ABSTRACT
The purpose of aggregation methods is to convert a list of objects of a set into a single object of the same set usually by an n-arry function, so-called aggregation operator. The key features of this work are the aggregation operators, because they are based on a novel set called Fermatean cubic fuzzy set (F-CFS). F-CFS has greater spatial scope and can deal with more ambiguous situations where other fuzzy set extensions fail to support them. For this purpose, the notion of F-CFS is defined. F-CFS is the transformation of intuitionistic cubic fuzzy set (I-CFS), Pythagorean cubic fuzzy set (P-CFS), interval-valued cubic fuzzy set, and basic orthopair fuzzy set and is grounded on the constraint that "the cube of the supremum of membership plus nonmembership degree is ≤1”. We have analyzed some properties of Fermatean cubic fuzzy numbers (F-CFNs) as they are the alteration of basic properties of I-CFS and P-CFS. We also have defined the score and deviation degrees of F-CFNs. Moreover, the distance measuring function between two F-CFNs is defined which shows the space between two F-CFNs. Based on this notion, the aggregation operators namely Fermatean cubic fuzzy-weighted averaging operator (F-CFWA), Fermatean cubic fuzzy-weighted geometric operator (F-CFWG), Fermatean cubic fuzzy-ordered-weighted averaging operator (F-CFOWA), and Fermatean cubic fuzzy-ordered-weighted geometric operator (F-CFOWG) are developed. Furthermore, the notion is applied to multiattribute decision-making (MADM) problem in which we presented our objectives in the form of F-CFNs to show the effectiveness of the newly developed strategy.
ABSTRACT
Drucker's knowledge-worker productivity theory and knowledge-based view of the firm theory are widely employed in many disciplines but there is little application of these theories in knowledge-based innovation among academic researchers. Therefore, this study intends to evaluate the effects of the knowledge management process on knowledge-based innovation alongside with mediating role of Malaysian academic researchers' productivity during the Pandemic of COVID-19. Using a random sampling technique, data was collected from 382 academic researchers. Questionnaires were self-administered and data was analyzed via Smart PLS-SEM. Knowledge management process and knowledge workers' productivity have a positive and significant relationship with the knowledge-based innovation among academic researchers during the Pandemic of COVID-19. In addition, knowledge workers' productivity mediates the relationship between the knowledge management process (knowledge creation, knowledge acquisition, knowledge sharing, and knowledge utilization) and knowledge-based innovation during the Pandemic of COVID-19. Results have also directed knowledge sharing as the key factor in knowledge-based innovation and a stimulating task for management discipline around the world during the Pandemic of COVID-19. This study provides interesting insights on Malaysian academic researchers' productivity by evaluating the effects of knowledge creation, acquisition, sharing, and application on the knowledge-based innovation among academic researchers during the Pandemic of COVID-19. These useful insights would enable policymakers to develop more influential educational strategies. By assimilating the literature of defined variables, the main contribution of this study is the evaluation of knowledge creation, acquisition, sharing, and utilization into knowledge-based innovation alongside the mediating role of knowledge workers productivity in the higher education sector of Malaysia during the Pandemic of COVID-19.