Improving the Job Search Experience with Multi-Criteria Decision Making (MCDM) Visualization
Summary
Purpose and Research Question: This research aimed to develop and evaluate the usability of a novel job search visualization tool using a combination of a specific Multi-Criteria Decision Making (MCDM) tool and Attribute Scoring Functions (referred to as Qualitative Criteria Quantifier in this study) visualization. The central question addressed was: "How can the application of MCDM principles and advanced visualization techniques improve the efficacy and user experience in online job search processes?" This study aimed to enhance the job-seeking experience by offering a more intuitive and efficient approach to navigating the job market.
Methodology: The study employed a mixed-methods approach, focusing on the development and evaluation of the visualization tool. The development phase involved integrating the Qualitative Criteria Quantifier into LineUp, while the evaluation phase consisted of a user study with university students and young professionals. Data were collected through usability tests and interviews.
Key Findings: The user study revealed that usage of the Qualitative Criteria Quantifier increased participants’ reported confidence in their decisions compared to decisions made using only the MCDM tool. Furthermore, participants indicated that the visualization aspect helped them better understand job preferences and options.
Conclusion: The research suggests that combining Qualitative Criteria Quan- tifier with MCDM visualization enhances user experiences in the job-seeking domain. The objectives of developing a more efficient and informative tool were successfully met, demonstrating the potential applicability of MCDM in job search interfaces. These findings open new avenues for further exploration in digital interface design, emphasizing user-centric approaches in technology development.