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1 – 2 of 2Jungeun Cho, Donghee Kim, Soo W. Kim and Jungsuk Oh
Many companies are trying to acquire innovative technologies and relevant knowledge by sending R&D work overseas. Although recent research has been focusing on the aspects that…
Abstract
Many companies are trying to acquire innovative technologies and relevant knowledge by sending R&D work overseas. Although recent research has been focusing on the aspects that motivate MNCs to establish offshore R&D facilities, such as cost reduction and market expansion, little is known about external or circumstantial factors influencing the performance of global R&D activities. Searching for enhancers of offshore R&D facilities, we investigated the relationships between the performance of offshore R&D and the technological capabilities of a parent company, its home country, and its R&D hosting country. Both patent data of EU and the EU R&D scoreboard of 134 overseas R&D labs from 46 MNCs, dating from the period of 2003 to 2005, are used in the analysis. The same time period is applied in calculating the RTA of each country. Regression analysis results support our main hypothesis that the technological capabilities of the parent company and the hosting country positively affect the performance of overseas R&D.
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Suhanom Mohd Zaki, Saifudin Razali, Mohd Aidil Riduan Awang Kader, Mohd Zahid Laton, Maisarah Ishak and Norhapizah Mohd Burhan
Many studies have examined pre-diploma students' backgrounds and academic performance with results showing that some did not achieve the expected level of competence. This study…
Abstract
Purpose
Many studies have examined pre-diploma students' backgrounds and academic performance with results showing that some did not achieve the expected level of competence. This study aims to examine the relationship between students’ demographic characteristics and their academic achievement at the pre-diploma level using machine learning.
Design/methodology/approach
Secondary data analysis was used in this study, which involved collecting information about 1,052 pre-diploma students enrolled at Universiti Teknologi MARA (UiTM) Pahang Branch between 2017 and 2021. The research procedure was divided into two parts: data collecting and pre-processing, and building the machine learning algorithm, pre-training and testing.
Findings
Gender, family income, region and achievement in the national secondary school examination (Sijil Pelajaran Malaysia [SPM]) predict academic performance. Female students were 1.2 times more likely to succeed academically. Central region students performed better with a value of 1.26. M40-income students were more likely to excel with an odds ratio of 2.809. Students who excelled in SPM English and Mathematics had a better likelihood of succeeding in higher education.
Research limitations/implications
This research was limited to pre-diploma students from UiTM Pahang Branch. For better generalizability of the results, future research should include pre-diploma students from other UiTM branches that offer this programme.
Practical implications
This study is expected to offer insights for policymakers, particularly, the Ministry of Higher Education, in developing a comprehensive policy to improve the tertiary education system by focusing on the fourth Sustainable Development Goal.
Social implications
These pre-diploma students were found to originate mainly from low- or middle-income families; hence, the programme may help them acquire better jobs and improve their standard of living. Most students enrolling on the pre-diploma performed below excellent at the secondary school level and were therefore given the opportunity to continue studying at a higher level.
Originality/value
This predictive model contributes to guidelines on the minimum requirements for pre-diploma students to gain admission into higher education institutions by ensuring the efficient distribution of resources and equal access to higher education among all communities.
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