offers key implications for decision makers, regulators, and managers associated with the insurance industry in Saudi Arabia and other emerging insurance markets

A fuzzy group prioritization method for deriving weights and its software implementation

Several Multi-Criteria Decision Making (MCDM) methods involve pairwise comparisons to obtain the preferences of decision makers (DMs). This paper proposes a fuzzy group prioritization method for deriving group priorities/weights from fuzzy pairwise comparison matrices. The proposed method extends the Fuzzy Preferences Programming Method (FPP) by considering the different importance weights of multiple DMs. The elements of the group pairwise comparison matrices are presented as fuzzy numbers rather than exact numerical values, in order to model the uncertainty and imprecision in the DMs’ judgments. Unlike the known fuzzy prioritization techniques, the proposed method is able to derive crisp weights from incomplete and fuzzy set of comparison judgments and does not require additional aggregation procedures. A prototype of a decision tool is developed to assist DMs to implement the proposed method for solving fuzzy group prioritization problems in MATLAB. Detailed numerical examples are used to illustrate the proposed approach