In developing countries, the government has played an important role in supporting startup businesses in various aspects, primarily through tech-focused government agencies. With a limited budget, the government agencies are critical to select plenty of tech startups for funding, leaving only promising tech startups. Consequently, government agencies inevitably face decision-making problems under uncertain circumstances, like private equity investment situations. Reviewing the relevant decision-making frameworks has identified that a classical multiple criteria decision-making (MCDM) approach is currently used, assuming decision-makers acquire complete information that is not realistic. Moreover, both qualitative and quantitative criteria used in evaluating startup businesses cannot represent the uncertainty which is the fundamental nature of the decision-making circumstance. Thus, this article presents a decision-making framework of tech-focused government agencies for selecting startup businesses based on a fuzzy MCDM of Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). Besides, it identifies selection criteria with mixed research methodologies and determines weights of importance criteria by the Delphi method. Finally, the proposed framework results are fairness, transparency, and eliminating bias in decision-making, including more efficiency when the framework’s ranking orders significantly correspond with actual performances. HIGHLIGHTS Criteria for selecting start-up businesses in technological-focused government agencies A decision-making framework of tech-focused government agencies for selecting startup businesses based on a fuzzy MCDM of Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) The performance of the decision-making framework in selecting startup businesses to acquire high potential tech startups to drive the national economy GRAPHICAL ABSTRACT

This study aims to analyze factors that influence tech-focused government agencies’ decision-making process to evaluate tech start-ups for supporting funds. The conceptual framework was based on qualitative research principles from in-depth interviews with seven tech-focused government agencies and confirmed the factors used in their decision-making processes. It was confirmed that the main factors consist of entrepreneurship characteristics, product/service characteristics, market characteristics, financial consideration, and capability of the management team. Furthermore, our findings revealed additional factors that influence tech-focused government agencies’ decision-making process, namely technology and innovation, business potential, and personnel and team.

This study is a qualitative research with the use of case study methodology. This research is focused on the influence of entrepreneurial origin (opportunity or necessity) and firm’s innovation strategy (technology-push or market-pull) mixes on levels of product innovativeness in the cases of agro-industry entrepreneur (agro-preneur) in Thailand. The Origin-Strategy Mixes (OSM) model was developed from past literature to help identify possible mixes and explain the relationships. The paper used narrative approach in investigating on these relationships on three Thai organic-based agro-preneurs. The empirical study has shown that entrepreneurial origin and business strategy mixes do discordantly affect levels of product innovativeness. The study provides initial understanding on the importance of OSM influences, which can be applied to improve the competitiveness of agro-preneur in Thailand. The main limitation of this study is that only three cases in Thailand were investigated. To address this, future research should emphasize on larger sample size to improve generalization ability. The use of quantitative research to further verify the OSM model is also encouraged. Keywords: Entrepreneur; Innovation; Origin; Strategy; Agro-industry