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

IF 2.9 Q2 MANAGEMENT
Iwan Iwut Tritoasmoro, U. Ciptomulyono, W. Dhewanto, Tatang Akhmad Taufik
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引用次数: 1

摘要

本文旨在探讨基于精益创业(LS)框架的创业孵化指标对创业企业孵化后生存的影响。本研究还分析了实施LS框架作为孵化度量的障碍。设计/方法/方法本研究采用混合方法。采用多元线性回归对2014-2017年在万隆科技园孵化的30家初创企业数据及孵化后的生存追踪数据进行定量研究。通过深入访谈12名受访者,包括孵化项目的创业毕业生、项目经理和导师,采用定性方法来完成解释性工作。本研究证实了几个LS孵化指标显著影响孵化后的创业可持续性。此外,本研究还解释了在应用LS学科时需要注意的几个问题,以提高孵化成功率。研究局限/启示研究仅在一个技术企业孵化器(TBI)模型中进行,该模型专注于新兴生态系统中的数字初创企业。在不同的情况和生态系统中,研究结果可能存在偏差。实践意义通过解释基于ls的孵化指标与初创企业生存的关系及其实施的挑战,可以为TBI管理层考虑和优先考虑干预策略提供参考,从而改善TBI的业务流程,提高孵化初创企业的成功率。社会影响创建大学初创企业和衍生产品已经成为印尼科技大学的一项关键绩效指标。大学中TBI机构作为技术商业化渠道的存在是必不可少的。孵化器成功地创建了一家新的技术型公司,将对周围环境产生重大的社会影响。创意/价值虽然LS方法在创业社区和从业者中很流行,但在大学的孵化过程中很少使用。这些结果可以作为大学tbi探索LS作为孵化管理工具来提高孵化初创企业成功率的参考。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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.
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来源期刊
CiteScore
5.90
自引率
8.70%
发文量
57
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