Startup evaluation criteria and startup selection model for corporate incubators

Abstract

The main goal of this thesis is to develop a thorough evaluation system for choosing entrepreneurs to receive support from corporate incubators. A methodical approach is taken in the design of the research, which combines material from academic research with input from external sources to develop a specialized evaluation procedure with the assistance of industry expertise. An in-depth literature review was the first step in the methodology, during which keywords are utilized to locate research that is pertinent to the evaluation of startups. The results of the search are sorted according to the subjects, and then they are further narrowed by the examination of the titles and abstracts. The selection is narrowed down to a final set of 28 articles for the purpose of conducting in-depth reading and analysis as a result of this approach. Following the selection of articles, the process of data extraction and refining is carried out in order to extract a full set of criteria from the articles. The elimination of duplicates and criteria that are similar results in the compilation of a list of 65 separate criteria. Criteria that are excessively specific are grouped together, which ultimately results in the consolidation of 46 criteria into a more refined form. In order to determine which criteria are the most important, a frequency analysis is carried out, which ultimately leads to the establishment of a total of 38 critical criteria. This set of requirements are broken down into five distinct categories: the team, the market, the idea or product, the finances, and the strategy. For the purpose of obtaining the perspectives of specialists from the Turkish entrepreneurship ecosystem regarding the significance of each evaluation criterion, surveys are carried out with the assistance of experts. A survey that is conducted via Google Forms is devised, and information is gathered from professionals who have specialized experience in the evaluation of startups. After that, the data that was collected is examined in order to determine which criteria received low scores and then eliminate them, another intermediate step is added that is corporate expert interviews to refine the criteria and move the perspective from general to corporate, completing the collection of evaluation criteria. In the end, 29 distinct criteria had been listed within 5 groups. Fuzzy Analytic Hierarchy Process (Fuzzy AHP) is utilized as a multi-criteria decision making method in order to carry out the process of weighting the evaluating criteria. A selected group of experts from various corporations' entrepreneurship and innovation departments, conducted pairwise comparisons to determine the relative importance of each criterion. This stage ensures that the evaluation criteria are weighted appropriately, reflecting the nuanced perspectives of individuals who have extensive expertise in the field. Finally, the team criteria category had a weight value of 31\%, the market criteria category had a weight value of 25\%, the idea/product criteria category had a weight value of 21\%, the finance criteria category had a weight value of 8\%, and the strategy criteria category had a weight value of 15\%. In the selection and ranking stage of the model, the TOPSIS method is utilized to rank the startups based on the predetermined framework of evaluation criteria. At this stage, it is possible to determine which alternative is the most suitable by calculating the degree to which it is similar to both the positive and negative ideal solutions. In general, the thesis offers a thorough and expertly validated methodology for the evaluation of startups that is specifically suited to meet the startup selection requirements of corporate incubators and accelerators. Within the context of the evaluation process, the systematic approach maintains the integrity and relevance of the review process by taking into account the various elements that contribute to the success of startups. In the context of business incubation and acceleration, the framework provides a comprehensive and individualized solution for selecting entrepreneurs through combining the theoretical framework an the practical knowledge accumulated in the industry. In conclusion, this thesis makes a contribution to the startup evaluation topic within the entrepreneurship research field by offering a structured startup selection criteria framework that includes the methodological process of multi-method MCDM-based startup selection model. Incorporating a review of the relevant literature, data extraction and refinement, expert surveys, criterion weighting, and the implementation of the TOPSIS approach are all components of the methodology. In order to provide a comprehensive evaluation of startups, the evaluation framework that was developed takes into account a variety of criteria, including the team, the market, the idea or product, the finances, and the strategy categories. It is possible for corporate incubators and accelerators to make use of this framework in order to choose and support promising entrepreneurs in an efficient manner. As for the practical implications, these criteria set and selection model can serve as a guide for startups to use it as a self-assessment tool to point their weak spots in the eyes of incubators or investors etc. Also for the policy implications; in the national and industrial level, this study can shed light on the prioritized specialities among the startups in the field so that governmental entrepreneurship support mechanisms or entrepreneurship education curriculum can be improved.