Purpose -This paper aims to improve the Commission of Higher Education (CHE)'s current university classification and develop the Thai Higher Education Classification Model (THEC-model). This study supports the CHE's initiative to ensure that the future is more science-oriented by encouraging universities to become National Research Universities (NRUs). Design/methodology/approach -The research applies empirical data and a statistical approach for the THEC-model's development. The model's results are then compared with the decisions reached earlier by the CHE in selecting public universities as research-intensive. Findings -The proposed classification criteria for NRUs consist of: research funding; the variety of instructional programmes; the level of instructional programmes; instructors and research staff body; and student body, which have significantly statistically influenced the differences in Y-variables: research output, citation, and research awards at alpha 0.05. The initial results show that eight universities are selected. The findings are consistent with the 2008 announcement, except for two universities. Practical implications -The developed THEC-model benefits academic researchers, university administrators, and policymakers for many reasons. For example, the THEC-model provides information for academic researchers to determine the important variables for a research university. The model provides information for policymakers to manage higher education effectively to raise the targets for a university. Originality/value -The THEC-model criteria were generated by reviewing the classification system in different locations. Such criteria could be applied extensively at domestic and international level. Moreover, the developed THEC-model is based on a statistical approach and empirical data improved the reliability and would be beneficial to the CHEs in Thailand for further improvement on research-focused HEI classification criteria in the future.

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Purpose -The paper aims to share experiences in Thailand's higher educational reforms in which academic excellence cannot be sustained without proper financial and fiscal consideration. The overall goal is to disclose the experiences and future issues facing public universities. Design/methodology/approach -The paper is based on actual involvement by Kasetsart University in assisting the Commission of Higher Education's (CHE) university reform efforts. In addition to projects supported financially by CHE, Kasetsart University has also participated as a committee member and an invited expert. The paper is narrative in nature. It begins by showing the positive impacts from higher education on a country's level of competitiveness, and the inter-relationship between higher education and innovation. The paper describes the country's recent major reform initiatives to achieve academic excellence and raises concerns over sustainability for public universities. Findings -The experiences from Thailand can be helpful for many countries as the country is moving from an industrial-based economy towards a knowledge-based economy. The major concern is that academic excellence for public universities cannot be sustained without more effective fiscal management and public-private partnership. Finally, despite the fact that the article is descriptive; the knowledge and lessons learned should be beneficial to scholars and practitioners who are interested in higher education reforms. Originality/value -Academic excellence has often been discussed within the context of quality and innovation without explicitly considering fiscal management. The potential use of public-private partnerships, which can improve the effectiveness of fiscal management, is revealed and discussed. The knowledge and lessons learned should be beneficial to scholars and practitioners who are interested in higher education reforms.

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The purpose of this study is to present the Geographic Information System (GIS) that supports land suitability evaluation for the development of target land in Bang Pu Sub-District Municipality in Samut Prakan Province in Thailand in order to promote the concept of the eco-industrial town. GIS was applied as the research methodology. SIEVE analysis was employed to evaluate suitable land. There are four factors involved in evaluating the land in this study. The first factor is the industrial density factor. The second factor is the industrial cluster factor. The third factor is the accessibility to green and recreation areas factor. The last factor is the risk to the urban ecology and environment factor. Each factor has three score levels in descending order: 3, 2, and 1. It was found that suitable target land could be found in five locations. There were 408 industrial factories on the target land (68.92% of 592 Group 3 factories). The findings are important information for the Samut Prakan Provincial Office to select suitable land, to make strategic and master plans, and to manage resources in order to maximize efficiency and develop the province into a model eco-industrial town in accordance with the province's vision.