Informatica

When it comes to building and sustaining a company’s financial base, financial officers (FOs) are indispensable. Consequently, hiring FOs should be fair and efficient to guarantee continuous economic growth. Evaluating their performance is crucial. The main objective of this research is to find the best financial officer. The research developed an innovative method based on the parametric representation of interval numbers to handle the uncertainty in real-life multi-criteria decision-making (MCDM) scenarios. This research considers all the essential characteristics of an FO to find the best candidate. We provide a new approach to determining the weight of each criterion and sub-criterion, the Parametric Interval Number-Analytic Hierarchy Process (PIVN-AHP). The next step in finding the best FO is to use a hybrid algorithm called PIVN-TOPSIS, which stands for Parametric Interval Number-Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). Several MCDM approaches, such as Simple Additive Weighting (SAW), Weighted Aggregated Sum Product Assessment (WASPAS), and the Weighted Sum Model (WSM), were used in a comparative study to confirm the ranks. We could also conduct a sensitivity study by shifting the weight of specific criteria. An FO’s evaluation focuses on key criteria and sub-factors, with PIVN-AHP used to calculate weights. “Accounts Knowledge” (C5) is the most significant criterion, while “Growth of Customer” (CW31) holds the highest sub-criterion weight.

Innovations in technology emerged with digitalization affect all sectors, including supply chain and logistics. The term “digital supply chain” has arisen as a relatively new concept in the manufacturing and service sectors. Organizations planning to utilize the benefits of digitalization, especially in the supply chain area, have uncertainties on how to adapt digitalization, which criteria they will evaluate, what kind of strategies should be developed, and which should be given more importance. Multi-criteria decision making (MCDM) approaches can be addressed to determine the best strategy under various criteria in digital transformation. Because of the need to capture this uncertainty, fermatean fuzzy sets (FFSs) have been preferred in the study to widen the definition domain of uncertainty parameters. Interval-valued fermatean fuzzy sets (IVFFSs) are one of the most often used fuzzy set extensions to cope with uncertainty. Therefore, a new interval-valued fermatean fuzzy analytic hierarchy process (IVFF-AHP) method has been developed. After determining the main criteria and sub-criteria, the IVFF-AHP method has been used for calculating the criteria weights and ranking the alternatives. By determining the most important strategy and criteria, the study provides a comprehensive framework of digital transformation in the supply chain.

Spherical fuzzy sets theory is useful and advantageous for handling uncertainty and imprecision in multiple attribute decision-making problems by considering membership, non-membership, and indeterminacy degrees. In this paper, by extending the classical linear assignment method, we propose a novel method called the spherical fuzzy linear assignment method (SF-LAM) to solve multiple criteria group decision-making problems in the spherical fuzzy environment. A ranking procedure consisting of aggregation functions, score functions, accuracy functions, weighted rank frequency, and a binary mathematical model are presented to determine the criterion-wise preferences and various alternatives’ priority order. The proposed method’s applicability and validity are shown through the selection problem among wind power farm locations. The proposed method helps managers to find the best location to construct the wind power plant based on the determined criteria. Finally, a comparative analysis is performed between the proposed spherical fuzzy linear assignment (SF-LAM) model and the spherical fuzzy analytic hierarchy process (SF-AHP) and spherical fuzzy WASPAS methods.

“Strategy implementation” is an inseparable part of strategic management process. Transformation strategies to typical operations and daily functions of staff exert a significant role in organization success. Balanced scorecard (BSC) and strategy map help senior managers to perfectly implement and monitor the accomplishment of the strategies by transforming strategies into operational programs. Using BSC and strategy map, the strategies are translated into some action plans which help the achievement of organizational goals and strategies. Due to shortage of resources, usually all organization's action plans cannot be implemented completely; therefore, managers should make use of some tools for assigning and selecting more efective action plans. In this paper, a procedure is suggested on the basis of grey TOPSIS to determine the preference of action plans to better aid managers in selection of the most effective action plans in a group decision making process.

The paper develops the idea of valuation capital market regulations efficiency. The performance and efficiency measurement idea is very widely spread in the private sector. However efficiency concept in a public sector is rather new approach and still underdeveloped. The goal of this paper is to reveal the possibilities to measure the efficiency of a public sector performance by applying some descriptive dependencies systems and by using the capital market regulations as an example to disclose the possible outcomes of that analysis process.