Prioritization of Factors Impacting Lecturer Research Productivity Using an Improved Fuzzy Analytic Hierarchy Process Approach

Abstract

Improving the scientific research productivity of lecturers is an important strategy contributing to improving the reputation of universities, attracting external funding sources, and improving the credibility of both domestic and international students. This study was carried out with the aim of determining the priority of the university’s governance factors that affect lecturers’ scientific research productivity. Six university governance factors were considered, including (i) research objectives and strategies, (ii) decentralization, (iii) leadership, (iv) support for research activities, (v) policy towards lecturers, and (vi) resources for research activities. In this study, an improved analytic hierarchy process method using generalized triangular fuzzy numbers and a centroid index was proposed. The research data were collected via in-depth interviews with experts and administrators at Vietnam National University, Hanoi (VNU). The results indicate that “resources for research activities” constitute the most important factor affecting the research productivity of lecturers at VNU, followed by research objectives and strategies and leadership.

Factors influencing the effectiveness of blended learning activities: A case study of Vietnam National University, Hanoi

“…Table 1 provides an overview of the factors and sub-factors used in this study. (5,6,7; 0.9) Very strong importance (V_S_I) (6,7,8; 0.9) Between V_S_I and A_I (7,8,9; 1.0) Absolute importance (A_I) (8,9,9; 1.0) In this study, Hue et al's (2022) approach was applied to evaluate the factors influencing the effectiveness of teaching using the BL model at VNU-Hanoi. The data for the study was collected through interviews with a panel of five experts who have many years of experience in managing training activities at VNU-Hanoi.…”

“…Hue et al ( 2022) proposed an improved fuzzy AHP approach that uses generalized fuzzy numbers to overcome the shortcomings of Chang's (1996) fuzzy AHP approach. The procedures of Hue et al's (2022) approach are as follows:…”

Penerapan Metode F-AHP dan F-TOPSIS Dalam Proses Seleksi Karyawan Untuk Bidang Teknologi Informasi

“…Untuk mengatasi tantangan ketidakpastian dan ketidakjelasan dalam pengambilan keputusan, AHP kemudian dikembangkan menjadi F-AHP dengan menerapkan logika fuzzy. Pendekatan ini sukses digunakan dalam berbagai konteks MCDM, seperti bidang pariwisata [4], model pengelolaan pengetahuan di universitas [5], serta produktivitas penelitian ilmiah dosen [6].…”