Chuanjin Ju, Songyan Hou, Dandan Shao, Zhijun Zhang and Zhangli Yu
The purpose of this report is to demonstrate open and distance education (ODE) can support poverty alleviation. Taking the practices of the Open University of China (the OUC) as…
Abstract
Purpose
The purpose of this report is to demonstrate open and distance education (ODE) can support poverty alleviation. Taking the practices of the Open University of China (the OUC) as an example, this paper aims to reveal how open universities make contributions to local residents in rural and remote areas.
Design/methodology/approach
Focusing on 25 poverty-stricken counties, the OUC had invested 58 million RMB to its learning centers in these counties from 2017 to 2020. The first one is to improve ICT and educational facilities in these learning centers. The second approach is to cultivate local residents with degree programs through ODE so as to promote local economic development. The third one is to design and develop training programs according to local context to meet the specific needs of local villagers.
Findings
After 3 years working, cloud-based classrooms and computer rooms have been set up. Bookstores have been founded and printed books have been donated. Hundreds of thousands of digital micro lectures have been supplied to these learning centers which have been improved and fully played their functions. Nearly 50,000 local residents have been directly benefited. Village leaders have helped lift local residents out of poverty. Poverty-stricken villagers have been financed to study on either undergraduate or diploma programs. Local residents have improved their skills by learning with the training programs offered by the OUC.
Originality/value
ODE is proved to be an effective way to eradicate poverty. Open universities are proved to be able to make contributions to social justice. By fulfilling its commitments to eliminate poverty within the national strategy framework, the OUC has built its brand nationwide.
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Keywords
Michael Adesi, Degraft Owusu-Manu, Frank Boateng, Michael Nii Addy and Ernest Kissi
The purpose of this study is to investigate the challenges of pricing quantity surveying (QS) professional services to enhance the understanding of practitioners in developing…
Abstract
Purpose
The purpose of this study is to investigate the challenges of pricing quantity surveying (QS) professional services to enhance the understanding of practitioners in developing strategies for the determination of fees for their services.
Design/methodology/approach
The paper adopts the quantitative approach by administering 150 survey questionnaires QS professionals out of which 79 questionnaires were retrieved for analysis using the mean, standard deviation, standard error and the Chi-Square test.
Findings
The study identified the challenges that continue to hamper the successful pricing of QS services as the inability to respond to changing contractual arrangements; lack of appropriate response to emerging services; slow response to changes in information and communication technology.
Research limitations/implications
This paper focused on QS professionals. Hence, a future study to encompass other professionals in the built environment will be novel.
Practical implications
The findings of this paper have the potential to motivate QS firms to develop solutions that address the challenges identified to improve the efficiency of their service delivery to clients. The paper also has the practical importance of opening up new frontiers of research that focus on pricing of professional services in the built environment in general.
Originality/value
The paper contributes to the awareness and understanding of QS professionals about the challenges that continue to hamper effective pricing of their services.
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Adela Socol and Iulia Cristina Iuga
This study aims to investigate the impact of brain drain on government AI readiness in EU member countries, considering the distinctive governance characteristics, macroeconomic…
Abstract
Purpose
This study aims to investigate the impact of brain drain on government AI readiness in EU member countries, considering the distinctive governance characteristics, macroeconomic conditions and varying levels of ICT specialists.
Design/methodology/approach
The research employs a dynamic panel data model using the System Generalized Method of Moments (GMM) to analyze the relationship between brain drain and government AI readiness from 2018 to 2022. The study incorporates various control variables such as GDP per capita growth, government expenditure growth, employed ICT specialists and several governance indicators.
Findings
The results indicate that brain drain negatively affects government AI readiness. Additionally, the presence of ICT specialists, robust governance structures and positive macroeconomic indicators such as GDP per capita growth and government expenditure growth positively influence AI readiness.
Research limitations/implications
Major limitations include the focus on a specific region of countries and the relatively short period analyzed. Future research could extend the analysis with more comprehensive datasets and consider additional variables that might influence AI readiness, such as the integration of AI with emerging quantum computing technologies and the impact of governance reforms and international collaborations on AI readiness.
Practical implications
The theoretical value of this study lies in providing a nuanced understanding of how brain drain impacts government AI readiness, emphasizing the critical roles of skilled human capital, effective governance and macroeconomic factors in enhancing AI capabilities, thereby filling a significant gap in the existing literature.
Originality/value
This research fills a significant gap in the existing literature by providing a comprehensive analysis of the interaction between brain drain and government AI readiness. It uses control variables such as ICT specialists, governance structures and macroeconomic factors within the context of the European Union. It offers novel insights for policymakers to enhance AI readiness through targeted interventions addressing brain drain and fostering a supportive environment for AI innovation.