Fuzzy and Genetic Algorithm-based Decision-making Approach for Collaborative Team Formation: A Study on User Acceptance using UTAUT

Forming an optimal collaborative team is achieved using members characteristics to improve team efficiency. A team’s performance may have a negative effect when a team is formed randomly. Moreover, it is quite impossible to achieve an optimal team manually as the formation can expand into countless possibilities. Hence, this paper presents a decision-making framework for collaborative team formation by incorporating Fuzzy Logic and Genetic Algorithm (Fuzzy-GA). The framework has been initiated by combining effective team formation factors such as skills, trust, leadership, and individual performance. Unified Theory of Acceptance and Use of Technology (UTAUT) is utilised to survey the readiness and technology acceptance of the organisations’ employees in adopting the proposed decision-making approach to form a collaborative team. The UTAUT survey had proven that behavioural intention (BI) had a positive impact on the performance expectancy (PE), effort expectancy (EE), social influence (SI) and facilitating conditions (FC). However, behavioural intention (BI) had a negative impact on the voluntariness of use (VU); thus the transformation of collaborative team formation must be further explored to increase the team’s voluntarism towards this automated collaborative team formation.

@article{Kassim2021,
  title     = {Fuzzy and Genetic Algorithm-based Decision-making Approach for Collaborative Team Formation: A Study on User Acceptance using UTAUT},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {12},
  number    = {8},
  year      = {2021},
  publisher = {The Science and Information Organization},
  author    = {Azleena Mohd Kassim and Norhanizah Minin and Yu-N Cheah and Fazilah Othman},
  doi       = {10.14569/IJACSA.2021.0120827},
  url       = {https://doi.org/10.14569/IJACSA.2021.0120827}
}