Iwan Iwut Tritoasmoro, U. Ciptomulyono, W. Dhewanto, Tatang Akhmad Taufik
{"title":"基于精益创业的孵化指标对孵化后创业可行性的决定因素:基于案例的研究","authors":"Iwan Iwut Tritoasmoro, U. Ciptomulyono, W. Dhewanto, Tatang Akhmad Taufik","doi":"10.1108/jstpm-12-2021-0187","DOIUrl":null,"url":null,"abstract":"\nPurpose\nThis paper aims to investigate the effect of business incubation metrics based on an adaptation of the lean start-up (LS) framework on start-up survival after incubation. This study also analyzes the obstacles in implementing the LS framework as incubation metrics.\n\n\nDesign/methodology/approach\nThis study uses mixed methods. Quantitative research using multiple linear regression was applied to the data of 30 start-ups incubated at Bandung Techno Park for the 2014–2017 period and survival tracking data after the incubation. A qualitative approach to complete the explanatory work was conducted through in-depth interviews with 12 respondents, including start-up graduates from the incubation program, program managers and mentors.\n\n\nFindings\nThis study confirms that several LS incubation metrics significantly affect start-up sustainability after incubation. In addition, this study also explains several problems in applying the LS discipline that needs attention to increase incubation success.\n\n\nResearch limitations/implications\nResearch was conducted only at one technology business incubator (TBI) model that focuses on digital start-ups in the emerging ecosystem. Research results can be biased in different situations and ecosystems.\n\n\nPractical implications\nThe explanation of the relationship of LS-based incubation metrics to the survival of start-ups, as well as the challenges of their implementation, can be a reference for TBI management to consider and prioritize intervention strategies, thereby improving TBI’s business processes and increasing the success rate of incubated start-ups.\n\n\nSocial implications\nThe creation of university start-ups and spin-offs has become a key performance indicator mandatory for technology universities in Indonesia. The existence of TBI institutions in universities as channels of technology commercialization is essential. The incubator’s success in creating a new technology-based company will have a significant social impact on the surrounding environment.\n\n\nOriginality/value\nAlthough the LS method is popular in start-up communities and among practitioners, it is rarely used in the incubation process at universities. These results can be considered for university TBIs to explore LS as an incubation management tool to increase the success rate of incubated start-ups.\n","PeriodicalId":45751,"journal":{"name":"Journal of Science and Technology Policy Management","volume":" ","pages":""},"PeriodicalIF":2.9000,"publicationDate":"2022-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Determinant factors of lean start-up-based incubation metrics on post-incubation start-up viability: case-based study\",\"authors\":\"Iwan Iwut Tritoasmoro, U. Ciptomulyono, W. Dhewanto, Tatang Akhmad Taufik\",\"doi\":\"10.1108/jstpm-12-2021-0187\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\\nPurpose\\nThis paper aims to investigate the effect of business incubation metrics based on an adaptation of the lean start-up (LS) framework on start-up survival after incubation. This study also analyzes the obstacles in implementing the LS framework as incubation metrics.\\n\\n\\nDesign/methodology/approach\\nThis study uses mixed methods. Quantitative research using multiple linear regression was applied to the data of 30 start-ups incubated at Bandung Techno Park for the 2014–2017 period and survival tracking data after the incubation. A qualitative approach to complete the explanatory work was conducted through in-depth interviews with 12 respondents, including start-up graduates from the incubation program, program managers and mentors.\\n\\n\\nFindings\\nThis study confirms that several LS incubation metrics significantly affect start-up sustainability after incubation. In addition, this study also explains several problems in applying the LS discipline that needs attention to increase incubation success.\\n\\n\\nResearch limitations/implications\\nResearch was conducted only at one technology business incubator (TBI) model that focuses on digital start-ups in the emerging ecosystem. Research results can be biased in different situations and ecosystems.\\n\\n\\nPractical implications\\nThe explanation of the relationship of LS-based incubation metrics to the survival of start-ups, as well as the challenges of their implementation, can be a reference for TBI management to consider and prioritize intervention strategies, thereby improving TBI’s business processes and increasing the success rate of incubated start-ups.\\n\\n\\nSocial implications\\nThe creation of university start-ups and spin-offs has become a key performance indicator mandatory for technology universities in Indonesia. The existence of TBI institutions in universities as channels of technology commercialization is essential. The incubator’s success in creating a new technology-based company will have a significant social impact on the surrounding environment.\\n\\n\\nOriginality/value\\nAlthough the LS method is popular in start-up communities and among practitioners, it is rarely used in the incubation process at universities. These results can be considered for university TBIs to explore LS as an incubation management tool to increase the success rate of incubated start-ups.\\n\",\"PeriodicalId\":45751,\"journal\":{\"name\":\"Journal of Science and Technology Policy Management\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":2.9000,\"publicationDate\":\"2022-09-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Science and Technology Policy Management\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1108/jstpm-12-2021-0187\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"MANAGEMENT\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Science and Technology Policy Management","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1108/jstpm-12-2021-0187","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MANAGEMENT","Score":null,"Total":0}
Determinant factors of lean start-up-based incubation metrics on post-incubation start-up viability: case-based study
Purpose
This paper aims to investigate the effect of business incubation metrics based on an adaptation of the lean start-up (LS) framework on start-up survival after incubation. This study also analyzes the obstacles in implementing the LS framework as incubation metrics.
Design/methodology/approach
This study uses mixed methods. Quantitative research using multiple linear regression was applied to the data of 30 start-ups incubated at Bandung Techno Park for the 2014–2017 period and survival tracking data after the incubation. A qualitative approach to complete the explanatory work was conducted through in-depth interviews with 12 respondents, including start-up graduates from the incubation program, program managers and mentors.
Findings
This study confirms that several LS incubation metrics significantly affect start-up sustainability after incubation. In addition, this study also explains several problems in applying the LS discipline that needs attention to increase incubation success.
Research limitations/implications
Research was conducted only at one technology business incubator (TBI) model that focuses on digital start-ups in the emerging ecosystem. Research results can be biased in different situations and ecosystems.
Practical implications
The explanation of the relationship of LS-based incubation metrics to the survival of start-ups, as well as the challenges of their implementation, can be a reference for TBI management to consider and prioritize intervention strategies, thereby improving TBI’s business processes and increasing the success rate of incubated start-ups.
Social implications
The creation of university start-ups and spin-offs has become a key performance indicator mandatory for technology universities in Indonesia. The existence of TBI institutions in universities as channels of technology commercialization is essential. The incubator’s success in creating a new technology-based company will have a significant social impact on the surrounding environment.
Originality/value
Although the LS method is popular in start-up communities and among practitioners, it is rarely used in the incubation process at universities. These results can be considered for university TBIs to explore LS as an incubation management tool to increase the success rate of incubated start-ups.