动态决策框架,用于评估市场潜力和创新创业公司的成功,基于使用r的营销研究方法

IF 0.5 Q4 ECONOMICS EGE ACADEMIC REVIEW Pub Date : 2023-07-18 DOI:10.32342/2074-5354-2023-2-59-14
O. Kofanov, Oleksandr V. Zozulov, Sergii O. Solntsev, Kateryna V. Bazherina
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引用次数: 0

摘要

目前,世界高度依赖技术进步和创新(TAI)作为经济增长、竞争力和整体社会进步的关键驱动力。高科技创业公司处于科技创新的前沿,他们开发新的产品和服务来满足消费者日益增长的需求。在过去的几十年里,创业公司的数量和质量都有了显著的提高,然而,他们仍然以高风险和低成功率而闻名,这往往导致投资者和创业者的经济损失。因此,本研究的目的是开发一个动态决策框架,以评估创新创业公司在其整个生命周期中的市场潜力和成功率,基于使用R编程语言的营销研究方法,为创业公司创始人、投资者、企业孵化器、创业加速器、技术中心等提供独特的解决方案。因此,基于t.l. Saaty的层次分析法(AHP),提出了一种评估创新创业公司市场潜力和成功率的新方法。考虑到AHP是基于专家意见的,建议将专家分为五组:科学专家、投资者代表、制造商代表、实践创业企业家、企业孵化器和创业加速器代表。每一组专家确定了创业吸引力的三个组成部分——创业项目的市场、营销和投资吸引力——的拟议标准和子标准之间的偏好程度。决策框架是基于“ahp”软件包在RStudio软件环境中创建和测试的,可以由创业公司创始人、投资者和其他利益相关者在项目的新信息可用时定期使用。
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DYNAMIC DECISION-MAKING FRAMEWORK FOR EVALUATING THE MARKET POTENTIAL AND SUCCESS OF INNOVATIVE STARTUPS ON THE BASIS OF A MARKETING RESEARCH APPROACH USING R
Currently, the world is highly dependent on technological advancements and innovations (TAI) being the key driver of economic growth, competitiveness, and overall societal progress. And high-tech startups are at the forefront of TAI, developing new products and services that meet the growing needs of consumers. Over the past decades, the quantity and quality of startups have increased significantly, however, they are still known for high risks and low success rates, which often lead to financial losses for investors and startup founders. Therefore, the aim of the study was to develop a dynamic decision-making framework for evaluating the market potential and success rates of innovative startups throughout their lifecycle on the basis of a marketing research approach using R programming language to provide a unique solution for startup founders, investors, business incubators, startup accelerators, tech hubs, etc. As a result, a new methodology for evaluating the market potential and success rates of innovative startups was proposed based on T. L. Saaty’s analytic hierarchy process (AHP) methodology. Taking into account the fact that AHP is based on expert opinions, it was proposed to divide experts into five groups – scientific specialists, investors representatives, manufacturers representatives, practicing startup entrepreneurs, business incubators & startup accelerators representatives. Each group of experts determined the degrees of preference between the proposed criteria and sub-criteria of each of the three components of startup attractiveness – market, marketing and investment attractiveness of the startup project. The decision-making framework was created and tested in the RStudio software environment based on the ‘ahp’ package and can be used by startup founders, investors, and other stakeholders on a regular basis as new information about their projects becomes available.
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EGE ACADEMIC REVIEW
EGE ACADEMIC REVIEW ECONOMICS-
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