Assessment of digital transformation indicators to prioritize sustainable financial services using q-rung orthopair fuzzy rough decision-making model
As the importance of environmental and social responsibility gains momentum, the financial sector is ever more
aware of its dynamic role in assisting the evolution to a low-carbon economy and a sustainable future. Digital
Transformation (DT) is the application of technologies for building innovative models, procedures and systems
that generates more profitable revenue, greater competitive advantage and better productivity. However, the DT
in sustainable financial services is slower than the other sectors. In this regard, very few articles have been
presented in the literature. This paper aims to assess the sustainable financial services based on the indicators of
DT using a decision support system. In this framework, the classical Alternative Ranking Order Method Accounting
for Two-Step Normalization (AROMAN) is extended from q-rung orthopair fuzzy rough information (q-
ROFRI) and combined with the decision-making experts (DMEs) and criteria weight-determination models. In
this method, firstly the DMEs’ weights are calculated using standard deviation-based tool. Second, the DMEs’
opinions are aggregated through novel Sugeno-Weber weighted averaging operator. In this regard, Sugeno-
Weber operators are proposed for q-ROFRI. Third, an integrated criteria weighting formula is determined in
which the objective weights are calculated using a distance measure-based model, while the subjective weights
are derived via relative closeness coefficient-based model with q-ROFRI. For this purpose, a novel distance
measure is proposed for q-ROFRI. Combining all these steps, a hybrid q-rung orthopair fuzzy rough AROMAN
method is introduced in which the weighted normalized ratings are computed through a new score function.
Further, an empirical study is presented to prioritize the sustainable financial services with respect to DT indicators’
assessment, which also shows the practicality and feasibility of presented method. The findings of this
work show that the option “green banking” is the most optimal choice among a set of five sustainable financial
services with the overall evaluation grade of 0.384, while the ranking order of options is green banking (0.384) >
values-based banking (0.3745) > ESG finance (0.3714) > climate finance (0.356) > social banking (0.3384). To
prove the stability of obtained results, sensitivity assessment is conducted on the basis of different values of
considered parameters. At last, comparison with extant methods is made to exemplify the robustness of proposed
framework under the context of q-ROFRI.
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