Mustafa Almuzel , Tugrul U Daim , Birol Yesilada , Marina Dabić , Gulin Idil Bolatan
{"title":"Developing an assessment model for entrepreneurship ecosystems using Hierarchical Decision Model","authors":"Mustafa Almuzel , Tugrul U Daim , Birol Yesilada , Marina Dabić , Gulin Idil Bolatan","doi":"10.1016/j.jik.2024.100562","DOIUrl":null,"url":null,"abstract":"<div><div>Entrepreneurship is a crucial driver of economic growth, necessitating the development of effective entrepreneurial ecosystems. However, there are significant gaps in the literature regarding the structured assessment of these ecosystems. This study addresses three main research gaps: the lack of structured evaluation methods, the need for a comprehensive analysis of ecosystem challenges from various perspectives, and the identification of critical factors essential for ecosystem growth. To bridge these gaps, the research introduces the Hierarchical Decision Model (HDM) as a universal assessment framework that can be adapted to different cities for creating effective entrepreneurial environments. The research methodology involved formulating perspectives and criteria through literature reviews and expert interviews. These perspectives and criteria were validated by subject matter experts and quantified by other experts to assign relative weights to each. Desirability curves were developed to measure these criteria, scored by experts. The practical applicability of the HDM was demonstrated through a case study of Riyadh, showcasing the model's effectiveness in real-world scenarios. Key findings include the identification and ranking of twenty critical criteria across five main perspectives, along with the development of desirability curves for each criterion. This provides a practical, easy-to-implement evaluation tool for policymakers. The contributions of this research are multifaceted: it introduces HDM to the field of entrepreneurship ecosystem assessment, offers a practical model for ecosystem performance measurement, and presents a framework for policy improvements. Additionally, it highlights the importance of continuous model refinement and the inclusion of diverse case studies for broader validation. Future research should focus on expanding the model to include sub-models for different regions and stages of startups’ development, ensuring its ongoing relevance and applicability. The findings show the most effective factors (perspectives and criteria) in developing entrepreneurial ecosystems and provide a method to measure the level of each criterion without requiring deep knowledge of the methodology, making it easier to implement the model in any ecosystem with any experts. The research offers an explicit case study evaluation of Riyadh's entrepreneurial ecosystem and provides recommendations for improvement areas. This study contributes to the technology management body of knowledge, particularly in the context of entrepreneurship ecosystems, presenting a universal assessment model for measuring ecosystem performance in any city. It creates an evaluation and improvement framework for policymakers to develop entrepreneurial ecosystems in their cities, ensuring continuous relevance and practicality through ongoing refinement and diverse case study applications.</div></div>","PeriodicalId":46792,"journal":{"name":"Journal of Innovation & Knowledge","volume":"9 4","pages":"Article 100562"},"PeriodicalIF":15.6000,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Innovation & Knowledge","FirstCategoryId":"91","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2444569X2400101X","RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BUSINESS","Score":null,"Total":0}
引用次数: 0
Abstract
Entrepreneurship is a crucial driver of economic growth, necessitating the development of effective entrepreneurial ecosystems. However, there are significant gaps in the literature regarding the structured assessment of these ecosystems. This study addresses three main research gaps: the lack of structured evaluation methods, the need for a comprehensive analysis of ecosystem challenges from various perspectives, and the identification of critical factors essential for ecosystem growth. To bridge these gaps, the research introduces the Hierarchical Decision Model (HDM) as a universal assessment framework that can be adapted to different cities for creating effective entrepreneurial environments. The research methodology involved formulating perspectives and criteria through literature reviews and expert interviews. These perspectives and criteria were validated by subject matter experts and quantified by other experts to assign relative weights to each. Desirability curves were developed to measure these criteria, scored by experts. The practical applicability of the HDM was demonstrated through a case study of Riyadh, showcasing the model's effectiveness in real-world scenarios. Key findings include the identification and ranking of twenty critical criteria across five main perspectives, along with the development of desirability curves for each criterion. This provides a practical, easy-to-implement evaluation tool for policymakers. The contributions of this research are multifaceted: it introduces HDM to the field of entrepreneurship ecosystem assessment, offers a practical model for ecosystem performance measurement, and presents a framework for policy improvements. Additionally, it highlights the importance of continuous model refinement and the inclusion of diverse case studies for broader validation. Future research should focus on expanding the model to include sub-models for different regions and stages of startups’ development, ensuring its ongoing relevance and applicability. The findings show the most effective factors (perspectives and criteria) in developing entrepreneurial ecosystems and provide a method to measure the level of each criterion without requiring deep knowledge of the methodology, making it easier to implement the model in any ecosystem with any experts. The research offers an explicit case study evaluation of Riyadh's entrepreneurial ecosystem and provides recommendations for improvement areas. This study contributes to the technology management body of knowledge, particularly in the context of entrepreneurship ecosystems, presenting a universal assessment model for measuring ecosystem performance in any city. It creates an evaluation and improvement framework for policymakers to develop entrepreneurial ecosystems in their cities, ensuring continuous relevance and practicality through ongoing refinement and diverse case study applications.
期刊介绍:
The Journal of Innovation and Knowledge (JIK) explores how innovation drives knowledge creation and vice versa, emphasizing that not all innovation leads to knowledge, but enduring innovation across diverse fields fosters theory and knowledge. JIK invites papers on innovations enhancing or generating knowledge, covering innovation processes, structures, outcomes, and behaviors at various levels. Articles in JIK examine knowledge-related changes promoting innovation for societal best practices.
JIK serves as a platform for high-quality studies undergoing double-blind peer review, ensuring global dissemination to scholars, practitioners, and policymakers who recognize innovation and knowledge as economic drivers. It publishes theoretical articles, empirical studies, case studies, reviews, and other content, addressing current trends and emerging topics in innovation and knowledge. The journal welcomes suggestions for special issues and encourages articles to showcase contextual differences and lessons for a broad audience.
In essence, JIK is an interdisciplinary journal dedicated to advancing theoretical and practical innovations and knowledge across multiple fields, including Economics, Business and Management, Engineering, Science, and Education.