Evaluation of university scientific research ability based on the output of sci-tech papers: A D-AHP approach

Abstract

University scientific research ability is an important indicator to express the strength of universities. In this paper, the evaluation of university scientific research ability is investigated based on the output of sci-tech papers. Four university alliances from North America, UK, Australia, and China, are selected as the case study of the university scientific research evaluation. Data coming from Thomson Reuters InCites are collected to support the evaluation. The work has contributed new framework to the issue of university scientific research ability evaluation. At first, we have established a hierarchical structure to show the factors that impact the evaluation of university scientific research ability. Then, a new MCDM method called D-AHP model is used to implement the evaluation and ranking of different university alliances, in which a data-driven approach is proposed to automatically generate the D numbers preference relations. Next, a sensitivity analysis has been given to show the impact of weights of factors and sub-factors on the evaluation result. At last, the results obtained by using different methods are compared and discussed to verify the effectiveness and reasonability of this study, and some suggestions are given to promote China’s scientific research ability.

An Optimization Model for Construction Stage and Zone Plans of Rockfill Dams Based on the Enhanced Whale Optimization Algorithm

“…for each search agent Update a, A, C, I and P If1 (p < 0.5) If2 (|A| < 1) Update the position of the current search agent by the Equations (19) and (20) else if2 (|A| ≥ 1) Select a random search agent(Xrand) Update the position of the current search agent by the Equations (25) and (26) Update the position of the current search agent using the levy flight Equation 27end if2 else if1(p ≥ 0.5) Update the position of the current search by Equations (23) and (24) end if1 end for Check if any search agent goes beyond the search space, and amend it Calculate the fitness of each search agent Update X* if there is a better solution t = t + 1 end while return X*…”

“…D numbers is a new representation of uncertain information developed by Deng [21], which overcomes the deficiencies of the Dempster-Shafer evidence theory [22,23] and contains the exclusiveness hypothesis and completeness constraint. Improving the traditional AHP and Dempster-Shafer theories, the D-AHP method has been proven effective in various areas, including the evaluation of the scientific research ability of universities [24], curtain grouting efficiency assessment [25] and construction management [26]. Therefore, the D-AHP method is used in this paper to integrate hard data with subjective judgments, which may be uncertain and fuzzy in the MCDM process for flow shop construction schemes.…”

“…When p < 0.5, the EWOA updates the position of the current search agent with the shrinking encircling mechanism represented by Equations (19) and (20). • The strategy of bubble-net attacking the prey When p ≥ 0.5, the position of the current search agent is updated with the spiral updating position mechanism represented by Equations (23) and (24).…”

Economics of Decision Making: Exploring Analytical Hierarchical Process (AHP)

“…Munasinghe, Hemakumara & Mahanama (2017) used AHP in GIS application for finding the best residential lands in Ratnapura municipal council area of Sri Lanka [27]. Zong & Wang (2017) followed a D-AHP approach in their seminal work for evaluation of university scientific research ability based on the output of science and technology papers [28].…”

Review of the Literature on Multicriteria Methods Applied in the Field of Public Security

“…The literature indicates that the MCDA methods are used and applied to solve decision problems in many areas, as [2,11,19]: information and communication technologies [22]; business intelligence [23]; environmental risk analysis [24,25]; environmental impact assessment and environmental sciences [26]; water resources management [27][28][29]; solid waste management [30,31]; remote sensing [32,33]; flood risk management [34,35]; health technology assessment [36,37]; health care [38]; transportation [39]; nanotechnology research [40]; climate change [41]; energy [42,43]; international politics and laws [44]; Human resources [45]; Investment decisions [46]; performance and benchmarking [47]; Supplier selection [48]; E-commerce and m-commerce [49]; Agriculture and horticulture [50]; Chemical and biochemical engineering [51]; Software evaluation [52]; Network selection [53]; Policy, social and education [54]; HVAC systems and small scale energy management [55].…”